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A Role for Adult Born Neurons in Memory Processing
by
Maithe Arruda Carvalho
A thesis submitted in conformity with the requirements for the degree of Doctorate of Philosophy
Institute of Medical Science
University of Toronto
© Copyright by Maithe Arruda Carvalho 2012
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A Role for Adult Born Neurons in Memory Processing
Maithe Arruda Carvalho
Doctor of Philosophy
Institute of Medical Science
University of Toronto
2012
Abstract
Throughout adulthood, the brain continuously generates new neurons in two neurogenic
regions: the subgranular zone of the hippocampus and the subventricular zone on the lateral wall
of the lateral ventricles. These neurons have been shown to integrate into hippocampal and
olfactory bulb circuitry, respectively. Nevertheless, their specific contribution to hippocampal or
olfactory function remains unclear. Previous studies have tried to assess adult born neuron
contribution to memory function by suppressing neurogenesis and examining the impact on
memory acquisition. Although ablation of neurogenesis has been shown to impair performance
in hippocampus dependent and olfactory tasks, many studies fail to see an effect. Compensation
from residual cells in either system after ablation may underlie these contradictory findings.
Thus, a more direct approach to answer this question would be to ablate adult born neurons after
their incorporation into the memory trace. To do this, we established a double transgenic strategy
to tag and selectively ablate adult born neurons with temporal control. Ablation of a population
of predominantly mature, adult generated dentate granule cells did not prevent acquisition of
contextual fear conditioning or Morris Water Maze memories. Removal of that same population
of cells after training, however, led to memory degradation in three hippocampus dependent
tasks. Similarly, post-training ablation of a population of adult generated olfactory interneurons
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impaired performance in an associative odour memory task, whereas pre-training ablation had no
impact. Together, these data show that adult generated neurons form a crucial component of both
hippocampal and olfactory memory traces.
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Acknowledgments
Paul, it is hard to put into perspective how much I have learned and grown in the five years since
I started in your lab. You have given me the opportunity to do a level of research I never
imagined, accompanied by an enthusiasm for each experiment I never thought I would have.
Thank you for all the opportunities, discussions, for disagreeing (and occasionally agreeing) with
me, for challenging me into becoming a better scientist. I have learned so much about the
elegance, hardship and finesse of scientific life from your example, and for all you have given
me I will forever be indebted.
Sheena, you have always supported and encouraged me throughout these years. I cannot thank
you enough for your generosity and openness in sharing with me your experience, giving me
precious advice, and all our discussions that have meant so much to me.
James Ellis and Freda Miller, thank you so much for your invaluable input and support over
these years, and for patiently heping me with our ‗schedule wars‘.
Cindi Morshead and Amelia Eisch, thank you for generously accepting to be reviewers for this
thesis, and sharing your suggestions to improve it.
Masanori Sakaguchi, who taught me so much in my first few years in the lab, whose lessons I‘ll
always carry with me and always be thankful.
Katherine Akers, who was such a crucial part of this thesis on all its levels, thank you so much
for being such a great partner (and editor!) and having the patience to work with me in both these
projects and put so much effort in revising this text.
Mika Yamamoto, you have been with us from the beginning, through the toughest times in our
hippocampal project. I have such admiration for you and wish to thank you so, so much for the
enormous help (even when I‘m not looking) and support throughout so many years.
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Toni DeCristofaro and Russell Braybon, who do such an amazing job managing the lab. Not a
single line in this thesis could have been written without your help and support, for which I
cannot thank or appreciate you enough.
The Josselyn/Frankland lab past and present members: Leigh Botly, Christy Cole, Loren DeVito,
Matthew Florczynski, Anna Gianlorenco, Liz Hsiang, Rachel Kang, Aneta Krakowski,
Alexander Marsolais, Tetyana Pekar, Asim Rashid, Blake Richards, Adam Santoro, Dani Sarkis,
Jason Snyder, Scellig Stone, Matt Tran, Joel Ross, Michel Van den Oever, Gisella Vetere, Afra
Wang, Chen Yan, Kirill Zaslavsky, Jeremy Zung, for all their support, without whom this thesis
would not have been possible.
Special thanks to: Ann Victory, who saved my life in so many burocratic situations and ensured
our collective sanity in our tuesday night movies; Catia Teixeira, Anne Wheeler and Melanie
Sekeres, who always helped and supported me through these years and without whom life is half
as amusing; Adelaide Yiu, who made everything seem so easy and simple with her generosity;
Jonathan Epp and Axel Guskjolen, who help me so much with our CamKII project (and weird
stem cell questions, Jon…); Alonso Martinez, who spent so much time troubleshooting
stereological tangles, Yosuke Niibori, who has patiently and generously assisted us in different
steps of these papers; Derya Sargin, for our conversations over tea or breaks in fear conditioning;
Leonardo Restivo and Valentina Mercaldo (and Sammy), for all their help and kindness inside
and outside the lab; Gemma Higgs, without your friendship and unconditional support these
years would have been so difficult, thank you!
Analena Mileo, Anelise Leite, Manuela Roitman, Marina Verjovsky, Matias Lopez, Nina
Barbieri, Maria Paula Almeida, Andre Ferracini e Gisele Neves, Silvia Rebello, amigos de toda
vida, nunca se movendo de mim, nao importa aonde va o trem.
Monika, thank you for being everything. For your never ending patience, unbounded support and
everlasting generosity; I truly hope you know.
Renée e Apo, René e Angela, apesar da distancia e da saudade voces nunca questionaram minhas
escolhas e sempre me encorajaram a viver minha vida como eu a quero. Nao tenho palavras para
expressar a honra, gratidao e orgulho de ter voces comigo, sempre. Voces sao o exemplo e a
motivacao, a base e a escada. Espero com amor muitos outros sonhos para compartilharmos.
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Table of Contents
Contents
Acknowledgments .......................................................................................................................... iv
Table of Contents ........................................................................................................................... vi
List of Abreviations ....................................................................................................................... ix
List of Tables ................................................................................................................................. xi
List of Figures ............................................................................................................................... xii
Chapter 1 Literature Review ........................................................................................................... 1
1.1 Memory ............................................................................................................................... 1
1.1.1 Founding concepts .................................................................................................. 1
1.1.2 Memory gradients and grades of memory .............................................................. 5
1.1.3 Memory consolidation ............................................................................................ 8
1.2 Hippocampus .................................................................................................................... 12
1.2.1 The hippocampal formation: an overview ............................................................ 13
1.2.2 Hippocampal functions: we are more than just our memories ............................. 14
1.2.3 Hippocampal functions: learning and memory ..................................................... 16
1.2.4 Dentate gyrus ........................................................................................................ 25
1.3 Adult neurogenesis ............................................................................................................ 30
1.3.1 History ................................................................................................................... 30
1.3.2 Hippocampal neurogenesis ................................................................................... 32
1.3.3 Olfactory neurogenesis ......................................................................................... 50
Chapter 2 Aims/hypotheses .......................................................................................................... 61
Chapter 3 General methods ........................................................................................................... 63
3.1 Cell culture ......................................................................................................................... 63
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3.2 Mice .................................................................................................................................... 63
3.3 Drugs .................................................................................................................................. 65
3.4 Immunohistochemistry ....................................................................................................... 65
3.5 Imaging and quantification ................................................................................................ 66
3.7 General behavioral apparatus and procedures .................................................................... 67
3.8 Specific experimental protocols ......................................................................................... 70
3.9 Data analysis ...................................................................................................................... 74
Chapter 4 Posttraining Ablation of Adult Generated Neurons Degrades Previously Acquired
Memories.................................................................................................................................. 75
4.1 Abstract .............................................................................................................................. 75
4.2 Introduction ........................................................................................................................ 76
4.3 Results ................................................................................................................................ 77
4.3.1 Murine cells are insensitive to DT ........................................................................... 77
4.3.2 Characterization of ‗tag and ablate‘ mice ................................................................ 78
4.3.3 Post-training ablation of tagged neurons degrades a contextual fear memory ........ 84
4.3.4 Pre-training ablation of tagged neurons does not prevent formation of new
contextual fear memory ........................................................................................ 87
4.3.5 Post-training ablation of tagged neurons degrades spatial memory ........................ 89
4.3.6 Post-training ablation of tagged neurons degrades remote spatial memory ............ 92
4.3.7 Post-training ablation degrades visual discrimination memory ............................... 92
4.4 Discussion .......................................................................................................................... 95
Chapter 5 Post-training Ablation of Adult Generated Olfactory Interneurons Impairs
Associative Odour Memory Expression .................................................................................. 99
5.1Abstract ............................................................................................................................... 99
5.2 Introduction ........................................................................................................................ 99
5.3 Results .............................................................................................................................. 101
5.3.1 CREERT2
expression is restricted to neural stem cells ............................................ 101
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5.3.2 Characterization of the tagging .............................................................................. 101
5.3.3 Post-training ablation of adult born olfactory interneurons impairs associative
olfactory memory expression .............................................................................. 103
5.3.4 Pre-training ablation of adult born olfactory interneurons does not interfere with
associative olfactory memory acquisition ........................................................... 106
5.4 Discussion ........................................................................................................................ 108
Chapter 6 General Discussion ..................................................................................................... 111
6.1 Summary of Results ......................................................................................................... 111
6.2 Pre vs. Posttraining........................................................................................................... 112
6.3 Erasure vs. Degradation ................................................................................................... 114
6.4 Drowning by numbers ...................................................................................................... 116
6.5 Avenues for silencing neurons ......................................................................................... 117
6.6 The unbearable lightness of inconsistencies .................................................................... 120
6.6.1 In the hippocampus ................................................................................................ 120
6.6.2 In the olfactory system ........................................................................................... 122
6.7 What are aDGCs (and DGCs) really good for? ............................................................... 125
6.8 What are aOGCs (and OGCs) really good for? ............................................................... 129
Chapter 7 Future Directions ........................................................................................................ 131
References ................................................................................................................................... 135
Appendix 1 .................................................................................................................................. 217
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List of Abbreviations
CamKII - -Calcium calmodulin kinase II
ACSF - Artificial cerebrospinal fluid
aDGC - Adult born DGC
AMPA - α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid
aOGC - Adult born OGC
AraC - Arabinofuranosyl Cytidine, also known as cytosine arabinoside
BDNF - Brain derived neurotrophic factor
bHLH - Basic helix-loop-helix
BrdU - 5-bromo-2'-deoxyuridine
CA- Cornu ammonis
cAMP - Cyclic adenosine monophosphate
Cdk5 - Cycline dependent kinase 5
CFC- Context fear conditioning
CNTF - Ciliary neurotrophic factor
CR - Calretinin
CREB- cAMP responsive element binding protein
CS- Conditioned stimulus
DCX - Doublecortin
DG - Dentate gyrus
DGCL - Dentate granule cell layer
DMTS – Delayed match to sample
DNMTS - Delayed non match to sample
DT - Diphtheria toxin
EC - Entorhinal cortex
EE - Environmental enrichment
EGF - Epidermal growth factor
E-LTP- Early long-term potentiation
EPL - External plexiform layer
ERK - Extracellular signal-regulated protein kinase
FGF2 - Fibroblast growth factor 2
FMRP - Fragile X mental retardation protein
GABA - γ-Aminobutyric acid
GFAP - Glial fibrillary acidic protein
GL - Glomerular layer
H.M. - Patient Henry Molaison
HB-EGF - Heparin binding EGF
HPA- Hypothalamo pituitary adrenocortical
iDTR - Inducible diphtheria toxin receptor
ISD - Immediate shock deficit
IPL - Internal plexiform layer
KCC2 - K+-coupled Cl
- transporter
LTM- Long term memory
LTP - Long term potentiation
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MAM - Methylazoxymethanol acetate
MCL - Mitral cell layer
MEC - Medial entorhinal cortex
MF - Mossy fiber
ML - Molecular layer
MTT - Multiple trace theory
MWM - Morris water maze
NCAM - Neural cell adhesion molecule
NeuN - Neuronal nuclei (maturation marker)
NKCC1 - Na+–K
+–2Cl
– co-transporter
NMDA- N-Methyl-D-aspartate
NMDAR - NMDA receptor
NR2b - N-methyl-D-aspartate receptor subunit
OB - Olfactory bulb
OGC - Olfactory granule cell
OGCL - Olfactory granule cell layer
ONL - Olfactory nerve layer
PGC - Periglomerular cell
PKA - Protein kinase A
PP1 - Protein phosphatase 1
PRP - Plasticity related proteins
PSA-NCAM - Polysialated neural cell adhesion molecule
RMS - Rostral migratory stream
SGZ - Subgranular zone
STM - Short term memory
SVZ - Subventricular zone
TAM - Tamoxifen
TH - Tyrosine hydroxilase
UR- Unconditioned response
US - Unconditioned stimulus
VEGF - Vascular endothelial growth factor
VTA - Ventral tegmental area
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List of Tables
Table 1: Comparative table of olfactory adult neurogenesis papers……………………………..60
Table 2: Maturation analysis of CREERT2
positive cell population in the DG…………………...94
Table 3: Maturation analysis of LacZ positive cell population in the DG………………………95
Table 4: Maturation analysis of CREERT2
positive cell population in the SVZ………………...107
Table 5: Maturation analysis of LacZ positive cell population in the OB……………………...108
xii
List of Figures
Figure 1: Scheme of memory classification. ……………………………………………………..8
Figure 2: Trisynaptic circuit……………………………………………………………………..14
Figure 3. MWM scheme………………………………………………………………………....20
Figure 4. Fear conditioning scheme……………………………………………………………..23
Figure 5. Dentate gyrus organization……………………………………………………………26
Figure 6. Scheme of the maturational stages of aDGCs………………………………………...36
Figure 7. Olfactory system………………………………………………………………………49
Figure 8. Structure of the olfactory bulb………………………………………………………...51
Figure 9.DT-based ablation……………………………………………………………………...78
Figure 10. CreERT2
expression is restricted to progenitor cells and limited to adult neurogenic
regions……………………………………………………………………………………………80
Figure 11.Tagging new neurons…………………………………………………………………81
Figure 12. Ablating tagged neurons……………………………………………………………...82
Figure 13.DT-induced ablation produces minimal inflammation………………………………..83
Figure 14. General health and behavior are not altered by DT-induced ablation………………..84
Figure 15. Post-training ablation of adult-generated neurons degrades contextual fear memory.86
Figure 16. Pre-training ablation of adult-generated neurons does not prevent the formation of a
new contextual fear memory……………………………………………………………………89
Figure 17. Post-training (but not pre-training) ablation of adult-generated neurons impairs spatial
memory expression……………………………………………………………………………..91
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Figure 18. Post-training ablation of adult-generated neurons impairs visual discrimination
memory…………………………………………………………………………………………94
Figure 19: CreERT2
expression is restricted to neural stem cells……………………………….101
Figure 21: Maturation analysis of adult born olfactory granule cells…………………………103
Figure 22: Post-training ablation of adult-generated olfactory interneurons impairs expression of
an associative olfactory memory………………………………………………………………105
Figure 23: Open field performance following DT-induced ablation of adult generated olfactory
interneurons. …………………………………………………………………………………..105
Figure 24: Post-training ablation of adult-generated olfactory interneurons impairs expression of
an associative olfactory memory………………………………………………………………106
Figure 25: Pre-training ablation of adult-generated olfactory interneurons does not impair
acquisition of an associative olfactory memory………………………………………………..107
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Chapter 1 Literature Review
This literature review is structured in a funnel, starting from basic concepts of memory
and a review of landmark discoveries pertinent to the field of neuroscience of memory. Within
this framework, the role of the hippocampus in memory processing is discussed, followed by a
description of the physiological functions and anatomy of a structure within the hippocampal
formation, the dentate gyrus. Next, the introduction focuses on a specific subset of dentate
granule cells, those born during adulthood, their genesis, regulation and potential role in memory
processing. Finally, a separate subsection provides an overview of the olfactory system and
possible functional implications of olfactory interneurons born during adulthood.
1.1 Memory
1.1.1 Founding concepts
The turn of the twentieth century is considered by many to be a golden era in the study of
brain and behaviour, around which the emergence of several key concepts and discoveries would
arguably come to found the field of modern neuroscience. The ground for this flourishing was set
by a few prior discoveries, two examples being the initial descriptions of brain anatomy by
Willis in the 17th
century, and Galvani‘s description of electricity as the means of nervous
conduction in the 18th
century (Eichenbaum, 2002).
This period is marked by vigorous debates and the establishment of what are now core
concepts in learning and memory. One such important debate involved the compartmentalization
of brain function, a new concept encountering strong resistance in the research community (Zola-
Morgan, 1995). In the early 1800‘s, Franz Gall performed the first systematic analysis of cortical
localization. He developed a theory, known as organology or phrenology, that stated that
psychological characteristics were mediated by specific regions in the brain (Zola-Morgan,
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1995), and went on into mapping them. Even though character and personality traits never
proved to be compartmentalized as predicted by Gall, subsequent evidence showed that specific
brain functions were.
The first demonstration of this compartmentalization came from the work of Paul Broca,
through a case study of a patient, who, due to a localized lesion to the frontal lobe (in what was
later referred to as Broca‘s area) became aphasic but could still understand language (Stone,
1991). In the second half of the 19th
century, studies done by Gustav Fritsch and Eduard Hitzig,
using brain stimulation in dogs, and by David Ferrier, with monkeys, provided strong evidence
for distinct motor areas in the cortex (Gross, 2007), further refuting the view of the cortex as a
unitary unit.
The debate continued with the strengthening of the anti-localization view through the
work of Karl Lashley, who systematically removed cortical surface areas in the rat to study its
effects on memory. Lashley concluded that the extent of memory deficit was proportional to the
size of cortical area removed, regardless of its location, which he referred to as the law of mass
action (Lashley, 1929, 1950). Only many years later and with additional experimental work it
was possible to arrive at a different conclusion from this discovery.
At the cellular level, another ‗unitarian‘ type debate was taking place, between the
reticularists, who believed the brain was formed by a unitary interconnected fiber network in
which all cells were fused to each other, and the antireticularists, who believed the brain was
formed by independent nerve cells. Santiago Ramon y Cajal was a key figure in ending this
debate, developing a ‗neuron doctrine‘ that would merit him a Nobel prize in 1906. Using
Camillo Golgi‘s method for staining brain tissue, Cajal was able to demonstrate that neurons are
single independent units and describe in detail their anatomical components (Ramón y Cajal,
1995).
These observations also allowed Cajal to infer that nerve cells were polarized, with
information flowing from the dendrites to the axon of one cell and through a specialized region –
later coined ‗synapse‘ by Charles Sherrington – into the dendrites of another, so that the
integration of information occurred through the sum of the axons of several neurons converging
into the dendrites of another. Additionally, by comparing brains of different species, Cajal noted
a correlation between number of connections between neurons and place of the animal in the
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phylogenetic scale, concluding that connectivity could be a measure of intellectual power. He
also suggested that this level of connectivity could be altered by behavior, suggesting that
plasticity underlies learning, an association that still guides memory research today.
Charles Sherrington‘s study of the reflex arc provided the next step in understanding
nerve cells and their circuitry. By describing the circuit of the knee-jerk reflex (Sherrington,
1892), he observed that even though sensory neurons possessed dedicated inputs into the spinal
cord, the output neurons received input from many such cells, evidence that complex behaviours
could consist of an integration of these inputs. Sherrington also contributed to the understanding
of reciprocal innervations - or how excitatory and inhibitory influences work together to generate
movement - and proposed a hierarchy of brain structures in mediating coordinated actions, with
the cortex as the most complex followed by brain stem and spinal cord (Eichenbaum, 2002;
Molnár and Brown, 2010).
Ivan Pavlov described a somewhat similar reflex arc for the digestive system involving
the brain stem and vagus nerve, elucidating the loop between food stimulation and ingestion (i.e.
activation of the gustatory sensory system in the mouth and gullet) and the release of gastric
fluids in the stomach for which he won the Nobel prize in 1904. His major breakthrough came
through the observation that the same loop could be activated by the mere sight of the food, or of
the person bringing the food.
Based on this observation, Pavlov proposed the existence of two types of reflexes:
unconditioned reflexes (like the ones described by Sherrington), which are innate and
uncontrollable; and conditioned reflexes, which are acquired through experience (Pavlov, 2003).
In an unconditioned reflex, an unconditioned stimulus (US), such as food in the mouth, drives an
unconditioned response (UR), such as salivation and increase of gastric fluids. In a conditioned
reflex, an arbitrary conditioned stimulus (CS) is paired with the US such that the CS alone comes
to elicit a conditioned response similar to the UR. This description was critical to the concept of
classical conditioning and the methodology later used to study memory.
Herman Ebbinghaus, inspired by this research, set on to develop a framework for a
systemic study of memory, creating rigorous methodology for objective and quantitative
assessment of memory. His intention was to develop methodology that would minimize variation
and render reliable and reproducible results, starting a school of thought called behaviourism. In
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his words: ―We must try in experimental fashion to keep as constant as possible those
circumstances whose influence on retention and reproduction is known or suspected (...). The
material must be so chosen that decided differences of interest are, at least to all appearances,
excluded; equality of attention may be promoted by preventing external disturbances; sudden
fancies are not subject to control, but, on the whole, their disturbing effect is limited to the
moment, and will be of comparatively little account if the time of the experiment is extended,
etc.‖ (Ebbinghaus, 1913). Behaviourists believed behaviour could be broken down into elements
of conditioned reflexes and associations.
Based on observations of animal learning, Edward Thorndike made his contribution to
the field by proposing his ‗law of effect‘, stating that within a specific situation, a behavior that
generates a reward is likely to be repeated given that same situation, meaning rewards will
reinforce the behavior that ensues them (Thorndike, 1998). Conversely, a behavior that leads to
an unpleasant or discomforting stimulus will be avoided. This observation would guide much of
what would later be called instrumental learning in the years to come.
William James, in his Principles of Psychology, also emphasizes the importance of reflex
mechanisms for the formation of a memory, calling them the building blocks of a ‗habit‘.
Moreover, according to James, complex behaviours such as walking or singing consist of well
rehearsed sequences of simple habits or reflexes, a concept very akin to the behaviourists. With
regard to memory per se, James proposes for the first time the existence of types of memory. The
first type is an initial ‗primary memory‘ in which information is processed and remains in our
‗stream of thought‘. A ‗secondary memory‘ is more enduring, consisting of both the actual
information and the experience of learning that information. In James‘s words: ―it is the
knowledge of an event, or fact, of which meantime we have not been thinking, with the
additional consciousness that we have thought or experienced it before‖ (James, 1905).
James‘ idea of a two-component memory, although attractive, was relatively forgotten for
a few decades - when behaviourists were focused largely on animal studies. Starting in the late
1950‘s it was reintroduced as a distinction between short-term memory (STM) and long-term
memory (LTM) (Broadbent, 1958; Glanzer and Cunitz, 1966; Atkinson and Shiffrin, 1971).
Experimental confirmation of that distinction came from studies with amnesic patients that
showed preserved STM but impaired LTM (Drachman and Arbit, 1966; Baddeley and
5
Warrington, 1970; Cave and Squire, 1992). The molecular and cellular underpinnings of this
distinction will be reviewed in section 1.1.3.
Importantly, William James‘ description of secondary memory captures the other
prominent school of thought in the memory field at the time, cognitivism. Cognitivists
interpreted memory and cognition as complex and elaborate phenomena, more than mere sums
of reflexes. The first step towards a resolution of the debate between cognitivists and
behaviourists came through the work of French philosopher Theodore Ribot, which started a
significant shift in the way long-term memory was perceived, as reviewed in the next sub-
section.
1.1.2 Memory gradients and grades of memory
Theodore Ribot, reviewing several cases of patients who suffered brain damage caused
by head trauma, noted that not only did they experience loss of memories prior to the trauma,
known as retrograde amnesia, but there was also a gradient in this memory loss: recent memories
were more affected than older memories. This led to the formulation of a law of regression, also
known as Ribot‘s law, that states that the likelihood of memory dissolution is inversely
proportional to the age of the memory, meaning older memories are less likely to be lost than
younger memories, suggesting a temporal reorganization of memory (Ribot, 1882).
In his words: ―We have stated these two facts in the dissolution of memory: the new
perishes before the old, the complex before the simple. The law which we have formulated is
only the psychological expression of a law of life, and pathology shows in its turn that memory is
a biological fact‖. And for a bit of poetry: ―It is a well-known fact in organic life that structures
last formed are the first to degenerate. It is, says a physiologist, analogous to what occurs in a
great commercial crisis. The old houses resist the storm; the new houses, less solid, go down on
every side. Finally, in the biological world, dissolution acts in a contrary direction to evolution: it
proceeds from the complex to the simple. Hughlings Jackson was the first to show that the higher
functions - the complex, special, voluntary functions of the nervous system - were the first to
6
disappear; that the lower, the simple, general automatic functions were the last to go.‖ (Ribot,
1882).
In the decades to come, much attention was paid to the behavioural characterization of
amnesic patients, a classic case being that of patient Henry Gustave Molaison (H.M). H.M. was
one of a few patients to undergo bilateral resection of the whole medial temporal lobe to treat
severe epilepsy. After performing these surgeries, Dr. William Scoville saw ―no marked
physiologic or behavioral changes with the one exception of a very grave, recent memory
loss”(Scoville, 1954). Given the severity of his deficit, his agreeability and the lack of
confounding factors such as psychosis, H.M. was the most studied case from that series of
surgeries. He displayed both retrograde and anterograde amnesia, retaining memories from his
childhood but losing the ones closest to the time of the surgery, consistent with the law of
regression, and being unable to form new memories (Scoville and Milner, 1957), at least at first
glance.
Two important developments ensued from the study of H.M.‘s amnesia. It was the first
time that a ‗pure‘ memory deficit was identified, with no other cognitive, perceptive or motor
consequences. This really settled the debate on whether there are regions in the brain with
specific functions, and also weakened the line of thought that the cortex played the most
important role in these processes. Secondly, as devastating as H.M.‘s amnesia was, deeper tests
mostly conducted by Brenda Milner showed that H.M. still retained the ability to learn. At least
certain things. She observed that, by training him in a motor learning task, in which subjects
learn to draw a star by looking at the reflection of their hand in a mirror, H.M. showed consistent
improvement in performance across trials, in spite of never remembering doing the task (Milner
et al., 1968, 1998).
This finding led the way to a series of careful investigations of the memory deficits in
amnesic patients, with important methodological developments. The initial findings suggested
that motor learning had a decisive role in determining whether memory for a task would be
preserved. Subsequent research, however, showed that amnesic patients also performed similarly
to controls in tasks involving learning of perceptual and cognitive skills (Corkin, 1968; Brooks
and Baddeley, 1976; Benzing and Squire, 1989), word priming (Graf et al., 1984; Shimamura,
1986; Tulving and Schacter, 1990), and simple pavlovian conditioning (Daum et al., 1989).
7
The first to suggest that these ‗exceptions‘ to amnesia actually composed a separate type
of memory were Cohen and Squire. After training amnesic patients to perform a pattern
analyzing skill – reading mirrored words – they saw that the patients were able to improve their
mirror reading skills despite claiming not to remember any of the words they had read. They
proposed that this evidence provided physiological basis for a distinction between procedural or
rule-based information (spared in amnesiacs) and declarative, or data-based information;
between knowing how and knowing that (Cohen and Squire, 1980). Daniel Schacter refers to
these two types of memory as implicit, when it does ―not involve any conscious or explicit
recollection of a prior episode‖, or explicit, when it does (Schacter, 1990).
Besides categorizing memory into different types, this mapping soon was extended to
anatomy. A more recent and well accepted division of these multiple memory systems refers to
declarative and nondeclarative memory (Squire, 1992). Declarative memory (or explicit
memory) refers to memory that involves conscious recollection, is fast, flexible, not always
reliable (subject to forgetting) and is dependent on the hippocampus and surrounding medial
temporal lobe areas and diencephalon (Squire et al., 1993). Non-declarative memory (or implicit
memory) encompasses a number of independent abilities, is generally slow, inflexible (meaning
the parameters have to be the same in a given situation for the memory to be accessed), reliable,
and involves areas outside of the medial temporal lobe and diencephalon (Squire et al., 1993).
Declarative memory can be further classified into episodic and semantic memory.
Episodic memory encompasses personal or autobiographical memories (including contextual and
spatial memories), generally regarding questions such as what, where and when (Tulving, 2002).
Semantic memory relates to a general or concept-based knowledge of the world. Semantic
memory refers to facts, whereas episodic memory has to do with events. Both types of memory
are declarative, in the sense that retrieval of information is carried out explicitly and subjects are
aware that stored information is being accessed (Tulving, 1987, 1992; Squire, 1992; Squire et al.,
1993).
Non-declarative (implicit or procedural) memory is perhaps the type of memory that best
relates to what behaviourists were investigating in their studies of reflexes, and what William
James qualified as ‗habits‘: skillful behavior that does not require conscious recollection for
retention. It includes motor, perceptual, perceptuo-motor and cognitive skills, simple classical
conditioning, emotional learning and priming (Squire and Zola-Morgan, 1988; Squire, 1992).
8
Studies showed that these sub-categories often rely in different brain areas, constituting
independent systems. For instance, skills are mostly dependent on the neostriatum (Packard et
al., 1978; Heindel et al., 1988, 1989; Saint-Cyr et al., 1988), emotional conditioning on the
amygdala (Davis, 1992; Kim and Fanselow, 1992), and some types of priming on the neocortex
(Squire et al., 1992). A scheme of this classification can be seen in Fig. 1.
Figure 1: Scheme of memory classification. Types of memory and the main underlying brain structures are
represented. Adapted from Squire, 1992.
1.1.3 Memory consolidation
Georg Müller and Alfons Pilzecker were the first to introduce the concept of memory
consolidation in 1900, proposing that the progression from learning of new information to
forming a permanent memory is not instantaneous, but that the information needs to be fixated or
consolidated, during which period it remains vulnerable to loss (Lechner et al., 1999). This
concept gained popularity in the late 1940‘s with the observation that electroconvulsive shocks
caused retrograde amnesia in rats (Duncan, 1949), which contributed to a long quest for animal
models of retrograde amnesia (McGaugh, 1966).
The study of memory consolidation can be divided into two levels: synaptic and systems
consolidation. The first refers to cellular and molecular events that take place in a time scale of
minutes to hours to render information fixed in synapses. The second refers to a reorganization
of memory within and across brain regions taking place in the time scale of weeks to years. Both
types of consolidation will be reviewed in separate subsections.
9
1.1.3.1 Synaptic consolidation
In 1949, Donald Hebb proposed a dual trace mechanism for memory, in which an initial
memory relies on neuronal reverberations, whose coordinated persistence leads to synaptic
connections, the cellular mechanism for consolidation: ―Let us assume that the persistence or
repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add
to its stability. (…) When an axon of cell A is near enough to excite a cell B and repeatedly or
persistently takes part in firing it, some growth process or metabolic change takes place in one or
both cells such that A's efficiency, as one of the cells firing B, is increased‖ (Hebb, 1949).
The discovery that protein synthesis inhibitors selectively disrupted LTM (Barondes and
Jarvik, 1964; Agranoff et al., 1966; Davis and Squire, 1984), whereas stimulant drugs could
enhance it (McGaugh, 1973), helped crystallize the concept of consolidation as a cellular process
that transforms ephemeral traces into persistent stable memories.
Extensive understanding of the molecular and cellular components of short and long-term
implicit memory came from studies with invertebrates such as the marine snail Aplysia
(reviewed in Kandel, 2002). An important insight into the cellular basis of explicit memory came
from the work of Timothy Bliss and Terje Lømo, who observed that persistent stimulation of the
perforant path led to a prolonged enhancement of excitatory post-synaptic potentials (EPSPs) in
dentate granule cells, a phenomenon they called long-term potentiation (LTP) (Bliss and Lømo,
1973).
Certain shared characteristics between LTP and memory made it an appealing cellular
mechanism for memory: it is present in the hippocampus (a crucial memory hub), is fast and
long-lasting, specific (neighboring synapses are unaffected) and associative, meaning integration
of different inputs leads to better potentiation (Morris et al., 1990a). Additionally, inhibition of
N-methyl-D-aspartate (NMDA) receptors, which blocked LTP, also impaired spatial memory
(Morris et al., 1986) and place field stability (Kentros et al., 1998) in rats.
Later research showed that LTP also posessed two phases. Early LTP (E-LTP) is
produced by a single train of stimuli, lasts from 1 to 3 hours and can still be induced in the
presence of transcription or translational inhibitors (Krug et al., 1984). Persistent stimulation
10
gives rise to late phase LTP (L-LTP), dependent on gene expression and protein synthesis
(Nguyen et al., 1994). As with memory formation (Restivo et al., 2009), L-LTP is associated
with neuronal structural changes (Fifková and Van Harreveld, 1977), some of which depend on
protein synthesis (Fifková et al., 1982; Stanton et al., 1984).
The molecular cascade responsible for L-LTP involves the activation of NMDA receptors
and influx of calcium (Nguyen and Kandel, 1996), activation of Calcium-calmodulin kinase II
(CamKII) (Silva et al., 1992a, 1992b), cyclic adenosine monophosphate (cAMP) and protein
kinase A (PKA) (Frey et al., 1993; Abel et al., 1997), cAMP responsive element binding protein
(CREB) (Bourtchuladze et al., 1994; Kida et al., 2002) and on the opposite vector of the cascade
calcineurin (Mansuy et al., 1998; Malleret et al., 2001) and protein phosphatase 1 (PP1) (Blitzer
et al., 1998).
To attempt to explain the synapse specificity of L-LTP, Richard Morris and his
colleagues put forward a theory called synaptic tagging and capture hypothesis. According to this
theory, stimulation (E-LTP) leads to the formation of a ‗synaptic tag‘, a protein synthesis
independent process that recruits plasticity related proteins (PRPs) to the potentiated synapse,
prepping it for L-LTP (Frey and Morris, 1997; Redondo and Morris, 2011).
The first experimental evidence for this was a dual LTP experiment, in which L-LTP was
formed in the presence of protein synthesis inhibitors if a nearby synapse had been potentiated
(E-LTP) shortly before (Frey and Morris, 1997). Although there remain some limitations of the
theory (such as updating the PRP mechanism to local protein synthesis in dendrites and dendritic
mRNAs) (Redondo and Morris, 2011), it is an interesting challenge to the original consolidation
hypothesis, turning synaptic consolidation into a pliant entity, and the synaptic milieu (or
heterosynapses) as a possible influence on the fate of memory traces.
Another challenge to the consolidation hypothesis gained notoriety in 2000, when Karim
Nader and colleagues showed that retrieval returned previously consolidated memories to a labile
state, vulnerable to protein synthesis inhibitors (Nader et al., 2000a). They stated that retrieval
triggered a process called reconsolidation, which shared the same molecular signatures as
synaptic consolidation (Kida et al., 2002; Nader and Einarsson, 2010). Long-term memories
11
were not as static as originally thought, but were revisited and updated during retrieval (Nader et
al., 2000b).
1.1.3.2 Systems consolidation
The study of long-term consolidation or systems consolidation was initially based on data
from amnesic patients, in which a localized brain lesion could be associated to a specified degree
of memory loss. A few models were developed to explain how remote memory is formed in the
brain, two of which are reviewed here.
The first to propose a model to explain how remote memories are formed was David
Marr in the 1970‘s. According to him, simple representations of events (simple memories) are
formed in the hippocampus and, through replay during sleep, are transferred to cortical areas to
be reorganized and reclassified (Marr, 1971). These concepts remain in the core of contemporary
systems consolidation theories.
The standard model of consolidation predicts that information is originally processed in
the neocortex but needs the hippocampus to be initially stored. The medial temporal lobe or
hippocampal formation acts as a temporary store or guide reinforcing the neocortical connections
representing the memory (Squire and Alvarez, 1995). With time, the hippocampus becomes
disengaged and remote memory becomes stored and can be retrieved directly from a more
permanent memory system confined to neocortical areas (Squire and Alvarez, 1995). This is
concluded largely from studies with patients with and animal models of hippocampal lesion (for
a review see section 1.1.2), which display temporally graded retrograde amnesia and anterograde
amnesia (Squire and Alvarez, 1995).
Importantly, this model predicts that information is initially processed in parallel in the
hippocampus and cortex, and the replay of the hippocampal network leads to strengthening of
cortico-cortico connections until the memory is incorporated with older cortical memories and
becomes independent of the hippocampus, implying that changes in strength of hippocampal-
12
cortex connections are fast and temporary, whereas cortico-cortico connections are slow and
permanent (O‘Reilly and McClelland, 1994; Frankland and Bontempi, 2005).
Nadel and Moscovitch proposed an alternative model of systems consolidation, Multiple
Trace Theory (MTT). Through a review of the case studies and animal literature they point out
two inconsistencies with the standard model. First, medial temporal lobe damage can generate
ungraded retrograde amnesia, particularly for episodic (autobiographical and spatial) memories
(Rosenbaum et al., 2000; Cipolotti et al., 2001; Viskontas et al., 2002; Martin et al., 2005).
Second, retrieval of detailed remote autobiographical memories engages the hippocampus (Ryan
et al., 2001; Gilboa et al., 2004).
According to MTT, new information is initially coded by the hippocampus, that later acts
as a pointer to form a memory trace binding hippocampal and cortical networks. Each
reactivation recruits the hippocampus to form another memory trace that is linked to the already
existing cortical one (Nadel and Moscovitch, 1997). This multitude of traces facilitates the
extraction of factual from contextual information, so that the hippocampus persistently stores the
temporal and spatial context of a memory, whereas the cortex stores the semantic information
(Nadel and Moscovitch, 1997). Although reports of preserved spatial and autobiographical
memories in a patient with extensive medial frontal lobe damage exist (Teng and Squire, 1999),
MTT supporters question the degree of detail of these preserved memories (Rosenbaum et al.,
2000).
The next sub-section further explores the anatomy and function of the hippocampal
formation before going into more depth on the animal literature pertaining to hippocampal lesion
and inactivation studies and their consequences for learning and systems consolidation.
1.2 Hippocampus
The hippocampus is an inherent part of memory processing. This section discusses the
anatomy, development and function of the hippocampus. Next follows an examination of the
dentate gyrus; a sub-region which continues to generate neurons throughout adulthood.
13
1.2.1 The hippocampal formation: an overview
The hippocampal formation is comprised of eight regions: cornu ammonis (CA)3, CA2,
CA1, dentate gyrus (DG), subiculum, presubiculum, parasubiculum and entorhinal cortex. Given
the considerable amount of debate over this nomenclature in the literature, to facilitate the
dialogue with hippocampal lesion studies, these eight regions are collectively refered to as the
hippocampal formation, and to CA1, CA2, CA3 and the DG as hippocampus proper throughout
this thesis.
One feature that makes the hippocampal formation unique is the predominance of
unidirectional connections within its structure. Most neocortical inputs reach the hippocampal
formation through the entorhinal cortex. This structure launches two sets of unidirectional
projections forming one of the major hippocampal input pathways: the perforant path. Neurons
from layer II of the entorhinal cortex project to the dentate gyrus and CA3. Neurons from layer
III project to CA1 and subiculum. In another unidirectional pathway, DG granule cells project to
CA3 pyramidal cells, through the mossy fibers. CA3 pyramidal cells, following this same rule,
project to CA1 forming the Schaffer collaterals. This part of the circuit, comprising the synapses
EC-DG, DG-CA3 and CA3-CA1 is referred as the trisynaptic circuit (Andersen et al., 1971)
(Fig. 2).
CA1, in its turn, projects nonreciprocably to the subiculum and entorhinal cortex. The
subiculum projects to the parasubiculum and presubiculum, as well as to the entorhinal cortex.
Hence, CA1 and subiculum form a loop, receiving input from the superficial layers of the
entorhinal cortex and projecting back to its deep layers.
14
Figure 2: Trisynaptic circuit. Representation of hippocampal areas CA1, CA3 and dentate gyrus (DG) and the
projections that form the trisynaptic circuit. Projections from the entorhinal cortex reach the DG through the
perforant path (PP). Dentate granule cells project to pyramidal CA3 cells through mossy fibers (MF). CA3
pyramidal cells project to CA1 cells forming the Schaffer collaterals (SC).
1.2.2 Hippocampal functions: we are more than just our memories
The shape and anatomy of the hippocampus raised scientific interest very early in history,
starting as early as ancient Greece. The term hippocampus – named because of its sea horse
shape – first appeared in the 16th
century, being proposed by Giulio Cesare Aranzi (Lewis,
1923). This comparison was not so welcomed amongst his contemporaries, some preferring the
likeness of a silk worm or the horn of a ram (Lewis, 1923).
In the 18th
century, de Garangeot proposed a new term, Ammon‘s horns, after the
Egyptian god: ―Following the ventricles in their downward curve . . . they terminate by a blunt
point which resembles sufficiently a ram‘s horn. It is alleged that this blunt point makes a small
winding at its tip, as do the ends of rams‘ horns and for this reason, then, they are named the
horns of Ammon” (Lewis, 1923). Even though the silk worm resemblance seems to have been
forgotten, the comparisons to a sea horse and the horns of Ammon remain to this day. In the 19th
century hippocampal cytoarchitecture fuelled Camillo Golgi‘s interest, featuring in some of his
most beautiful pictures (Bentivoglio and Swanson, 2001).
15
Function attributed to the hippocampus changed quite a few times in the last century.
Until the 1940‘s, the hippocampus was considered part of the olfactory system, largely due to the
presence of olfactory projections surrounding the hippocampal formation, coupled with its
particularly large size in macrosmatic animals, and reports of olfactory related behaviors in
response to hippocampal stimulation or seizures (Brodal, 1947). However, the absence of an
olfactory deficit in animals with neocortical or hippocampal lesions and the presence of
hippocampi in microsmatic animals, among other evidence, mostly discredited this view (Brodal,
1947).
Papez proffered that the hippocampus, along with the hypothalamus and the gyrus
cinguli, formed an ―ensemble of structures (…) proposed as representing theoretically the
anatomical basis of emotions‖ (Papez, 1937), an assumption again to be refuted by Brodal for a
lack of biological basis (Brodal, 1981). Around the 1950‘s the discovery of theta oscillations
and their relation to attention (Green and Arduini, 1954) led to a series of studies linking the
hippocampus with attention control (Kaada and Pribram, 1949; Sloan and Jasper, 1950; Kaada et
al., 1953; Grastyan et al., 1959).
In the 1960‘s, studies showing an increase in basal glucocorticoid levels in response to
hippocampal lesions (Knigge, 1961) drew attention to the mechanisms mediating the relationship
between stress and cognition (McEwen and Sapolsky, 1995; de Kloet et al., 1999).
Glucocorticoid and mineralocorticoid receptors are abundant in the hippocampus (Herman et al.,
1989), and particularly the ventral hippocampus has been shown to negatively control the
hypothalamo-pituitary-adrenocortical (HPA) axis (Jankord and Herman, 2008), even though the
precise mechanism is still unclear.
Presently, the most prominent line of hippocampal function research involves its role in
learning and memory. Significant early efforts on this line date back to 1950‘s and 60‘s, through
the work of Penfield, Scoville and Milner (see next sub-section). Despite the current prevalence
of a hippocampal view of learning and memory, alternative theories and criticism are present, a
couple of which are mentioned in the next paragraphs.
Vanderwolf and Cain (1994) made an extensive case against limiting the study of
behaviour to pre-existing psychological theories expressing a reductionist view of the mind,
compartmentalized into perception, attention, memory, motivation, etc. According to these
16
authors, this ―psychological approach (…does) not take adequate account of the importance of
the intrinsic organization of the brain and the instinctive behavior that results from it. Further, if
the behavior of all mammals is discussed in terms of the same processes of sensation, perception,
cognition, memory, etc., actual behavior is trivialized and interspecific differences tend to be
ignored.‖ (Vanderwolf and Cain, 1994). They argue for a conceptual reorientation, through
which the hippocampus is not ‗uniquely important‘ for memory but part of a broader circuit, one
to be unlocked by unbiased assessment of experience driven behavior.
Another theory involves the role of the hippocampus in behavioural inhibition (Kimble,
1968) and anxiety (Gray, 1982). Gray and McNaughton (2003) proposed that the hippocampus
acts as a conflict solver, thus serving a function more basic than memory. Within this framework,
the hippocampus detects and solves conflicts by suppressing conflicting or competing
information, thereby minimizing interference (Gray and Mcnaughton, 2003; Davidson and
Jarrard, 2004). This is an interesting counterpoint to theories of the hippocampus being involved
in one type of memory, as will be reviewed in the next sub-section.
1.2.3 Hippocampal functions: learning and memory
A connection between memory and the hippocampus first arose in the 1880‘s through the
description of what is now known as Wernicke-Korsakoff syndrome, an illness derived from
high alcohol consumption that leads to amnesia (Victor and Yakovlev, 1955). This syndrome
was later associated with a pathology of the mammillary bodies and the mediodorsal nucleus of
the thalamus, targets of hippocampal efferent input (see Kopelman et al., 2009 for a review).
Evidence for a direct role of the hippocampal formation in memory became available a
few years later, through the emergence of case studies of patients with damage to the
hippocampus who presented memory deficits ( see Orbach et al., 1960 for a review). In the early
1950‘s, Wilder Penfield and Brenda Milner observed that some patients who had undergone
unilateral temporal lobe removal to treat epilepsy presented anterograde amnesia (Penfield and
Milner, 1958). These results interested another surgeon, William Scoville, who contacted
Penfield and Milner on account of some of his own patient findings.
17
Following a series of bilateral medial temporal lobe resections performed in patients who
suffered from psychosis or severe epilepsy, William Scoville observed an unexpected result:
severe memory loss (Scoville, 1954). Further analysis of the outcome of this type of operation
led Scoville and Milner to establish a relationship between the degree of memory impairment
and the extent of the hippocampal lesion (Scoville and Milner, 1957). In particular, observations
of one such patient, H.M., who incurred anterograde and retrograde amnesia following bilateral
hippocampal resection (Scoville and Milner, 1957; Sagar et al., 1985), was arguably a turning
point for the study of memory, setting new theoretical and experimental groundwork (see section
1.1.2).
This discovery incited numerous but somewhat contradictory attempts at finding an
animal model for amnesia, in monkeys (Orbach et al., 1960; Correll and Scoville, 1967) and rats
(Kaada et al., 1961; Kimble, 1963, 1968; Kveim et al., 1964; Isaacson and Kimble, 1972). Some
clarification was brought to the field in the 1970‘s with theoretical advances in the classification
of types of memory, which were presumably subserved by different circuits (see section 1.1.2).
This allowed for the development of targeted tasks and clarified the role of the hippocampus in
encoding of spatial and contextual memory. The following section explores in detail some of
these tasks and the level of hippocampal involvement therein.
The theory proposing a connection between hippocampus and declarative memory led to
the development of an animal model of amnesia in primates, with a task termed delayed
matching to sample (DMTS). In this recognition memory task, monkeys were shown a particular
object and were subsequently (at varying time intervals) given the option of choosing between a
new object and the one that was previously shown (a measure of STM) (Gaffan, 1974). Choosing
the familiar object was rewarded with a sugar puff. Two variants were added to the task: longer
delays and a choice phase in which several previously rewarded objects were to be selected from
non-rewarded ones (lists) (Gaffan, 1974). Animals subjected to fornix lesions showed delay-
dependent and list-length deficits, but intact short-term memory and intellectual function (since
they could remember the matching-to-sample rule at shorter delays) (Gaffan, 1974), consistent
with the behavior of amnesic patients.
Using a variation of DMTS in which animals were required to select the novel object
(delayed nonmatching to sample or DNMTS), Mishkin showed that combined (but not separate)
18
lesions of amygdala and hippocampus caused severe impairments in delay-dependent and list
length tests, thus reproducing the lesion type and behavioural profile of patient H.M. (Mishkin,
1978). DNMTS became the most widely used task in a battery of declarative memory animal
models of amnesia (Squire and Zola-Morgan, 1988). In the years to come much of these data has
been revisited and concerns have been raised with regard to the extent of the lesions and
interpretation of the results (Mumby, 2001; Squire, 2004), questioning the role of the
hippocampus in recognition memory and declarative memory theory of hippocampal function as
a whole (Murray and Wise, 2004).
In 1971, O‘Keefe and Dostrovsky recorded a population of hippocampal cells that
displayed preferential activation in specific spatial locations, referred to as place cells (O‘Keefe
and Dostrovsky, 1971). This discovery led O‘Keefe and Nadel to propose a new theory of
hippocampal function, the cognitive map theory, claiming that ―the hippocampus is the core of a
neural memory system providing an objective spatial framework within which the items and
events of an organism's experience are located and interrelated‖ (O‘Keefe and Nadel, 1978).
The cognitive map theory‘s basic proposition is that spatial information (with regard to
an allocentric representation) is stored in a map format - constituting a framework they called
‗locale‘system, which is a cognitive map or schema used by animals in order to navigate. They
claimed that all allocentric spatial information, or locale, is permanently stored in the
hippocampus, and that this memory system emerged neuroethologically in response to
environmental pressures for naturalistic behaviours such as food storing in birds and mating in
small mammals (O‘Keefe and Nadel, 1978; Jacobs and Spencer, 1994; Clayton and Krebs,
1995).
This theory was mostly based from findings that hippocampal lesions impair performance
in spatial tasks in rats (O‘Keefe et al., 1975; Olton et al., 1978; O‘Keefe and Nadel, 1978) and
indications that place cells encode a map of environmental cues (Muller and Kubie, 1987;
O‘Keefe and Burgess, 1996), presumably forming a topological representation of space.
However, much evidence has shown that this spatial representation is not cohesive, with
overlapping or fragmented coding (Shapiro et al., 1997; Tanila et al., 1997; Eichenbaum et al.,
1999). The circuit underlying spatial representation has also been put in question, especially with
regard to which brain areas are involved and how this cognitive map is used for navigation.
19
Although the most distinct firing patterns are predominant in the CA1 region, all
hippocampal subfields have place-responding cells (Barnes et al., 1990). Moreover, spatial
computation is not exclusive to the hippocampus, since place firing in CA1 persists in the
absence of intrahippocampal inputs from the DG (Mcnaughton et al., 1989) or CA3 (Brun et al.,
2002), suggesting that CA1 receives direct spatial signals from the entorhinal cortex via the
perforant path.
Indeed, the medial entorhinal cortex (MEC) has cells that respond to spatial signals (Fyhn
et al., 2004), but unlike hippocampal place cells, these cells have multiple firing fields organized
in an array of tessellated triangles, or grid: a very likely element of a spatial metric system
(Hafting et al., 2005). Nevertheless, having a functional metric system – or a cognitive map - and
using it for navigation are different things. In order to move from one location to another, some
algorithm must be in place to link one map to the next, a path integrator. This integrator is most
likely outside of the hippocampus – which would facilitate discrimination between overlapping
spatial maps - and might involve MEC and grid cells, but is currently the subject of theoretical
models (Moser et al., 2008). Although it is irrefutable that the hippocampus is critical for spatial
memory, how this spatial memory is accessed, integrated and commanded is still unclear.
1.2.3.1 A task for spatial memory: Morris Water Maze
The cognitive map theory‘s premise that the hippocampus is necessary for navigation led
to the development of navigational tasks, such as the radial maze (Olton and Samuelson, 1976)
and the Morris Water Maze (MWM) (Morris, 1981). Richard Morris created a task in which the
goal was invisible (distal localization), inaudible, could not be detected by smell and was not
marked by local cues, so that finding the hidden goal could only be achieved by inferring its
location relative to distal cues (Morris, 1981), a concept akin to place cells.
The task apparatus consists of a large circular pool of opaque water. The pool hides a
submerged escape platform placed at a fixed location and is surrounded by distal cues on the
walls (see Fig. 3 for a scheme). An animal is placed placed in the water at different starting
locations. Over several trials the animal finds the hidden platform with decreasing latencies.
20
During a probe test, the platform is absent and the time spent close to its former location is used
as a measure of learning. Both rats and mice are natural swimmers, although there is evidence
that rats are better swimmers (Dagg and Windsor, 1972).
Figure 3. MWM scheme. Distal cues are located on the walls and a camera records the animal‘s swim path. The
animal is dropped at random start locations to find a submerged platform.
Morris and colleagues demonstrated that animals with hippocampal (but not cortical)
lesions were severely impaired in finding the hidden platform (place navigation) (Morris et al.,
1982). When they were trained with a visible platform (cue navigation), however, they behaved
similarly to controls (Morris et al., 1982). Since the cue navigation version of the task shares the
same basic elements as the place navigation, i.e. swimming, motivation, vision, this shows that
the deficit exhibited by the hippocampal lesioned animals was in the spatial learning component
of the task.
The simplicity of the task, the absence of odour cues (as opposed to dry mazes), the
possibility of using automated tracking systems, and the flexibility of design (visible vs. hidden
platform tasks) have contributed to the popularization of the MWM as one of the most frequently
used tasks in behavioural neuroscience (D‘Hooge and De Deyn, 2001). The MWM is frequently
used as a general task to assess cognitive ability in a variety of models, including ischemia
(Block, 1999), Alzheimer‘s disease (Quon et al., 1991), pre-natal drug exposure (Cutler et al.,
1996) and developmental disorders such as fragile X syndrome (D‘Hooge et al., 1997).
Critics of the task argue that water is aversive to the animals and could lead to
considerable stress and endocrinological changes - particularly on the first training days - and
21
impact learning (Wenk, 2004). Indeed, MWM training leads to significant increases in serum
corticosterone in mice (Harrison et al., 2009) and rats (Beiko et al., 2004), which can be reduced
with pre-exposure to the pool (Beiko et al., 2004). Stewart and Morris, however, argue that stress
should be minimal at proper water temperature (25oC) (in Arjun Sahgal, 1983).
Later studies showed that water maze deficits were found in animals with lesions to the
entorhinal cortex (Schenk and Morris, 1985), dentate gyrus (Sutherland et al., 1983), perforant
path (Skelton and McNamara, 1992), septum (Hagan et al., 1988), and subiculum (Taube et al.,
1992), leading to the overall agreement that a complete hippocampal formation is necessary for
MWM performance. Importantly, this hippocampal dependency is not temporally graded, since
hippocampal lesions performed long after MWM training still disrupt performance (Clark et al.,
2005; Teixeira et al., 2006), indicating that the hippocampus is always necessary for MWM
memory.
Interestingly, aspiration (Moser et al., 1993) or ibotenic acid (Moser et al., 1995) partial
lesions of the hippocampus revealed a functional dissociation in the septotemporal axis, with
dorsal lesions being far more disruptive for MWM learning than ventral ones: normal MWM
performance can be supported by lesion of ~60-80% of the hippocampus, as long as the dorsal
part is the one spared. Consistent with this, place cells are more numerous and have more
focused place fields in the dorsal compared to ventral hippocampus (Jung et al., 1994). A step
further, Moser and Moser showed a dissociation between acquisition and retrieval in the MWM:
while lesions of ~80% of the hippocampus do not impair acquisition, a loss of as little as ~30%
leads to a deficit in retrieval (Moser and Moser, 1998). This topic will be explored in more detail
in the discussion.
1.2.3.2 A task for contextual memory: Fear conditioning
Studies with amnesic patients strongly indicated a role for the hippocampus in encoding
contextual components of memories (i.e. episodic memories). Cognitive map theory and place
cells also suggested the importance of the hippocampus for spatial representation. Contextual
22
fear conditioning (CFC) is a task that explores contextual representation memories using a fear
conditioning framework.
Fear is necessary for survival, is a robust and conserved response across species, and
perhaps for that reason it is one of the most studied and well understood neural circuits (Johansen
et al., 2011). Pavlovian fear conditioning is a form of associative learning designed to take
advantage of these characteristics. The basic premise is to assess contextual memory by making
it salient through an association between an aversive stimulus (a foot shock) and the context in
which it is received (fear chamber). Fear conditioning can be learned in a single session and
produces a robust and long-lasting memory, contributing to its popularity to this day, and
recently raising interest as a possible model for post-traumatic stress disorder (Jovanovic and
Ressler, 2010).
The most popular version of the CFC task was developed by Michael Fanselow
(Fanselow, 1980, 2000a) and consists of two phases. In the training phase, an animal is placed in
a chamber with a metal grid floor (context A). The animal is allowed to explore the chamber for
a few minutes and then receives a mild foot shock. In the probe phase, animals are returned to
the context in which they received the shock (Fig. 4A). During probe, learning of the context-
shock association leads to fear to receive a shock, expressed as periods of immobility, or absence
of all movement except for breathing, referred to as freezing behavior (Fanselow, 1982).
Freezing is believed to be part of a species-specific array of innate defensive reactions (Bolles,
1970) that occur in response to natural stimuli (Blanchard and Blanchard, 1972).
In the CFC task, from a Pavlovian perspective, the foot shock represents the US, and
freezing the CR. Freezing is incited by the context, which constitutes the CS (Fanselow, 2000b).
Freezing does not occur in the absence of shock, is specific to the context and proportional to
shock intensity (Fanselow, 1980), although generalization might occur (see later).
In a different version of the CFC task, an audible tone precedes the shock, and, during the
probe in a different chamber (context B), freezing in response to the tone is used as an index of
tone-shock association. Tone fear conditioning or auditory FC has been shown to depend on the
amygdala, where auditory and nociceptive stimuli converge to form the association that leads to
freezing (Maren et al., 1996; Maren, 2003; Rosen and Donley, 2006; Johansen et al., 2010, 2011)
(see Fig. 4B for a scheme).
23
The first evidence that contextual and auditory fear conditioning could involve different
brain circuits came in 1991. Selden and colleagues paired a clicker with a shock and saw a
double dissociation: animals with amygdala lesions were selectively impaired in conditioning to
the explicit cue (clicker), whereas animals with hippocampal lesions were selectively impaired in
conditioning to the context (Selden et al., 1991). This finding was later confirmed by different
groups (Kim and Fanselow, 1992; Phillips and LeDoux, 1992).
Figure 4. Fear conditioning scheme. Training and probe chambers and the experimental designs are illustrated. A.
Contextual fear conditioning. B. Tone fear conditioning. Adapted from Wang et al., 2008.
According to Fanselow, the initial exploration of the chamber creates a contextual
representation (‗gestalt memory‘) integrating all of its sensory components, i.e. visual
appearance, somatosensory components and odour, that is active at the time of, and comes to be
associated with, the shock (Fanselow, 2000b). Evidence for this comes from experiments
showing that a minimum amount of time spent exploring the chamber prior to the shock is
necessary in order for the contextual representation to become associated with the shock,
otherwise no freezing is observed during probe, a phenomenon called immediate shock deficit
(ISD) (Fanselow, 1990; Frankland et al., 2004). Pre-exposure to the context - but not its isolated
features - alleviates this deficit (Fanselow, 1990; Rudy and O‘Reilly, 1999; Frankland et al.,
2004).
Anterograde amnesia for contextual fear memories following dorsal hippocampal lesions
is found in some (Phillips and LeDoux, 1992; Young et al., 1994) but not other (Phillips and
LeDoux, 1994; Maren et al., 1997; Frankland et al., 1998) studies. A possible explanation
24
pertains to two possible forms of acquiring contextual information: polimodal (or configural) vs.
unimodal (or elementar). The hippocampus is believed to form a polimodal unified
representation of context (Sutherland and Rudy, 1989), although a unimodal component of the
context (e.g. tone, or a particular odour) may be sufficient to generate recognition - and freezing
- in the animal.
According to that view, in the absence of the hippocampus, other brain regions may
support learning about particular elements of the context (unimodal or elementar), hence
avoiding the anterograde amnesia, but are still unable to form a configural representation.
Consistent with this, animals with pre-training HPC lesions acquire CFC but are impaired in
contextual discrimination, a task best solved through polimodal-based contextual encoding
(Frankland et al., 1998).
Kim and Fanselow showed that hippocampal dependency of CFC is temporally graded
(Kim and Fanselow, 1992). Rats were subjected to tone and context conditioning and underwent
electrolytic lesions of the hippocampus 1, 7, 14 or 28 days after training. Memory to the context
was spared in all but the day 1 group, while tone memory was preserved, showing a temporally
graded retrograde amnesia for context memory (Kim and Fanselow, 1992), that was later
confirmed with between (Maren et al., 1997) and within subject designs (Anagnostaras et al.,
1999).
Additionally, animals pre-exposed to the training context 28 days before hippocampal
lesions did not present ISD (Young et al., 1994), reinforcing the notion that the hippocampus is
necessary for consolidating this unified representation of the contextual CS (not the CS-US
association), that is later stored elsewhere, consistent with the standard model of consolidation
(see section 1.1.3.2). Interestingly, the level of generalized freezing in context B also increases
with time, suggesting that memory precision is lost over time (Biedenkapp and Rudy, 2007;
Wiltgen and Silva, 2007; Winocur et al., 2007), fitting with multiple trace theory. Although it is
well accepted that the general contextual representation in fear conditioning is hippocampus
dependent, the level of hippocampal involvement in remote CFC memory is still under debate
(see also Wang et al., 2009).
25
1.2.4 Dentate Gyrus
Even though extensive work has been done in solidifying the connection between the
hippocampus and learning and memory, the specific contribution of the DG remains a topic of
some debate. Historically, the dentate gyrus has been the locus of crucial breakthroughs in the
field. LTP was first demonstrated in dentate granule cells (Bliss and Lømo, 1973), the very cells
in which local dendritic protein synthesis was first demonstrated (Aakalu et al., 2001; Jiang and
Schuman, 2002).
In terms of function, Rolls and others have proposed that the DG could be critical for
integrating information from different sensory inputs during the encoding of spatial
representations (Rolls, 1996). The link between DG function and spatial processing is supported
by an array of DG lesion studies describing significant deficits in acquisition and retrieval in
tasks such as the MWM (Sutherland et al., 1983; Nanry et al., 1989; Xavier et al., 1999; Jeltsch
et al., 2001), radial arm maze (Walsh et al., 1986; McLamb et al., 1988; Emerich and Walsh,
1989) and contextual fear conditioning (Lee and Kesner, 2004).
Spatial pattern separation has also emerged as a putative function of the DG, with support
from both quantitative modeling (O‘Reilly and McClelland, 1994; Rolls, 1996) and experimental
observations (Gilbert et al., 2001; Leutgeb et al., 2007; McHugh et al., 2007). Recently, adult
generated dentate granule cells were also implicated in this function (Clelland et al., 2009) (see
section 1.3.2.3).
The next subsections review some of the anatomical, biochemical and cellular
characteristics that may underlie the role the DG plays in information processing within the
hippocampal formation.
1.2.4.1 Anatomical organization
The dentate gyrus is composed of three layers: the molecular layer (ML), mostly devoid
of cells, but comprising the dendrites of dentate granule cells and efferent perforant path fibers,
26
the dentate granule cell layer (DGCL), a ~60m layer of densely packed granule cells, and the
hilus or polymorphic cell layer (Fig. 5A). During adulthood, an abundance of progenitor cells are
located at the bottom of the DGCL in contact with the hilus, a region referred to as the
subgranular zone (SGZ) (Fig. 5A) (Amaral et al., 2007).
The DG is further subdivided into three portions. The overall shape of the DG resembles
that of an arrow head, and CA3 protrudes into its concave surface serving as a reference for this
next anatomical division. The suprapyramidal (or upper) blade of the DG comprises the area
above the CA3 protrusion (located between CA3 and CA1). Opposite the upper blade is the
infrapyramidal (or lower) blade, located below the CA3 line. Connecting the two blades is the
crest (Fig. 5B). Granule cells in the upper blade have greater dendritic length, spine number and
density compared to those in the lower blade (Desmond and Levy, 1985; Claiborne et al., 1990).
Figure 5. Dentate gyrus organization. A. micrograph of the DG showing its organization in layers. B. Anatomical
division of the DG. ML=molecular layer, DGCL=dentate granule cell layer, SGZ=subgranular zone.
1.2.4.2 Genesis of the DG
The dentate gyrus is the last hippocampal structure to appear during development (Bayer,
1980). The genesis of the dentate gyrus can be divided into three phases: embryonic, infantile
and adult. Dentate granule cells originate in the primary dentate neuroepithelium, a germinal
matrix adjacent to the one that gives rise to pyramidal cell precursors (Altman and Bayer,
1990a). The onset of dentate development starts at embryonic day 16 (E16) in the rat (Bayer,
1980), with the proliferation of precursor cells from the primary dentate neuroepithelium. At
27
E18, the primary dentate matrix is surrounded by a secondary matrix that, at E19, initiates a first
wave of migration, leading to the formation of the outer shell of the DGCL, which is completed
at birth (Altman and Bayer, 1990a, 1990b).
A second wave of dentate migration reaches the dentate by the first few days after birth.
This second wave is the source of the tertiary matrix and the subgranular zone, the substrates for
the infantile and adult phases of DG development, respectively. The infantile (or postnatal) phase
starts at P1 and consists of a volumetric expansion of the DGCL by the tertiary matrix of the
dentate (Altman and Bayer, 1990b).
Even though the majority of granule cells originate from the secondary and tertiary
matrices, these germinal regions drastically decline around P10, and by P20-30 proliferating cells
from the tertiary matrix are no longer observed (Altman and Bayer, 1990b). This marks the onset
of the adult phase of DG development, when proliferative cells accumulate and are restricted to
the subgranular zone, where they continue to proliferate throughout the life of the animal
(Altman and Bayer, 1990b).
In the mouse DG a similar patter arises, with the first neurons detected at around E10,
and a peak at E17-18 (Angevine, 1965). The number of new cells largely declines at around P10
and, starting at P20, cells are fewer and restricted to the SGZ (Angevine, 1965), thus establishing
the onset of the adult phase of mouse DG neurogenesis, which also continues throughout life
(Kempermann et al., 1998).
1.2.4.3 Granule cells
Dentate granule cells have an elliptical soma of ~m width by ~18m height
(Claiborne et al., 1990). Their dendrites extend to the ML and receive anatomically-specific
inputs. The entorhinal projections are limited to the outer two thirds of the molecular layer: the
most superficial third of the molecular layer receives input from the lateral perforant path, and
the middle third is innervated by medial entorhinal fibers (Steward, 1976).
Presubiculum and parasubiculum projections also reach the molecular layer in a region
strewn between the perforant path projections (Köhler, 1985), suggesting a thalamic link to the
28
DG. Furthermore, other sources of input to the DGCL or the hilus are cholinergic and
GABAergic projections from the septal nuclei (Amaral and Kurz, 1985), glutamatergic
projections from hypothalamic nuclei (Kiss et al., 2000), noradrenergic input from the locus
coeruleus (Pickel et al., 1974), dopaminergic from the VTA (Amaral et al., 2007), and
serotoninergic from the raphe nuclei (Conrad et al., 1974; Vertes et al., 1999).
Granule cells project single axons towards CA3, forming the mossy fibers (MF). These
form predominantly excitatory synapses with hilar and CA3 interneurons and pyramidal CA3
cells. Still, MFs are not the only excitatory source for CA3 pyramidal cells. Stellate cells from
layer II of the entorhinal cortex and CA3 collaterals reach CA3 pyramidal cell apical and basal
dendrites (Steward, 1976; Li et al., 1994), and are important sources of excitation (Urban et al.,
2001).
1.2.4.4 Mossy Fibers: form and function
Mossy fibers have three types of terminals: large mossy boutons, filopodial extensions of
mossy boutons, and small varicosities. Mossy boutons predominantly contact pyramidal CA3
neurons at the most proximal point of their apical dendrites, in a narrow band just above the
pyramidal cell layer called stratum lucidum. A single granule cell contacts approximately 15
pyramidal cells, and a pyramidal cell receives a maximum of 50 mossy inputs (Amaral et al.,
1990).
Large mossy boutons have a high density of vesicles (Blackstad and Kjaerheim, 1961) in
more than one active zone and encompass a complex multi-headed postsynaptic CA3 spine
forming a structure called thorny excrescence (Amaral and Dent, 1981; Chicurel and Harris,
1992). From the mossy boutons emerges a set of filopodia collaterals predominantly innervating
a variety of GABAergic interneurons in the hilus (mossy cells, pyramidal basket cells) and CA3.
Small varicosities protrude from the granule cell axon and also contact mostly hilar and CA3
interneurons (Amaral and Dent, 1981).
The MF bouton‘s close proximity to CA3 pyramidal cells, and the large pool of vesicles
readily available (Hallermann et al., 2003) raise the view that the MF synapse could act as a
29
‗detonator‘, from which a single action potential from a granule cell could exert powerful
excitatory influence on a CA3 pyramidal cell. That and the sparcity of these inputs led to an idea
of a ‗teacher‘ synapse, instructing pyramidal cells to fire according to the pattern of granule cell
activity during learning (Treves and Rolls, 1992a, 1994). In this manner, the DG could have a
role in coding information from the EC into a sparse, pattern separated representation forwarded
to CA3 for storage (Acsády and Káli, 2007).
Not only could the CA3 store information received from the DG, it could also integrate
signals from the strong MF input with the weaker perforant path as a form of associative learning
(Mcnaughton and Morris, 1987; Lisman, 1999). Alternatively, Treves and Rolls proposed that
the MF, as a detonator, could force encoding into CA3 independent of other input sources, and
thereby be the driving force of acquisition; whereas the CA3, through its collaterals and
perforant path inputs would primarily be involved during retrieval (Treves and Rolls, 1992a).
Certain aspects of MF-CA3 physiology, however, argue against this detonator concept.
Small terminals and filopodia synapses outnumber mossy terminals by approximately 10 fold
(Bragin et al., 1995, Acsády et al., 1998). Activation of inhibitory interneurons by MF is very
reliable (Scharfman et al., 1990) and leads to a feedforward inhibition of CA3 pyramidal
neurons, so that MF release leads to monosynaptic activation and disynaptic inhibition of these
cells.
Additionally, glutamate is the primary excitatory neurotransmitter in granule cells
(Crawford and Connor, 1973; Terrian et al., 1988), but GABA is also produced and is present in
vesicles in the release zone, albeit at a lower concentration (Bergersen et al., 2003). These factors
make an argument against high reliability in DGC-pyramidal CA3 synapse relay. In fact, low
firing frequencies (<0.5Hz) rarely elicit a spike in CA3, preferentially activating interneurons
(Bragin et al., 1995a; Penttonen et al., 1997). Higher frequencies, however, breach the spike
threshold and depolarize pyramidal CA3 cells quite reliably (Henze et al., 2002).
This experimental evidence led Urban et al. to propose that instead of detonators, MF
synapses might function as ‗discriminators‘, such that at high frequencies the high reliability of
the MF-CA3 relay favours the decorrelation of similar inputs, or pattern separation, but at low
frequencies the silencing of DG inputs by interneuron driven inhibition would facilitate CA3‘s
role in collapsing similar inputs into one output, or pattern completion (Urban et al., 2001).
30
Experimental work has confirmed the importance of the trisynaptic pathway to memory
consolidation and its involvement in so called pattern completion (Nakashiba et al., 2008, 2009),
as well as implicating the DG in what is referred to as pattern separation (Gilbert et al., 2001;
Leutgeb et al., 2007), and has led to an an additional area of research, the potential contribution
of granule cells born during adulthood to this circuit (Clelland et al., 2009; Sahay et al., 2011a).
The integration of adult born granule cells into the hippocampal circuit and their contribution to
memory function is the theme of the next section.
1.3 Adult Neurogenesis
In spite of reports of adult neurogenesis from as early as the 1960‘s (Altman, 1962), it
was only recently fully accepted that new neurons are generated throughout adulthood in specific
regions of the brain. These regions include the subgranular zone (SGZ) of the dentate gyrus of
the hippocampus and the subventricular zone (SVZ) of the lateral ventricles (Zhao et al., 2008;
Deng et al., 2010). Under non-pathological conditions, neurogenesis in other areas of the brain is
not consistently found, remaining controversial (Gould, 2007). Although we know that neurons
born during adulthood mature (Petreanu and Alvarez-Buylla, 2002; Espósito et al., 2005; Zhao et
al., 2006), form functional synapses (Toni et al., 2007) and are incorporated into memory
networks (Kee et al., 2007; Stone et al., 2011b), the physiological significance of this
incorporation remains unclear.
This section first describes the history of adult neurogenesis, from discovery to
acceptance by the scientific community, followed by two main parts: hippocampal neurogenesis
and SVZ neurogenesis, reviewing factors involved in the regulation of neurogenesis, maturation
of adult born cells and their incorporation into existing circuitry, and possible functions.
1.3.1 History
31
The existence of adult generated neurons was controversial for almost a century. In the
beginning of the 20th
century the predominant view was that neurons divided only during
development, and stopped well before puberty (Ramón y Cajal, 1928, 1995; Gross, 2000).
Although reports of mitotic cells in the adult central nervous system of mammals did appear
(Hamilton, 1901; Allen, 1912; Sugita, 1918), it was technically impossible to confirm that
neurons, and not glia, were being born, and the idea was soon discarded.
In the 1950‘s, tritiated thymidine autoradiography became available, and proliferating
cells could finally be birth-marked and tracked. In the 1960‘s, pioneering work by Joseph
Altman showed for the first time 3H-thymidine labelled cells in the brain of adult mammals
(Altman, 1962), particularly in the hippocampus (Altman and Das, 1965) and olfactory bulb
(Altman, 1969). This discovery was disregarded for almost 2 decades, partly due to technical
concerns over the identification of those cells as neurons, and some believe also due to Altman
still being a young scientist going against a strong current (Gross, 2000).
In the 1970‘s, Michael Kaplan and colleagues provided the missing piece of the puzzle.
Through combination of 3H-thymidine injections and electron microscopy they were able to
identify the labeled cells as neurons in the olfactory bulb and dentate gyrus of adult rats and mice
(Kaplan and Hinds, 1977; Kaplan and Bell, 1984). In the 1980‘s, however, Pasko Rakic‘s report
that new neurons were absent in the adult rhesus monkey brain (Rakic, 1985) deeply influenced
the field, which remained dormant for a few years.
A few developments helped change that perspective. A series of elegant papers by
Nottebohm and colleagues using the canary vocal system extended the so far merely
morphological evidence for adult neurogenesis (Goldman and Nottebohm, 1983) into detailed
accounts of migration (Alvarez-Buylla and Nottebohm, 1988), axon targeting (Alvarez-Buylla et
al., 1988) and electrophysiological recordings (Paton and Nottebohm, 1984).
These studies gave way to a rediscovery of adult neurogenesis in the 1990‘s, further
prompted by technical developments such as markers for proliferation, cell type and maturation
stage (Mullen et al., 1992; Kuhn et al., 1996), and suggestions of a physiological function for
neurogenesis from evidence of regulation by stress (Gould et al., 1992; Gould and Tanapat,
1999), learning (Gould et al., 1999) and enrichment (Kempermann et al., 1997a). Finally, the
32
report of adult DG neurogenesis in humans (Eriksson et al., 1998) consolidated its existence and
increased the interest in studying adult neurogenesis in animal models.
1.3.2 Hippocampal neurogenesis
The generation of new neurons in the adult DG differs from embryonic neurogenesis in a
few critical ways. From P10-20 the progenitor cell pool is much diminished, is restricted to the
SGZ (Altman and Bayer, 1990b in rats; Angevine 1965 in mice; see section 1.2.4.2), and
generates one neuronal cell type: excitatory granule cells (Markakis and Gage, 1999; van Praag
et al., 2002; Lagace et al., 2007; Imayoshi et al., 2008). Given this qualitative and quantitative
difference, and the fact that adult neurogenesis persists throughout the life of the animal (Kuhn et
al., 1996 in rats; Kempermann et al., 1998 in mice), it is difficult to argue that neurogenesis
during adulthood is merely protracted development.
The issue of whether adult-generated dentate granule cells (aDGCs) replace old cells or
are added to a growing DG is still controversial. While some authors claim that the turnover rate
in the DGCL is low (Crespo et al., 1986), and neurons are continuously added to a growing
DGCL (Imayoshi et al., 2008), other authors fail to see an increase after 30d (Lagace et al., 2007)
or 4 months of age (Ninkovic et al., 2007). It is still technically challenging, even with
stereological techniques, to detect small differences in cell population numbers in the DGCL,
especially due to the high baseline (of around half a million cells) and age-related decline in
neurogenesis levels (Kuhn et al., 1996). Technical advances should help clarify this issue in the
near future.
1.3.2.1 Becoming an aDGC: from birth to senescence
1.3.2.1.1 Life and death in the adult DG
33
Cameron and McKay estimated that, in the rat brain, the duration of the cell cycle is of
approximately 25 hours, and 9000 new cells are generated each day (Cameron and McKay,
2001). This estimation was done using a mixture of two types of cell cycle markers, 5-bromo-2-
deoxyuridine (BrdU) and tritiated thymidine (Cameron and McKay, 2001), which are
incorporated into the DNA during the S phase of the cell cycle (Cavanagh et al., 2011). In the
C57/Bl6 mouse brain, the cell cycle is 12-14h long and 1600 cells are generated per day (Hayes
and Nowakowski, 2002). Furthermore, there are large differences in neurogenesis rates within
species due to genetic influences, with proliferation being at least 1.5 times higher in C57/Bl6
mice compared to other mouse strains (Kempermann et al., 1997b).
Long-term survival rates for adult born neurons are low, approximately 50% of new
neurons survive in the rat (Brandt et al., 2003; Dayer et al., 2003; Snyder et al., 2009a) and 30%
in the mouse (Kempermann et al., 1997b; Snyder et al., 2009), respectively. In C57/Bl6 mice,
BrdU positive cell numbers drop drastically between 1-3 weeks after labeling, but after 4 weeks
remain stable throughout the life of the animals (Kempermann et al., 1997b; Kempermann,
2003). This curve is similar in rats (Biebl et al., 2000; Snyder et al., 2009a). Since neuronal
markers are detected as early as 1-3 days after BrdU labeling (Brandt et al., 2003), this curve
suggests most of the long-term survival outcome occurs during the early post-mitotic period,
which coincides with synapse formation and integration into hippocampal circuitry (see next
sections).
1.3.2.1.2 Looking at morphology and electrophysiology
Adult neurogenesis in the hippocampus starts through the proliferation of neural
progenitor cells (NPCs) in the SGZ of the DG. As with embryonic development (Noctor et al.,
2002) and the SVZ (Doetsch et al., 1999), the SGZ progenitors present typical radial glia-like
morphology, with long processes reaching through the DGCL to the ML, and astrocytic qualities,
such as electrophysiological properties and expression of astrocytic markers (Filippov et al.,
2003; Fukuda et al., 2003).
34
The vast majority of the progeny of NPCs in the SGZ differentiates into dentate granule
cells (DGCs), whereas a minority becomes glia (Cameron et al., 1993). During the first week
after birth, young neuroblasts undergo a short radial migration into the inner-middle third of the
DGCL (Kempermann, 2003; Espósito et al., 2005; Zhao et al., 2006) and start projecting
processes. Although they lack synaptic connections at this stage, GABA and glutamate receptors
are already present (Espósito et al., 2005).
As is typical of neurons in the immature brain (Ben-Ari et al., 1989; Ben-Ari 2002 for a
review), GABA has a depolarizing action on immature aDGCs (Ge et al., 2006). The polarity of
GABA action is mostly driven by the expression of specific Cl- transporters, and the
developmental switch between GABA-driven excitation and inhibition appears to happen
through the sequential expression of the Na+–K
+–2Cl
– co-transporter NKCC1, a chloride
importer, and the K+-coupled Cl
- transporter KCC2, a chloride exporter (Delpire, 2000; Ben-Ari,
2002; Owens and Kriegstein, 2002). Indeed, knockdown of NKCC1 in aDGCs through shRNA-
expressing retrovirus led to GABA-induced hyperpolarization of 7 day old cells (Ge et al., 2006).
Interestingly, NKCC1-knockdown cells displayed defects in GABA- and glutamate-
mediated synapses and reduced dendritic arbourisation, whereas a GABA agonist induced
dendritic growth (Ge et al., 2006). Overall, this period of GABA activation seems critical to the
development of adult-generated granule cells (see also Tozuka et al., 2005), likely through a
CREB-mediated pathway (Ge et al., 2006; Jagasia et al., 2009).
During the second week neuroblasts start to present typical mature neuronal morphology,
with concomitant axonal and dendritic outgrowth. Dendrites reach the molecular layer at around
day 10, and their arbourization becomes complex (Zhao et al., 2006). Axons reach CA3 at
around day 7, before spinogenesis begins (Faulkner et al., 2008). Afferent synaptogenesis begins
around day 8, and, mirroring development, these early inputs are exclusively GABAergic, with
glutamatergic postsynaptic currents only being detected at day 16 (Espósito et al., 2005;
Overstreet Wadiche et al., 2005; Markwardt et al., 2009). Cholinergic innervation from septal
neurons has been reported, but no functional synapse has yet been demonstrated (Ide et al.,
2008).
The third week marks the onset of spinogenesis, on day 16 (Espósito et al., 2005; Ge et
al., 2006; Zhao et al., 2006; Toni et al., 2007). On day 17, synapses between aDGCs and
35
pyramidal CA3 cells are already present (Toni et al, 2008). Synaptic integration coincides with
the excitatory/inhibitory GABA switch and the onset of glutamatergic inputs, on day 18
(Espósito et al., 2005; Ge et al., 2006). Both filopodia/spines and axonal boutons tend to form
near pre-existing connections, suggesting a role for ongoing circuit activity in this integration
(Faulkner et al., 2008; Toni et al., 2008). Consistent with this, Tashiro and colleagues reported an
NMDAR-dependent critical window for survival at around 3 weeks, suggesting NMDA-receptor
mediated cell autonomous activity regulates cell death/survival during the third week after birth
(Tashiro et al., 2006).
By the fourth week the glutamatergic excitatory drive from the perforant path is fully
formed, with mature synapses reported as early as day 30 (Toni et al., 2007). Spine density is
still not equivalent to a mature cell, increasing until day 56, when it reaches a plateau (Zhao et
al., 2006). Hence, the glutamatergic input is still weak, but the high input resistance (that leads to
increased excitability) allows these immature neurons to spike in response to perforant path
axons (Espósito et al., 2005; Mongiat et al., 2009).
Around 4 weeks in the mouse (Ge et al., 2007b) and 2-3weeks in the rat (Schmidt-Hieber
et al., 2004), aDGCs are more excitable, displaying a lower threshold for LTP and higher LTP
amplitude, a process mainly driven by a differential expression of NR2B-containing NMDARs
(Ge et al., 2007b). This enhanced synaptic plasticity is transient, and restricted to the 4-6 weeks
window (Ge et al., 2007b). During this window, a weak stimulation paradigm is able to induce
LTP that is insensitive to GABAergic inhibition, which some researchers refer to as artificial
cerebrospinal fluid (ACSF)-LTP (Snyder et al., 2001; Saxe et al., 2006; Ge et al., 2008).
At about 6-8 weeks of age these cells are structurally and functionally mature in the
mouse (van Praag et al., 2002; Laplagne et al., 2006, 2007; Zhao et al., 2006; Faulkner et al.,
2008), even though morphological changes (spines, axonal boutons) continue to occur (Zhao et
al., 2006; Toni et al., 2007, 2008; Faulkner et al., 2008). This process appears to be faster in the
rat (Snyder et al., 2009a).
1.3.2.1.3 Looking at stages and markers
36
Puzzled by the parallel efflux of papers on regulation of neurogenesis (see next
subsection) and of morphological and electrophysiological description of aDGC maturation, but
lack of intersection between the two, Kempermann and colleagues set out to partition the aDGC
maturation process into a series of sequential steps - classified by morphological differences and
expression of selective markers - in the hopes that this would enable a deeper understanding of
neurogenesis regulation on a cellular level (Kempermann et al., 2004). Seri and colleagues had
proposed a different nomenclature and division of maturation stages for aDGCs (Seri et al.,
2001, 2004), but Kempermann‘s became predominant in the literature.
Their model consists of six stages (or milestones) (Kempermann et al., 2004). In the first
stage, a stem-like cell (type 1 cell) divides, leading to three consecutive stages (2-4) of divisions
of progenitor cells (or transit amplifying cells) that increasingly lose the potential to proliferate
and differentiate. These cells are referred to as type 2a, type 2b and type 3. Stage 5 consists of a
recent post-mitotic phase during which these immature neurons start making connections and
survival is determined. Stage 6 is that of a terminally diferentiated mature neuron (Kempermann
et al., 2004). Fig. 6 shows a scheme.
Type 1 cells are the putative stem cells of the SGZ (Seri et al., 2001). A stem cell is
defined by its capacity to self renew and to differentiate into specialized cell types (Weissman,
2000). Whereas the presence of stem cells in the SVZ is well accepted (Doetsch et al., 1999;
Seaberg and van der Kooy, 2003), the ‗stemness‘ of type 1 cells has been challenged for many
years, especially due to a lack of in vivo evidence for multilineage (Seaberg and van der Kooy,
2002, 2003; and see Morshead, 2004). Very recently, Bonaguidi and colleagues showed for the
first time in vivo evidence of self-renewal and generation of glial and neuronal cells from type 1
progenitors (Bonaguidi et al., 2011).
37
Figure 6. Scheme of the maturational stages of aDGCs. Each stage of maturation and the gradients of expression of
key markers is represented. Approximate peak expression as measured by days after BrdU administration are
signaled for some of the markers (see text for more extensive discussion). DCX=doublecortin.
SGZ progenitors or type 1 cells (Filippov et al., 2003) display astrocytic morphology (see
previous section) and expression of markers such as glial fibrillary acidic protein (GFAP)
(Filippov et al., 2003; Fukuda et al., 2003) but not S100 (Steiner et al., 2004). Another common
marker used to identify type 1 cells is the transcription factor Sox-2 (Komitova and Eriksson,
2004), from the sex determining region of Y-chromosome, SRY, related HMG- box (Sox) gene
family. Sox-2 is one of the earliest transcription factors to be expressed in the developing neural
tube (Cai et al., 2002).
Type 1 cells also express nestin, an intermediate filament named after ‗neuroepithelium
stem cells‘ due to its expression at earlier stages of neural differentiation (Lendahl et al., 1990).
Although type 1 cells comprise approximately one third of the nestin+ population, they are
responsible for only 5% of its cell divisions, meaning these cells are slow to divide and likely do
so assymetrically, also giving rise to a nestin-expressing type 2 cell (Filippov et al., 2003;
Kronenberg et al., 2003). In fact, nestin ceases to be expressed at the type 3 stage (Kronenberg et
al., 2003).
Type 2a and 2b cells do not express GFAP and have a very different morphology from
type 1 cells, with an ovoid or round nucleus, soma with scant cytoplasm, and short plump
processes that run tangentially to the SGZ, where they reside (Filippov et al., 2003). They are
38
also highly proliferative, particularly the type 2a cells (Kronenberg et al., 2003). Two main
factors distinguish type 2a from 2b: electrophysiological properties, mainly distinguished by the
presence of Na+ currents in the more differentiated type 2b cells (Filippov et al., 2003), and the
expression of the immature neuron marker doublecortin (DCX), which is absent in 2a
(Kronenberg et al., 2003).
DCX was first identified as being involved in neuronal migration in the cortex, since it is
mutated in lissencephaly syndrome/band heterotopia (a.k.a. double cortex) cases (Gleeson et al.,
1998; des Portes et al., 1998). It is expressed throughout development in migrating neurons of
the central and peripheral nervous system (Gleeson et al., 1999) and consists of a microtubule-
associated cytoplasmic protein necessary for migration (Tanaka et al., 2004). In the adult DG,
DCX is first expressed by type 2b cells and its expression continues until the immature neuron
stage. In a time course analysis with BrdU, DCX is expressed very early, consistent with its
presence in proliferating cells, which is further confirmed by its double-labeling with Ki67
(Brown et al., 2003). DCX expression in the rat peaks at 3-7 days and rapidly decreases
thereafter, being minimal at 4 weeks and undetectable at 8 (Brown et al., 2003). In the mouse,
DCX expression remains high until approximately day 21 (Snyder et al., 2009).
Another marker that mostly overlaps with DCX is the polysialated form of neural cell
adhesion molecule (PSA-NCAM). PSA-NCAM is a cell surface glycoprotein involved in
processes such as cell adhesion and neural morphogenesis (Seki and Arai, 1993a), and was one
of the first markers of immature neurons to be used in the adult DG (Seki and Arai, 1993b; Seki,
2002). Type 3 cells still express DCX and PSA-NCAM (but not nestin); are proliferative and
have a round nucleus (Kempermann et al., 2004).
After the last cell division these immature neurons undergo a phase marked by the
transient expression of calretinin (CR) around 3 days after the last division (Brandt et al., 2003).
CR is a calcium binding protein expressed in the hippocampus and commonly known as a
marker for specific interneuron populations (Rogers, 1987; Baimbridge et al., 1992; Gulyás et
al., 1992; Freund and Buzsáki, 1996). CR positive cells do not colabel with Ki67, thus CR is a
marker for the postmitotic stage (Brandt et al., 2003). Calretinin expression is detected one day
after BrdU, increases during the first week with a peak at 7 days, and decreases thereafter, being
undetectable at 6 weeks (Brandt et al., 2003).
39
Early post-mitotic cells exhibit vertical morphology (perpendicular to the SGZ in the
coronal plane) with an almost triangular nucleus and a pronounced apical dendrite (Kempermann
et al., 2004). The onset of CR expression nearly coincides with that of another marker, NeuN.
NeuN is a neuron-specific nuclear protein (Neuronal Nuclei) that was discovered through an
immunological screening with immunizations of brain cell nuclei (Mullen et al., 1992). It is
expressed by most neurons in the central nervous system and has recently been identified as the
RNA splicing regulator Fox-3 (Kim et al., 2009).
NeuN is detected as early as 1 day after BrdU injection by some groups (Brandt et al.,
2003; Kempermann et al., 2004), or at 10 days by others (Brown et al., 2003). NeuN/DCX
populations show the largest overlap between days 10-14, which subsides thereafter (Brown et
al., 2003). According to Brown and colleagues, the proportion of NeuN positive cells rapidly
increases from day 14-30, and then slows down (Brown et al., 2003; but see Snyder et al., 2009
for a discussion on making sense of the Brandt and Brown curves), but expression persists in
mature DGCs (Brandt et al., 2003; Brown et al., 2003), showing that NeuN is a marker of
immature and mature neurons.
The last stage is marked by a switch between CR expression and that of another calcium-
binding protein, calbindin (Brandt et al., 2003). Calbindin was originally isolated as an intestinal
calcium transport protein (Baimbridge and Miller, 1982), and was later found to be expressed in
the adult brain in all mature dentate granule cells (Sloviter, 1989). Also, through its calcium
binding abilities, it has been shown to play a facilitating role in MF synapses (Blatow et al.,
2003).
The CR-calbindin switch happens around 2-3 weeks after exiting the last cell division
(Kempermann et al., 2004), with calbindin expression being low on the first week after BrdU
labeling, but increasing over time and peaking at 3 weeks (Snyder et al., 2009a). Therefore, cells
still undergo maturation while expressing calbindin before they become indistinguishable from
their developmentally generated counterparts at 6-8 weeks of age (van Praag et al., 2002;
Laplagne et al., 2006, 2007; Zhao et al., 2006; Faulkner et al., 2008).
40
1.3.2.2 Regulating adult hippocampal neurogenesis
Adult neurogenesis has been shown to be bi-directionally regulated by a multitude of
factors. The number and heterogeneity of these factors have led researchers to wonder what does
not regulate adult neurogenesis (Kempermann, 2011). The next two sections review some of
these factors, from recent studies of punctual gene deletion to the most prominent extrinsic
manipulations shown to regulate neurogenesis.
To facilitate this description, neurogenesis regulators have been divided into two
categories, intrinsic or extrinsic, based on the nature of the manipulation. Therefore, studies that
have identified regulators of neurogenesis through gene deletion have been grouped in the
intrinsic section (1.3.2.2.1), and external manipulations (such as infusion of growth factors,
running, or stress hormones) are described in the extrinsic section (1.3.2.2.2). Importantly, it is
often technically challenging to determine whether certain factors exhert their action on aDGCs
in an exclusively intrinsic (cell autonomous) or extrinsic (non-cell autonomous) manner, and the
following separation is only meant to facilitate the review of this literature.
1.3.2.2.1 Intrinsic regulation
The use of transgenic and viral strategies to knock down specific genes has helped
surface several adult neurogenesis regulators. Starting this review from the nucleus onwards,
many transcription factors have been implicated in the regulation of adult neurogenesis. The
transcription co-factor PC3/Tis21 regulates proliferation and terminal differentiation of aDGCs
(Farioli-Vecchioli et al., 2008, 2009). Knockdown of transcription factor NF-B with an
CamKII promoter (around type 2b-3 stage) suggested a role in synaptogenesis, axogenesis and
survival (Imielski et al., 2012). During the critical period for survival of aDGCs, Krüppel like
factor 9, an activity-dependent transcription factor, seems critical for maturation and synaptic
plasticity, since its knockdown impairs ACSF-LTP (Scobie et al., 2009).
41
The HMG-box transcription factor Sox2 is a progenitor marker, present in type 1 and 2
cells, that precedes the expression of the proneural basic helix- loop-helix (bHLH) transcription
factor NeuroD1, transiently expressed at the type 3-immature stage (Kuwabara et al., 2009).
Work led by the groups of Jenny Hsieh and Fred Gage revealed a pathway in which Wnt/-
catenin signaling alleviates Sox2 repression to turn on NeuroD1 expression (Kuwabara et al.,
2009), which is necessary for aDGC survival and maturation (Gao et al., 2009). Another bHLH
transcription factor, Ascl1, is expressed in transient amplifying progenitors (Kim et al., 2011),
and has been implicated in neuronal commitment, since retrovirus mediated overexpression of
Ascl1 led to a switch in progenitor cells to the oligodentrocytic lineage (Jessberger et al., 2008b).
Sox2 has also been directly implicated in stem cell maintenance and differentiation (Ferri
et al., 2004; Cavallaro et al., 2008). Moreover, SoxC transcription factors Sox4 and Sox11 are
expressed at a time of neuronal commitment - starting at late transient amplifying stage (2b cells)
and stopping before calbindin expression - and seem to be necessary for aDGC differentiation
(Mu et al., 2012). Retrovirus mediated knockdown of the transcription factor cAMP response
element-binding protein (CREB) led to deficits in survival, maturation and morphological
development (Jagasia et al., 2009), with the reduction in dendritic length and arbourisation likely
being driven by CREB-mediated expression of microRNA mir132 (Magill et al., 2010).
Classic cell signalling molecules are also regulators of adult neurogenesis. Erk5 is
expressed in adult neurogenesis regions and regulates aDGC proliferation (Pan et al., 2012). The
transmembrane receptor Notch 1 is expressed in type 1 cells and maturing DCX positive cells
(Breunig et al., 2007). Ables and colleagues showed that Notch1 knockdown starting at the
nestin stage led to a decrease in proliferation, number of type 1-3 cells and dendritic complexity
of immature neurons (Ables et al., 2010). A similar study knocking down Notch1 in GFAP
positive cells in the postnatal brain (P10, P12 and P14) found comparable results (Breunig et al.,
2007).
Additionally, knockdown of Rbpj, an intracellular mediator of all Notch receptors, in the
adult brain led to premature differentiation of stem cells into transient amplifying cells, which
caused a transient increase in proliferation but later cessation of SVZ neurogenesis due to
depletion of the stem cell pool (Imayoshi et al., 2010). Together these studies open a door for a
deeper study of the role of Notch1-mediated lateral inhibition in the adult brain (Kageyama et al.,
42
2008; Ables et al., 2011). Curiously, a similar premature differentiation and depletion of
progenitor cells was induced by the overexpression of PC3, a gene associated with terminal
differentiation (Farioli-Vecchioli et al., 2008).
The same phenomenon was found with yet another cell signaling molecule, Pten, a tumor
suppressor protein that negatively regulates of the phosphatidylinositol-3-kinase (PI3K)
signalling cascade (Maehama and Dixon, 1998). Pten knockdown in adult progenitor cells leads
to increased proliferation and differentiation of aDGCs, eventually depleting the progenitor pool
(Amiri et al., 2012). Another tumor suppressor protein, Neurofibromin, a negative regulator of
Ras, modulates aDGC proliferation likely through an extracellular signal-regulated kinase
(ERK)-mediated pathway, but had no effect on differentiation (Li et al., 2012). Additionally,
both the orphan nuclear receptor TLX (Zhang et al., 2008) and adhesion molecules such as
NCAM (Amoureux et al., 2000) have been implicated in the control of aDGC proliferation.
Cycline dependent kinase 5 (Cdk5) is expressed in DCX+ and NeuN+ neurons (Lagace et
al., 2008) and plays an important role in neuronal migration, maturation and survival during
development (Jessberger et al., 2010). Two groups have independently shown that Cdk5 is also
important for aDGC maturation and survival (Jessberger et al., 2010). Using a transgenic
strategy, Lagace and colleagues knocked down Cdk5 in progenitor cells and showed that its
expression in immature neurons is necessary for survival (Lagace et al., 2008). Through
retrovirus mediated knockdown of Cdk5, Jessberger and colleagues showed a deficit in
migration and morphological maturation, with aberrant dendrite extension and formation of
ectopic synapses (Jessberger et al., 2008a).
Fragile X mental retardation protein (FMRP), a protein associated with a common
inherited form of mental retardation, was also shown to modulate adult neurogenesis, since
knockdown of fmrp in nestin positive progenitor cells led to increased proliferation, decreased
neuronal differentiation and dendritic complexity, as well as increased astrocytic differentiation
(Guo et al., 2011), suggesting a possible role of adult neurogenesis in the cognitive deficits seen
in fragile X syndrome patients.
Finally, on the interface between extrinsic and intrinsic, between environment and genes,
lie a complex array of epigenetic factors whose function in the regulation of adult neurogenesis
is beginning to be elucidated (Ma et al., 2010; Sun et al., 2011).
43
1.3.2.2.2 Extrinsic regulation
Environmental enrichment (EE) consists of a more complex and socially rich
environment compared to standard animals housing conditions, usually involving a bigger cage
with toys, tunnels, nesting materials and often running wheels (van Praag et al., 2000). EE leads
to increased survival (Kempermann et al., 1997a; Nilsson et al., 1999; van Praag et al., 1999b) of
nestin negative cells (type 3 onwards) (Kronenberg et al., 2003) or cells of about 2 weeks of age
(Tashiro et al., 2007), probably during the critical period for long-term survival of aDGCs.
Voluntary running has been shown to increase proliferation in young (van Praag et al.,
1999a, 1999b; Kronenberg et al., 2003) and old (van Praag et al., 2005) animals. This effect
seems to take place at the level of type 2b cells (Kronenberg et al., 2003), and leads to an
increase in the proportion of NeuN positive cells (van Praag et al., 1999b) and in the number of
arc positive cells in response to seizures, possibly indicative of functional maturation (Snyder et
al., 2009b). With at least 14 days of running, survival of new neurons is also increased (Muotri et
al., 2009; Snyder et al., 2009b).
Network activity also alters rates of adult neurogenesis. Entorhinal cortex stimulation
through deep brain stimulation leads to an increase in cell proliferation in the DG (Stone et al.,
2011a). LTP induction through perforant path tetanus enhances survival of cells at least 1-2
weeks old (Bruel-Jungerman et al., 2006) and proliferation (Bruel-Jungerman et al., 2006; Chun
et al., 2006) in a NMDA-dependent manner (Chun et al., 2006). As with glutamate (through
NMDARs) and GABA (see section 1.3.2.1.2), other neurotransmitters such as acetylcholine
(Kaneko et al., 2006), serotonin (Brezun and Daszuta, 1999) and dopamine (Höglinger et al.,
2004) have been proposed to alter the proliferation, survival or differentiation of aDGCs (Jang et
al., 2007; Balu and Lucki, 2009). Additionally, epileptic seizures increase proliferation and
interfere with the maturation of type 3 cells leading to abnormal migration and functional
integration (Parent et al., 1997; Jessberger et al., 2005, 2007; Overstreet-Wadiche et al., 2006).
Growth factors such as fibroblast growth factor 2 (FGF-2) (Rai et al., 2007; Zhao et al.,
2007) and vascular endothelial growth factor (VEGF) (Jin et al., 2002), and neurotrophic factors
44
such as brain derived neurotrophic factor (BDNF) (Scharfman et al., 2005; Balu and Lucki,
2009) interfere with proliferation and survival and are likely important endogenous regulators of
adult neurogenesis.
The relationship between stress and the hippocampus has been extensively studied, from
glucocorticoids affecting hippocampal structure and function (McEwen and Sapolsky, 1995;
McEwen, 2006; Joëls et al., 2007) to hippocampal regulation of the HPA axis (Jankord and
Herman, 2008; and see section 1.2.2). Stress is a powerful suppressor of neurogenesis (Gould
and Tanapat, 1999). Physical (Malberg and Duman, 2003; Pham et al., 2003; Vollmayr et al.,
2003), psychosocial (Gould et al., 1998; Czéh et al., 2002), acute (Gould et al., 1997; Heine et
al., 2004) or chronic stress (Czéh et al., 2002; Heine et al., 2004) decrease proliferation and
survival.
Interestingly, depression-like behaviours are associated with dysregulation of
glucocorticoids (Holsboer and Ising, 2010), and most antidepressants stimulate neurogenesis
(Malberg et al., 2000; Sahay and Hen, 2007). Linking neurogenesis and depression, Dranovsky
and colleagues recently showed that the actual ratio of stem cells to neurons can be modulated by
experience, with social isolation causing an accumulation of type 1 cells to the detriment of
neurogenesis (Dranovsky et al., 2011). In a recent report, Snyder and colleagues directly
implicated aDGCs in HPA axis regulation, showing they function as a buffer to temper stress
responses, which possibly provides a physiological link to depression (Snyder et al., 2011).
The first indication that learning could regulate neurogenesis came in 1999 with work by
Elizabeth Gould and colleagues. They showed that two hippocampus-dependent tasks (trace
eyeblink conditioning and MWM), but not their hippocampal independent counterparts (delay
eyeblink conditioning and visible MWM), increased the survival of aDGCs (Gould et al., 1999).
The survival effect seems to be specific to cells 6-10 days old (Ambrogini et al., 2000; Hairston
et al., 2005; Epp et al., 2007; Sisti et al., 2007), a time in which new neurons are extending axons
and starting to form connections.
Another report claimed different phases of MWM training had different effects on
neurogenesis. The initial, more challenging, phase of MWM training increased survival of
aDGCs, whereas a later phase of training increased cell death of 5d old neurons, which
correlated with performance and increased proliferation (Döbrössy et al., 2003). The same group
45
later showed that this increase in cell death of 5d old neurons seems to be necessary for learning,
and that the increase in proliferation and the pro-survival effect on 1 week old cells are
homeostatic responses to this cell death (Dupret et al., 2007).
1.3.2.3 Functional significance of adult hippocampal neurogenesis to learning and memory
The fact that the hippocampus is one of two brain regions with adult neurogenesis
prompted the question of whether these aDGCs could be involved in memory formation. The
function of aDGCs in learning and memory has been investigated within two basic frameworks:
in silico computational modeling studies and animal gain or loss of function studies. Due to the
nature of our experiments and to facilitate the description of the literature, the animal studies will
be further divided into two parts: one involving the behavioural impacts of extrinsic or intrinsic
manipulations through which neurogenesis levels are increased or decreased (referred to as
correlative studies), and ablation studies.
1.3.2.3.1 Function of aDGCs: computational networks
Several computational models of DG function have been critical for testing predictions
and putting forward new potential functions for aDGCs. Even though there is a considerable
degree of variability in the models, some general concepts emerge from the in silico adult
neurogenesis work. The potentially privileged position of the DG to pattern separate, largely
driven by its characteristic sparsification and orthogonalization of signals to CA3, has been
predicted by models (Treves and Rolls, 1992b) and found experimental support (Lee and Kesner,
2004; Leutgeb et al., 2007; McHugh et al., 2007) (see section 1.2.4), but how would
continuously adding neurons to this network contribute to its function?
46
Aimone and colleagues propose that whereas mature granule cells contribute to pattern
separation, immature aDGCs are ‗pattern integrators‘ (Aimone et al., 2009). Their rationale is
that the hyperexcitability that aDGCs experience during their maturation could lead to
indiscriminate firing and incorporation into an already existing CA3 representation. Thus, while
mature DGCs orthogonalize signals from the EC and pattern separate, immature aDGCs are
forming associations between events, or pattern integrating (Aimone et al., 2009). Consistent
with this view, a recent report has shown, in hippocampal slices, that 4 week old cells are almost
twice more likely to spike in response to two independent perforant path inputs (pattern
integrate) when compared to mature DGCs (Marín-Burgin et al., 2012).
However, this hyperexcitable period is time restricted, and the surviving neurons will
indelibly mature and contribute to sparse encoding. Therefore, within each wave of neurogenesis
exists a unique window of time when less strict associations are formed. It has been speculated
that this window could promote associations between events that happened around the same
period of time (Aimone et al., 2006). Although alluring, this prediction has not yet been
confirmed experimentally.
Becker and Wojtowicz also take this hyperplasticity period of aDGCs into consideration
to propose what they call a ‗functional cluster‘ (Becker and Wojtowicz, 2007). Since adult
neurogenesis occurs in waves and clusters of proliferating cells are commonly seen, they
stipulate that these clusters, maturing at the same rate, could encode different features of an event
or context through their differential perforant path afferent inputs, and, due to their shared
plasticity tempo, remain tuned to promptly respond to re-exposure to the same context (Becker
and Wojtowicz, 2007). Aimone and colleagues find that the neurons that respond the most to a
given environment are the ones that had been exposed to that environment when around 3 weeks
of age (Aimone et al., 2009), consistent with Becker and Wojtowicz‘s idea of a maturation-stage
dependent collective representation of a context.
Another prediction from computational models comes to tackle a riddle in hippocampal
function. It is speculated that within a restricted set of neurons, continuous new learning could
eventually exhaust the number of possible encoding patterns, thus leading to new information
overwriting an already existing pattern, a phenomenon known as catastrophic interference
(McClelland et al., 1995). In that sense, the continuous addition of new neurons throughout life
47
could increase memory storage capacity and prevent such catastrophic interference (Wiskott et
al., 2006).
On the other hand, this constant addition of new neurons and excess of excitatory drive
could in itself lead to indiscriminate activation of downstream neurons and degradation of pre-
existing memory traces. A model created by Meltzer and colleagues shows that addition of new
neurons in the absence of homeostasic mechanisms (i.e, turnover of cells or scaling back of
overall network activity) can lead to vast memory impairment (Meltzer et al., 2005).
1.3.2.3.2 Function of aDGCs: correlative studies
Several of the intrinsic and extrinsic regulators of neurogenesis reviewed in sections
1.3.2.2.1 and 1.3.2.2.2 also influence learning and memory. Some of the first observations
strengthening the idea that new neurons could be important for memory came from observations
that manipulations that increase neurogenesis (e.g. EE, running) also facilitate learning, whereas
manipulations that decrease neurogenesis (e.g. stress, aging, depressive states) also impair
learning. For instance, EE causes a mild facilitation of MWM acquisition (Kempermann et al.,
1997a; Nilsson et al., 1999) and improves performance in an object recognition task (Bruel-
Jungerman et al., 2005), and running increases DG LTP and facilitates MWM acquisition (van
Praag et al., 1999a, 2005).
However, manipulations such as running or EE have physiological consequences beyond
neurogenesis (e.g. effects on anxiety, motivation, and mood), which has made it difficult to
prove the causal link between enhanced neurogenesis and improved cognition. Running or EE in
the absence of neurogenesis, through pharmacological agents or X-ray irradiation, has yielded
mixed results, eliminating the EE-driven improvement in recognition memory (Bruel-Jungerman
et al., 2005), but not interfering with the spatial memory improvement (Meshi et al., 2006).
Using the inverse approach, Sahay and colleagues devised a transgenic strategy to
increase the survival of aDGCs in a cell autonomous manner (Sahay et al., 2011a). Augmenting
48
neurogenesis enhanced ACSF-LTP and facilitated acquisition of a contextual discrimination
task, but had no effect on MWM learning (Sahay et al., 2011a).
Additionally, although there are reports of correlations between neurogenesis levels and
cognitive performance during aging (Drapeau et al., 2003; Driscoll et al., 2006) or stress (Shors,
2004; Montaron et al., 2006), they are not always consistent (Bizon et al., 2004) and, as with
running and EE studies, could be a symptom of a more complex phenomenon (Shors, 2004;
Klempin and Kempermann, 2007).
More recently, genetic deletion of some intrinsic regulators of neurogenesis was also
shown to impact behaviour. Decrease of neurogenesis caused by deletion of the orphan receptor
TLX (Zhang et al., 2008) or the fragile X syndrome protein FMRP (Guo et al., 2011) led to a
mild impairment in MWM, and to deficits in contextual and tone fear conditioning, respectively.
Attenuation of neurogenesis caused by Erk5 knockdown in progenitor cells impaired CFC (weak
shock) and reversal learning in the MWM (Pan et al., 2012). Interestingly, lentivirus mediated
knockdown of the Wnt signaling pathway in the DG also decreased neurogenesis and impaired
long-term MWM memory retention (Jessberger et al., 2009).
Manipulations that alter the maturation program of aDGCs can also lead to memory
deficits. Induction of differentiation in progenitor cells through expression of the
prodifferentiative gene PC3 decreased LTP and caused deficits in the MWM, radial maze and
CFC (Farioli-Vecchioli et al., 2008), whereas embryonic deletion of the transcription factor
Krüppel-like factor 9, which decreases differentiation, led to an anxiety phenotype and impaired
contextual fear discrimination (Scobie et al., 2009).
1.3.2.3.3 Function of aDGCs: ablation studies
Several studies have used pharmacological, irradiation, and, more recently, transgenic
approaches to examine the effects of ablating adult born neurons on memory formation. The first
direct implication of aDGCs in memory function came in 2001, when Shors and colleagues
reduced neurogenesis levels by treating rats with the antimitotic drug methylazoxymethanol
49
acetate (MAM) and saw an impairment in trace eyeblink conditioning, a hippocampus dependent
task, but not in delay eyeblink conditioning, which is hippocampus independent (Shors et al.,
2001). Subsequent work showed, however, that not all hippocampus dependent tasks are
impaired by blockade of neurogenesis (Shors et al., 2002), on perhaps an epilogue for the whole
subfield (see the supplemental table in Deng et al., 2011 for a complete listing).
Ablation of neurogenesis is sometimes found to impair hippocampus dependent
contextual fear conditioning (Saxe et al., 2006; Winocur et al., 2006; Imayoshi et al., 2008;
Warner-Schmidt et al., 2008; Hernández-Rabaza et al., 2009; Ko et al., 2009; Snyder et al.,
2009a; Denny et al., 2011) but other times has no effect (Shors et al., 2002; Dupret et al., 2008;
Zhang et al., 2008; Deng et al., 2009) . Although one study reported a deficit in hippocampus
independent tone fear conditioning after ablation of neurogenesis (Shors et al., 2002), most
studies see no effect (Saxe et al., 2006; Winocur et al., 2006; Imayoshi et al., 2008; Warner-
Schmidt et al., 2008; Zhang et al., 2008).
Regarding spatial memory, some studies report that neurogenesis ablation does not affect
MWM performance (Shors et al., 2002; Madsen et al., 2003; Raber et al., 2004; Meshi et al.,
2006; Saxe et al., 2006), whereas other studies report a deficit during acquisition (Dupret et al.,
2008; Zhang et al., 2008; Deng et al., 2009) or reversal learning (Garthe et al., 2009).
Furthermore, some studies show intact acquisition but a deficit in long-term ( > 2 weeks)
retention (Snyder et al., 2005; Jessberger et al., 2009).
Interestingly, consistent with the deficits found when flexibility of spatial information
was required, as in reversal learning (Dupret et al., 2008; Garthe et al., 2009), a recent report
showed a role for adult born neurons in cognitive flexibility, or the ability to selectively use
previously acquired information when there is a change in contingencies (Burghardt et al., 2012),
which had been predicted earlier by computational models (Wiskott et al., 2006)
These ablation studies vary in terms of ablation technique, degree of ablation, age of the
cells affected, animal species (and strain) and behavioural protocol. Some or all of these factors
could contribute to the contradictory results. For a detailed discussion on this topic see chapter 6.
A few papers have raised other interesting functions for adult hippocampal neurogenesis,
including regulation of stress-induced social avoidance (Lagace et al., 2010), vulnerability to
50
cocaine addiction and relapse (Noonan et al., 2010), systems consolidation, by regulating the
hippocampus dependent period of memory (Kitamura et al., 2009), and pattern separation
(Clelland et al., 2009; Sahay et al., 2011a; Nakashiba et al., 2012; Tronel et al., 2012). This last
topic has emerged as a strong putative function of aDGCs and will be discussed in detail in
chapter 6.
1.3.3 Olfactory neurogenesis
Similar to the DG, most the olfactory bulb (OB) neurogenesis occurs postnatally and
continues throughout adult life (Kaplan and Hinds, 1977; Bayer, 1983). The largest germinal
zone in the adult brain lies in the lateral walls of the lateral ventricles, the SVZ. Neurons born in
the SVZ migrate anteriorly through the rostral migratory stream (RMS) to the olfactory bulb,
where they differentiate mostly into two types of interneurons, olfactory granule cells (OGCs)
and periglomerular cells (PGCs) (Altman, 1969; Lois and Alvarez-Buylla, 1994; Doetsch and
Alvarez-Buylla, 1996) (see Fig. 7A).
Figure 7. Olfactory system. A. Neuroblasts born in the subventricular zone migrate through the rostral migratory
stream toward the olfactory bulb where they differentiate into granule cells and periglomerular cells. B. Scheme of
the olfactory circuit. Sensory information is transduced from olfactory sensory neurons into mitral and tufted cells in
the OB. These relay information to higher order cortical structures, which is modulated by olfactory interneurons,
granule and periglomerular cells. The flow of information from the outside world into the cortex is named bottom up
pathway (black arrows). Cortical areas also regulate olfactory interneurons through centrifugal fibers in what is
referred to as the top-down pathway (purple arrows). LV=lateral ventricle, SVZ= subventricular zone, RMS= rostral
migratory stream, GCL=olfactory granule cell layer, Glut=glutamate
51
In the following subsections, the olfactory system is briefly described with an emphasis
on anatomical circuitry, followed by a discussion of adult neurogenesis in the olfactory system
and description of the the trajectory of olfactory neuroblasts from birth through their migration
and final differentiation. Behavioural experiments that attempt to elucidate the function of these
adult born interneurons are discussed in a separate sub-section.
1.3.3.1 Olfactory system: an overview
Olfaction is a very important sensory modality, crucial for finding food, social
interactions like mating, conspecific recognition and maternal behaviours, as well as detecting
danger. The chemosensory starting point of this system is the main olfactory epithelium, where
olfactory sensory neurons – lined with olfactory receptors – transduce chemical stimuli into
spike trains. This leads to glutamate release through the olfactory nerve to glomeruli in the main
olfactory bulb, reaching the distal dendrites of mitral and tufted cells (Lledo et al., 2005 but see
Gire et al., 2012). These mitral and tufted cells act as relay neurons to higher olfactory structures
such as piriform cortex, anterior olfactory nucleus, and entorhinal cortex (Korsching, 2002) that
further process olfactory information (Wilson and Sullivan, 2011). Because this flow of
information goes from the external environment to the brain this is called a bottom-up pathway
(see Fig. 7B for a scheme).
Nonetheless, the OB circuit is more than a relay station, it refines olfactory information
through two classes of inhibitory interneurons, OGCs and PGCs, that facilitate mitral cell
syncronization and network oscillations (Bathellier et al., 2006; Lagier et al., 2007). PGCs are
GABAergic and dopaminergic, and connect either directly to the olfactory nerve or the primary
dendrites of mitral/tufted cells (Kosaka and Kosaka, 2005). OGCs are GABAergic and represent
over 90% of bulbar interneurons, connecting and inhibiting mitral cells via reciprocal
dendrodendritic synapses (Wilson, 2008; Mouret et al., 2009b).
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Excitation of mitral/tufted cells leads to glutamate release into OGCs that in turn inhibit
neighbouring mitral/tufted cells. This lateral inhibition has been shown to be essential for
olfactory discrimination (Yokoi et al., 1995; Abraham et al., 2010), and enhancement of
olfactory discrimination is accompanied by an increase in OGC recruitment (Mandairon et al.,
2008). Additionally, it is speculated that the oscillatory synchronization generated by
interneurons could be critical for sparcification of an otherwise distributed and redundant
stimulus representation, thus being essential for olfactory learning/encoding (Laurent, 2002;
Lledo and Lagier, 2006; Nusser et al., 2012; but see Wilson and Stevenson, 2003 and Vincis et
al., 2012).
The OB is a laminar structure divided in seven layers (see Fig. 8). The most external is
the olfactory nerve layer (ONL), containing axons from olfactory sensory neurons and glia. The
next layer is the glomerular layer (GL), containing spherical neuropil rich structures surrounded
by neurons and glia called glomeruli. It is through the ONL that external input reaches the
glomeruli, activating mitral/tufted and periglomerular cells (Shipley and Ennis, 1996; Lazarini
and Lledo, 2011).
Figure 8. Structure of the olfactory bulb. OB micrograph showing its layers. From the most superficial to the
deepest: the olfactory nerve layer (ONL), followed by the glomerular layer (GL), external plexiform layer (EPL),
mitral cell layer (MCL), internal plexiform layer (IPL) and finally the olfactory granule cell layer (OGCL). At the
core of the OB, with a higher nuclear density, is the rostral migratory stream.
Under the GL is the external plexiform layer (EPL), containing mostly dendrites of
mitral/tufted cells and granule cells. Subjacent to the EPL lies the mitral cell layer (MCL), a thin
monolayer of mitral cell somata. Immediately deeper is the internal plexiform layer (IPL),
53
containing the axons of mitral/tufted cells that lead out to the cortex as well as granule cell
dendrites. This layer is followed by the granule cell layer (OGCL to distinguish from the
DGCL), containing the aggregated granule cell bodies (often united through gap junctions).
Finally, at the core of the OB lies the rostral migratory stream (Shipley and Ennis, 1996; Lazarini
and Lledo, 2011).
This circuit is further regulated by a top-down pathway that stems from higher order
structures such as frontal and olfactory cortices through centrifugal fibers back to OGCs and
PGCs at the OGCL and GL, respectively (Fig. 7B). The inputs from these centrifugal fibers are
believed to add contextual information to olfactory processing, such as attention, behavioural
state and learning context (Mouret et al., 2009b). Furthermore, the addition of new neurons and
their early regulation by centrifugal forces could contribute to this process (Whitman and Greer,
2007; Panzanelli et al., 2009).
1.3.3.2 Olfactory neurogenesis: birth, migration and maturation
The subventricular germinal zone is composed of three basic cell types: stem cells,
proliferating progenitors and migrating neuroblasts (Doetsch et al., 1997). The SVZ is separated
from the ventricular cavity by an epithelium monolayer of ependymal cells (E cells) (Doetsch et
al., 1997). The stem cells of the SVZ are periventricular astrocytes, also referred as B cells.
These cells have been shown to have all the characteristics of stem cells (Doetsch et al., 1999;
Seaberg and van der Kooy, 2003; Garcia et al., 2004), astrocytic morphology and expression of
GFAP and nestin (Doetsch et al., 1997). B cells give rise to C cells, transit amplifying cells, that
in turn give birth to migrating neuroblasts, A cells (Doetsch et al., 1999). D cells, or tanycytes,
are less common but reside between E cells, contacting the ventricle with microvilli in their
luminal surface (Doetsch et al., 1997).
C cells are the most proliferative cells in the SVZ. They are large and have a spherical
morphology, are nestin positive and are normally present in clusters or isolated in proximity to a
chain of A cells, which they presumably generate (Doetsch et al., 1997). Type A cells have
elongated cell bodies with one or two processes, are nestin, PSA-NCAM and Tuj1 [a class III
54
tubulin marker that stains young neurons (Geisert and Frankfurter, 1989; Easter et al., 1993)]
positive, forming elongated chains of 1-4 cells wide and 20-30 cells long ensheathed by B cells
(Doetsch et al., 1997).
These chains of A cells migrate tangentially 3-8 mm through the rostral migratory stream
until they reach the OB, in approximately 5-12 days (Altman, 1969; Lois and Alvarez-Buylla,
1994; Doetsch and Alvarez-Buylla, 1996; Petreanu and Alvarez-Buylla, 2002). Once there, they
detach from the chains and migrate radially to reach the outer or more superficial layers of the
OB (Lois and Alvarez-Buylla, 1994). The vast majority of neuroblasts (over 90%) differentiate
into granule cells, with a minority (~3%) differentiating into periglomerular cells (Winner et al.,
2002; Lazarini and Lledo, 2011). Neuroblasts can also differentiate into juxtaglomerular cells,
glutamatergic interneurons, but in a very small proportion (Brill et al., 2009). The rate of cell
death for these differentiating neuroblasts is very high, over 50% during the first 2 months
(Winner et al., 2002).
Granule cells form clusters in the OGCL, where, having no axon, they extend a large
dendrite towards the EPL, making dendrodentritic connections with mitral cells present in the
mitral cell layer, and becoming fully mature at around 2 weeks of age (Shipley and Ennis, 1996;
Petreanu and Alvarez-Buylla, 2002). Using retrovirus labeling of neurons born in the adult SVZ,
Petreanu and Alvarez-Buylla divided granule cells into 5 classes based on their maturational
state (Petreanu and Alvarez-Buylla, 2002).
Class 1 is composed of tangentially migrating neuroblasts in the RMS, from days 2 to 7.
These cells have a small elongated cell body with one prominent process and small trailing ones.
Around day 5, class 2 neuroblasts arrive at the OB and start radial migration, during which their
processes become longer and they start expressing Tuj1. At day 9, class 3 cells have completed
their migration, are larger, rounder and have a single process, the apical dendrite, that remains
unbranched and does not extend beyond the MCL (Petreanu and Alvarez-Buylla, 2002).
Class 4 cells, around day 13, have elaborate branched dendrites but no spines, whereas
class 5 cells, around day 15, are mature OGCs with a high density of dendritic spines on their
apical dendrite (Petreanu and Alvarez-Buylla, 2002). Although spines are present around day 15,
pre and postsynaptic markers are not observed until day 21, suggesting a role for system activity
55
(centrifugal, mitral/tufted cells) in regulating aOGC maturation and incorporation into the
olfactory circuitry (Whitman and Greer, 2007)
Class 1 and 2 cells lack voltage-gated Na+ conductance, and are thus unable to spike, but
already express functional GABAA receptors and some AMPA receptors with GluR2 subunits
(Carleton et al., 2003). Over the course of radial migration (class 2) they start expressing
NMDARs. Migrating neuroblasts (class 1 and 2) express DCX and PSA-NCAM (Bonfanti and
Theodosis, 1994; Belluzzi et al., 2003).
Immature aOGCs are silent or non-spiking for most of their maturation: class 3 cells
already receive synaptic inputs but action potentials only start to be seen at the end of class 4 and
beginning of class 5 (Carleton et al., 2003). Starting at day 10 (class 3) cells start expressing
mature markers such as NeuN, calretinin, GABA and TH (Winner et al., 2002). Class 5 cells
were reported to be indistinguishable from their developmentally-generated counterparts
(Carleton et al., 2003), but were later shown to display a restricted time window of
hyperplasticity, present at 2 weeks of age and mostly lost at 8 weeks (Nissant et al., 2009).
The maturation of aPGCs differs from that of OGCs in a few key aspects. Periglomerular
cells‘ full axonal and dendritic maturation takes longer, around 4 weeks and, in constrast to
OGCs, their maturation of voltage dependent Na+ current and consequent ability to generate
action potentials precedes the presence of synaptic contacts (Petreanu and Alvarez-Buylla, 2002;
Belluzzi et al., 2003; Carleton et al., 2003). Similar to aOGCs, the first input to aPGCs is
GABAergic, which later becomes glutamatergic (Belluzzi et al., 2003).
Unlike the DG, in the olfactory bulb several pieces of evidence point towards a dynamic
replacement or turnover of neurons: the OB does not increase in size (Pomeroy et al., 1990),
there is continual apoptosis in the layers where new neurons are present (Fiske and Brunjes,
2001), and a very small proportion of neurons survive past 21 months (Kaplan et al., 1985).
More recently, definitive evidence confirmed the existence of the turnover, showing that adult
neurogenesis in the OB replenishes the population of interneurons (Imayoshi et al., 2008).
56
1.3.3.3 Olfactory neurogenesis: intrinsic regulators
The specialized microenvironment responsible for regulating adult stem cell renewal and
neuroblast differentiation is referred to as the adult neurogenic niche (Alvarez-Buylla and Lim,
2004), allowing for a series of intrinsic-extrinsic interactions necessary for regulating
proliferation, cell fate and migration.
Classical development signaling pathways are present in the adult neurogenic niche, such
as BMP-Noggin, which is implicated in adult SVZ cell fate (Lim et al., 2000). Similarly, the
Ephrin family and their Eph tyrosine kinase receptors are crucial for axon guidance and cell
migration in the adult brain (Egea and Klein, 2007). EphB1–3, EphA4, EphA7 and their
transmembrane ligands, ephrins-B2/3 and A2, are expressed in the SVZ and are necessary for
neuroblast migration and proliferation (Conover et al., 2000; Holmberg et al., 2005). Sonic
Hedgehog signaling regulates progenitor cell maintenance and proliferation in the adult SVZ and
SGZ (Lai et al., 2003; Machold et al., 2003), similar to its functions during development
(Fuccillo et al., 2006). In vitro neurosphere assay data also suggests a role for Notch signaling in
the control of SVZ progenitor differentiation (Grandbarbe, 2003).
The transcription factor Pax6 is necessary for initial neuronal specification, being
expressed in an increasing gradient along the RMS towards the OB, with its persistent expression
leading to a dopaminergic periglomerular cell phenotype (Hack et al., 2005; Kohwi et al., 2005).
Transcription factors such as E2F1, traditionally linked to cell cycle regulation (Yoshikawa,
2000), seem to be involved in the control of adult neuroblast proliferation in the SVZ and SGZ
(Cooperkuhn et al., 2002). The glicosilphosphatidil inositol anchored signaling protein CD24 has
also been implicated in the control of SVZ proliferation (Belvindrah et al., 2002).
Lastly, a recent report shines light onto possible molecules necessary for the synaptic
integration of adult born olfactory interneurons into the OB circuit. The proteoglican Agrin, also
important during development and primarily studied as a synapse inducing factor in the
neuromuscular junction (Williams et al., 2008), was found to be necessary for survival and
morphological differentiation of olfactory interneurons (Burk et al., 2012).
57
1.3.3.4 Olfactory neurogenesis: extrinsic regulators
The migration of A cells through the RMS is regulated by a series of extracellular signals,
some of which are beginning to be described. During tangential migration, chemorepulsive or
permissive signals including Slit proteins (Wu et al., 1999; Nguyen-Ba-Charvet et al., 2004),
integrin/laminin (Emsley, 2003a) and Erb4 receptor/neuregulin (Anton et al., 2004) interactions
help guide the neuroblasts. Arriving in the OB, chain detachment signals are received through
reelin-mediated mitral cell interactions (Hack et al., 2002) and tenascin-R present in the
extracellular matrix, which also marks the start of radial migration (Saghatelyan et al., 2004).
Several neutrotransmitters modulate SVZ proliferation: GABA (Liu et al., 2005) and
nitric oxide (Packer et al., 2003; Moreno-López et al., 2004) decrease proliferation, serotonin
increases proliferation (Brezun and Daszuta, 1999; Banasr et al., 2004), and dopamine can either
decrease or increase proliferation depending on the manipulation (Baker et al., 2004; Höglinger
et al., 2004; Kippin et al., 2005).
Growth factors also modulate SVZ proliferation in the adult brain, some examples being
BDNF (Zigova et al., 1998), which also modulates survival (Bath et al., 2008), FGF2, epidermal
growth factor (EGF) and heparin binding EGF (HB-EGF) (Kuhn et al., 1997; Doetsch et al.,
2002; Jin et al., 2003), ciliary neurotrophic factor (CNTF) (Emsley, 2003b), and vascular
endothelial growth factor (VEGF) (Jin et al., 2002), which is particularly relevant to the interplay
between vasculogenesis and neurogenesis that takes place in the SVZ (Alvarez-Buylla and Lim,
2004).
SVZ neurogenesis is also regulated by sensory input. Long-term odour enrichment
increases the survival of olfactory interneurons (Rochefort et al., 2002; Bovetti et al., 2009),
whereas sensory deprivation leads to OB atrophy, reducing survival (Corotto et al., 1994;
Petreanu and Alvarez-Buylla, 2002; Mandairon et al., 2003, 2006b) of granule cells particularly
around 14-28 days of age (Yamaguchi and Mori, 2005), which is consistent with the critical
period of survival of OGCs.
Similar to the hippocampus, olfactory learning modulates SVZ neurogenesis. Survival of
olfactory interneurons is increased by olfactory associative learning (water deprived animals
58
learn to lick for water in reponse to a specific odour, or food deprived animals to dig for a food
reward) (Alonso et al., 2006; Mouret et al., 2008; Sultan et al., 2010), but not by mere exposure
to odours (Alonso et al., 2006). A more detailed analysis uncovered a rather complex
relationship between olfactory learning and neuron survival, with learning inducing both survival
of 18-30 day old neurons and death of 38-45 day old neurons, along with spatial redistribution of
adult born neurons (Mandairon et al., 2006a; Mouret et al., 2008).
1.3.3.5 Olfactory neurogenesis: functions
Olfactory interneurons are thought to be critically involved in olfactory discrimination,
mainly through lateral inhibition and the synchronization of network oscillations (see section
1.3.3.1). In the rabbit, granule cells and their inhibitory influence on mitral/tufted cells were
shown to mediate inhibitory responses to similar odorants (Yokoi et al., 1995), and disruption of
oscillatory synchronization in the honeybee impaired the discrimination of molecularly similar
(but not dissimilar) odorants (Stopfer et al., 1997).
In mice, an increase in network oscillation due to developmental knockdown of GABAA
receptor 3 subunit altered the discrimination between individual and mixtures of odours (Nusser
et al., 2012). Similarly, an increase or decrease in mitral cell inhibition levels, through granule
cell ionotropic glutamate receptor manipulation, led to acceleration and deceleration of olfactory
discrimination, respectively (Abraham et al., 2010). Odour enrichment leads to facilitation of
short-term olfactory memory in an odour recognition task, which was correlated to a transient
increase in OB cell number (Rochefort and Lledo, 2005), suggesting a link between olfactory
memory performance and adult generated olfactory interneurons (see also Moreno et al., 2009).
Several strategies have been used to alter adult neurogenesis levels and examine the
impact on olfactory function, including developmental knockdowns, SVZ irradiation,
pharmachological treatment, aging, apoptotic inhibitors and genetic ablation (Lazarini and Lledo,
2011). The results have been quite mixed, with some manipulations impairing olfactory
discrimination (Gheusi et al., 2000; Enwere et al., 2004; Bath et al., 2008; Moreno et al., 2009;
59
Mouret et al., 2009a) and others seeing no effect (Kim et al., 2007; Imayoshi et al., 2008; Breton-
Provencher et al., 2009; Lazarini et al., 2009).
Importantly, olfactory discrimination has been assessed using different tasks, some being
associative and operant (Enwere et al., 2004; Kim et al., 2007; Imayoshi et al., 2008; Breton-
Provencher et al., 2009; Lazarini et al., 2009; Moreno et al., 2009; Mouret et al., 2009a), and
others being non-associative and spontaneous (Gheusi et al., 2000; Bath et al., 2008; Moreno et
al., 2009) (for a full comparison of the studies see table 1).
Most studies do not see impairment in odour detection following reduction of
neurogenesis (Gheusi et al., 2000; Mechawar et al., 2004; Kim et al., 2007; Lazarini et al., 2009),
although one study found that AraC infusion led to a loss of odour detection at lower
concentrations (Breton-Provencher et al., 2009). Similar mixed results have been found with
regard to odour memory, with studies reporting no deficit (Imayoshi et al., 2008; Mouret et al.,
2009a), short-term memory deficits (Gheusi et al., 2000; Mechawar et al., 2004; Breton-
Provencher et al., 2009; Sultan et al., 2010) or long-term memory deficits (Lazarini et al., 2009).
Many factors could contribute to the mosaic of results found in this literature, including
compensation, non-specific effects of the manipulations, the developmental stage of the
manipulation, age of the cells affected, and type of task used. For a detailed discussion of these
factors see section 6.2.2.
Furthermore, odour is an important component in other types of behaviour, such as
detecting danger or social interactions. In fact, ablation of neurogenesis has been found to disrupt
odour fear conditioning (Valley et al., 2009). Interestingly, adult OB neurogenesis is also
involved in several social behaviours (Gheusi et al., 2009), including afilliative and social
behaviours in adolescent mice (30-40 days old) (Wei et al., 2011), female-male interaction
(Feierstein et al., 2010) and female mate preference (Mak et al., 2007), and paternal offspring
recognition (Mak and Weiss, 2010).
60
Table 1. Comparison between olfactory neurogenesis behavioural papers
Study Method
Impact on immature
adult-generated
neurons
Impact on mature adult-
generated neurons
Odor
detection
Habituation
test
Odour memory
Task used for Odour
discrim
Cross-Hab
test
Odour
discrimination
(other)
Gheusi et
al., 2000 NCAM-/- Proliferation: no change OGCL width: 35% reduction No deficit
No deficit but less
exploration in
NCAM-/-
Impaired short-term
(80-100min)
Cross-habituation
Impaired ---
Enwere et
al., 2004
Aging, Lifr+/,
Tgfawa1/wa1
BrdU/Calretinin+ cells
(4 wpi): 59% reduction
in GL in aged mice, 57% Tgfa
BrdU/GABA+ cells (4 wpi):
41% reduction in GL, 55%
reduction in OGCL in aged mice,61% tgfa
---
---
Associative, Operant
(mix of coconut or
almond in water for fine discrimination)
--- Impaired In fine
discrim (not
100:0)
Bath et al.,
2008
BDNF+/-,
TrkB+/-, BDNFMet/Met
Proliferation: no change
BrdU+ cells in OGCL
(4 wpi): 10% reduction in
BDNF+/- and 30% reduction in TrkB+/- and BDNFMet/Met
mice
---
---
Cross-habituation
---
Impaired BDNF+/- ,
BDNF+/Met and
BDNFMet/Met
Imayoshi et
al., 2008
Nestin-
CRE-ERT2× NSE-DTA
--- NeuN+ cells in OGCL: 10%
reduction ---
No deficit (from
discrim task, 1or 7d)
Associative, Operant
(digging)
No deficit No deficit
Lazarini, et
al., 2009
Focal SVZ
irradiation
DCX+ cells in GL and
GCL: 70% reduction --- No deficit
Impaired long-term
(30d) (Operant 2 odour task)
Associative, Operant (go-no go licking) and
cross-habituation
(as in Gheusi et al)
No deficit
No deficit
Breton-Provencher
et al., 2009
SVZ AraC 28d
infusion
DCX+ cells in GCL:
75% reduction
NeuN+ cells in OGCL:
No change Impaired
No deficit long term
(Imayoshi et al)
Impaired short-term (60-120min)
Associative,
Operant
(digging) (as in Imayoshi et al.)
No deficit No deficit
Kim et al., 2007
Bax-KO mouse
No change in prolif,
SVZ, RMS enlargement
with ectopic NeuN+
No effect in OB size No deficit
---
Associative,
Operant
(as in Enwere et al.)
---
No deficit
Sultan et
al., 2010
SVZ AraC
25d infusion
Vast reduction BrdU+
cells in GL and GCL No effect in OB size ---
Impaired 5d
No effect acquisition
(associative learning digging task one
odour)
---
--- ---
Moreno et
al., 2009
SVZ AraC
21d infusion
Decreased proliferation No effect in OB size,
decrease in GAD67 labeling ---
---
Cross-habituation
Impaired
(after enrichment)
Mouret et al., 2009
zVAD
infusion into
OB
Increased survival
of granule cells ---
No deficit on go-no go
Associative, Operant
(go-no go licking)
No deficit
(overall longer explorations in
zVAD);
No deficit
(lag in discrimination
latency)
Mechawar et al., 2004
Nicotinic
AchR 2-/-
mice
No effect in prolif,
migration or
differentiation
Increased survival granule cells, more cells in OGCL
No deficit
Impaired short term
(240m)
---
--- ---
61
Chapter 2 Aims/Hypotheses
This thesis is part of a broad scope of efforts trying to elucidate the physiological
significance of adult neurogenesis, particularly with respect to memory function. Current adult
neurogenesis literature encompasses efforts centered on the cellular and molecular levels, in
understanding and trying to control proliferation, survival and cell fate choices in the adult brain,
and on the system level, through models and behavioural studies trying to determine whether
there is a meaning in having a continuous pool of cells after development. The thesis‘ general
aim is to try and address the issue of adult born neuron contribution to memory function with a
more direct approach, hopefully helping to explain some of the apparent contradictions found in
the literature.
For technical reasons, all manipulations of adult neurogenesis thus far have been done
prior to memory acquisition. Although important correlations have been drawn from this
literature, it has many inconsistencies and raises a concern for compensation in the system
influencing memory acquisition/retrieval. We reasoned that a more direct way to establish if
adult born neurons are involved in representing a memory trace would be to ablate them after
encoding. That way, if these neurons indeed support memory, ablation will lead to a deficit in
retrieval. Thus, we developed a ‗tag and ablate‘ strategy to temporally control the ablation of
adult born neurons, gaining the freedom to independently target different stages of memory
processing.
Our first goal was to compare ablations of adult neurogenesis done before and after
training in hippocampus dependent tasks. Hippocampal lesion literature shows that
posttraining lesions are more disruptive than pretraining ones (Moser and Moser, 1998). Given
that some pretraining ablation studies see a deficit in memory tasks, we hypothesized that: (1)
posttraining ablation of aDGCs would impair retrieval of hippocampus dependent memory, and
(2) posttraining ablations would cause bigger deficits than pretraining ablations. If a deficit is
seen, it will provide the first direct evidence of adult born neurons supporting memory retrieval.
62
Adult neurogenesis in the olfactory system has been implicated in odour memory and
odour discrimination. Since studies pertaining to this literature have also been limited to
pretraining strategies and the findings are quite contradictory, our second goal is to explore the
effect of pre- and posttraining ablation of adult born neurons in an associative odour
discrimination task. To do this we use our tag and ablate strategy in a mouse line with higher
recombination efficiency in the SVZ, in a hippocampus independent task. We hypothesized that
posttraining ablation of adult born olfactory interneurons would impair performance in an
associative memory task, and that these effects would be greater than pretraining ones.
Overall in this thesis we intended to develop a technique to allow the dissection of task
components that might offer insight into questions that have been raised in the field, rendering
some direct answers and hopefully helping understand past results and generate new questions.
63
Chapter 3
General Methods
3.1 Cell culture
In order to verify that murine-derived cells are insensitive to DT, we conducted cell
viability assays using two cell lines, one from mice (3T3 cells) and one from monkey (2-2 cells).
Cells were seeded in 6-well plates (2 × 105 cells per plate). 24 h later DT (0, 0.01, 0.1, or 1
ng/ml) was applied to fresh medium. Supernatant and trypsinized cells were collected 72 h later.
Cell viability was assessed by exclusion of trypan blue (Sigma, IL). Internal duplicates were run
for each condition.
3.2 Mice
Nestin-CreERT2
mice. Nestin-CreERT2
+ mice express TAM-inducible Cre recombinase
under the control of a nestin promoter, and have been previously described (Imayoshi et al.,
2008). The lines of nestin-CreERT2
mice we used in our experiments corresponds to line 4 (for
chapter 4) and 5-1 (chapter 5) in Imayoshi et al. (Imayoshi et al., 2008), and have the highest
recombination efficiency in the subgranular zone of the hippocampus and subventricular zone,
respectively.
iDTR mice. Inducible diphtheria toxin receptor (iDTR) mice have been previously
described (Buch et al., 2005; Gropp et al., 2005). In iDTR+ mice, the gene encoding DTR
(simian Hbegf, heparin-binding epidermal growth factor-like growth factor) is under the control
of the ubiquitous Rosa26 locus promoter, but expression of the DTR transgene is dependent on
the Cre recombinase-mediated removal of a transcriptional STOP cassette. It is important to note
that neither high doses of DT in wild-type mice (Saito et al., 2001) nor expression of DTR alone
(without DT) (Buch et al., 2005) produces behavioral abnormalities or cell death.
64
Rosa-LacZ mice. The Rosa-LacZ reporter mice have been previously described
(Zambrowicz et al., 1997). Similar to iDTR mice, the gene encoding LacZ is under the control of
the ubiquitous Rosa26 locus promoter, and expression of the LacZ transgene is dependent on the
Cre recombinase-mediated removal of a transcriptional STOP cassette. We crossed this reporter
line with nestin-CreERT2
mice to initially characterize TAM-induced recombination because,
unlike LacZ, which is expressed in the nucleus, DTRs are expressed as membrane proteins and
therefore difficult to quantify precisely. Importantly, we observed similar patterns of LacZ and
DTR expression following TAM treatment when crossed with nestin-CreERT2
mice.
All lines were maintained on a C57BL/6 background (Taconic Farms, Germantown, NY).
Genotypes were determined by PCR analysis of tail DNA samples as previously described (Buch
et al., 2005; Imayoshi et al., 2008; Zambrowicz et al., 1997). Nestin-CreERT2+
mice were bred
with iDTR+/-
or iDTR+/+
mice, resulting in nestin-CreERT2+
/iDTR+, nestin-Cre
ERT2+/iDTR
-, nestin-
CreERT2-
/iDTR+, and nestin-Cre
ERT2-/iDTR
- offspring. An equivalent breeding strategy was used
for the LacZ reporter line. Except in the case of wild-type mice, all of the transgenes were kept
as heterozygote in the chromosome of each transgenic mice to avoid possible complications by
over-expressing Cre recombinase (Forni et al., 2006) or loss of the Rosa allele (Zambrowicz et
al., 1997). In most ablation experiments we compared double transgenic mice (2xTg, nestin-
CreERT2+
/iDTR+) to control, single transgenic littermate mice (CTR, nestin-Cre
ERT2+/iDTR
- or
nestin-CreERT2-
/iDTR+). Both CTR and 2xTg mice were treated with TAM and subsequently DT
(see below). Importantly, this design ensures that group effects cannot be attributed to non-
specific effects of TAM or DT. In order to characterize TAM-induced recombination we
compared nestin-CreERT2+
/Rosa-LacZ+ vs. Nestin-Cre
ERT2-/Rosa-LacZ
+ mice.
Mice were bred in our colony at The Hospital for Sick Children, and maintained on a 12
h light/dark cycle with free access to food and water. Prior to all behavioral experiments, mice
were handled for 2 min twice a day for 5 days. Male and female offspring were used in all
experiments. All experiments were performed in the light cycle and conducted in accordance
with the Hospital for Sick Children Animal Care and Use Committee.
65
3.3 Drugs
Tamoxifen (TAM) treatment. TAM (Sigma, IL) was dissolved in minimal ethanol (10%)
and suspended in sunflower seed oil (Lagace et al., 2007). Mice received either one (chapter 5)
or three (chapter 4) rounds of TAM treatment. In each round, mice received daily injections (180
mg/kg; i.p.) for 5 days, and each round was 4 weeks apart. TAM injections started at 4 weeks of
age for the hippocampal experiments (chapter 4), and around 4-5 or 8 weeks for the olfactory
experiments (chapter 5).
Diphtheria toxin (DT) treatment. Preparation and delivery of DT was described
previously (Han et al., 2009). DT (Sigma, IL) was dissolved in phosphate buffered saline (PBS)
and readily crosses the blood-brain barrier (Wrobel et al., 1990). In the majority of hippocampal
(chapter 4) experiments mice received daily injections of DT (16 µg/kg; i.p) for 7 days. In two
experiments (the visual discrimination and remote water maze experiments) mice received
injections for 2 days. We chose 2 days of DT treatment in these experiments because we
observed significant forgetting after a week-long retention delay in preliminary visual
discrimination experiments. For the olfactory experiments (chapter 5) mice received 5 days of
injections.
3.4 Immunohistochemistry
Mice were perfused transcardially with PBS (0.1 M) and 4% paraformaldehyde (PFA).
Brains were removed, fixed overnight in PFA and transferred to 0.1 M PBS. Coronal sections
(40 µm) were cut using a vibratome (Leica VT1200S). The following primary antibodies were
used: rabbit monoclonal anti-calbindin (D28K; 1:600; Cell Signaling Technology, MA), mouse
monoclonal anti-calretinin (1:1500; Swant, Bellinzona, Switzerland), goat polyclonal anti-
doublecortin (1:4500; Santa Cruz Biotechnology, CA), rabbit polyclonal anti-Egr1 (Zif268;
1:10000; Santa Cruz Biotechnology, CA), rabbit polyclonal anti-ERalpha (1:1000; Santa Cruz
Biotechnology, CA), mouse monoclonal anti-glial fibrillary acidic protein (GFAP; 1:120000;
Cell Signaling Technology, MA), rabbit polyclonal anti-Iba1 (1:1200; Wako Chemicals, Wako,
Japan), mouse monoclonal anti-NeuN (1:1000; Millipore, MA), rabbit polyclonal anti-LacZ
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(1:6000; Molecular Probes, OR), mouse monoclonal anti-nestin (1:150; BD Pharmingen, NJ),
rabbit polyclonal anti-Ki67 (1:10000; Abcam, MA) and goat anti-human HB-EGF (DTR; 1:150;
R&D Systems, MN). All sections were treated with 1% hydrogen peroxidase. Sections were then
incubated overnight with the primary antibody and then for 60 min at 20 ºC with HRP-
conjugated or biotinylated secondary antibodies (1:750; Jackson Immuno-research, PA). Signals
were amplified and visualized using Vectastain Elite ABC kit (Vector Laboratories, Burlingame,
CA), tyramide signal amplification, Alexa-Fluor conjugated Streptavidin (Invitrogen, Carlsbad,
CA) or DAB. Sections were mounted on slides with Permafluor anti-fade medium. For Ki67
staining slides were counterstained with methyl green and mounted with Cytoseal 280 mounting
medium (Thermo Fisher Scientific, Waltham, MA).
3.5 Imaging and quantification
All images were acquired using epifluorescent (either a Nikon Eclipse 80i or an Olympus
BX61) or confocal (LSM 710 Zeiss) microscopes. To calculate cell number, cell density, or
proportion of double-positive cells we used 1/5 systematic section sampling fractions covering
the entire anterior-posterior extent of the DG. To calculate the proportion of double-labeled cells,
confocal 1 µm Z-stack images were obtained using ZEN software (Zeiss, Oberkochen, Germany)
with a minimal interval of 15 µm to prevent duplicate counts of the same cell. We quantified
Ki67+ cells throughout the anterior-posterior extent of the DG using a 10× objective on the
Nikon Eclipse 80i epifluorescence microscope. We estimated the total number of LacZ+ cells
following TAM treatment using the optical fractionator method on the Olympus BX61
epifluorescence microscope using a 60×, 1.45 N.A objective and a motorized XYZ stage
attached to a computer with Stereoinvestigator 9.1 (MBF bioscience) (Chen et al., 2004). A
random systematic sampling was used for these stereological analyses (section interval of 1/5,
grid size of 250 × 250 m, 2D counting frame of 90 × 90 m using fractionators of 30 m in
thickness). Tissue thickness measured in each counting frame was used to estimate the total
number of LacZ+ cells in the entire DG. Conditions were optimized to obtain a Gundersen
coefficient of error below 0.05 (Gundersen et al., 1999).We quantified GFAP+ cells and Iba1
+
cells in the DG and CA1 throughout the entire anterior-posterior extent of the hippocampus.
Using StereoInvestigator software and the Olympus BX61 epifluorescence microscope, we
67
created separate contours for the DG and the CA1. All GFAP+ and Iba1
+ cells within the
contours were counted using a 40× objective. Cell density was calculated by the total number of
cells divided by the total area of the contours.
3.7 General behavioral apparatus and procedures
Context fear conditioning. In the fear conditioning experiments, three contexts were used.
Context A (the training context) consisted of a stainless steel conditioning chamber (31 cm × 24
cm × 21 cm; Med Associates, St. Albans, VT), containing a stainless steel shock-grid floor.
Shock grid bars (diameter 3.2 mm) were spaced 7.9 mm apart. The grid floorwas positioned over
a stainless-steel drop-pan, which was lightlycleaned with 70% ethyl alcohol to provide a
background odour.The front, top, and back of the chamber were made of clear acrylicand the two
sides made of modular aluminum. For context B, a white, plastic floor covered the shock grid
bars and a plastic, triangular insert was placed inside the same conditioning chamber used for
context A. One of the walls of this insert had a black/white striped pattern. The other two walls
were white. Context B was cleaned with water. As contexts A and B were located in the same
windowless room and used common apparatus, they shared some overlapping features. In
contrast, context C (37 cm × 16 cm × 27 cm) was located in a different room and contained
features that were largely distinct from contexts A or B. It was made of opaque acrylic walls,
with bedding covering the floor. In contexts A and B, mouse freezing behavior was monitored
via overhead cameras. Freezing was assessed using an automated scoring system (Actimetrics,
Wilmette, IL), which digitized the video signal at 4 Hz and comparedmovement frame by frame
to determine the amount of freezing. Freezing in context C was scored manually.
During training, mice were placed in context A. After 2 min, mice were presented with a
30 s tone (2800 Hz, 85 dB) that co-terminated with a 2 s footshock (0.5 mA). Mice remained in
the context for a further 30 s before being returned to their home cage. Responsivity to the shock
during training was estimated by comparing mouse velocity immediately preceding vs. during
shock presentation using the following formula: (velocityshock – velocitypre-shock)/ (velocityshock +
velocitypre-shock).
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Eight days after training, freezing was assessed in 5 min tests in contexts A and B (~ 4 h
inter-test interval). In context B, the tone was presented after a 2 min delay. Three hours later,
freezing was assessed in a 2 min test in context C. Discrimination of contexts A and B was
computed by comparing freezing in contexts A and B during the first 2 min of testing (i.e.,
before the tone was presented). As in previous studies, we used the following discrimination
index (Corvelo and Eyras, 2008; Wang et al., 2009): (freezingcxt A - freezingcxt B)/max(freezingcxt
A,freezingcxt B). Discrimination scores ranged from -1 to +1, with positive scores reflecting
greater levels of freezing in context A compared to context B. This measure changes at the same
rate regardless of the relative difference in freezing levels in contexts A and B, and therefore is
more sensitive in detecting small differences in relative freezing levels than other commonly
used discrimination indices (e.g., (freezingcxt A - freezingcxt B)/(freezingcxt A + freezingcxt B))
(McHugh et al., 2007) that change slowly when differences are small and more rapidly when
differences are large (Corvelo and Eyras, 2008). Importantly, we found no difference between
statistical analyses based on our discrimination index compared to other commonly used
discrimination indices.
Water maze (hidden platform version). The apparatus and behavioral procedures have
been previously described (Teixeira et al., 2006; Kee et al., 2007). Behavioral testing was
conducted in a circular water maze tank (120 cm in diameter, 50 cm deep), located in a dimly-lit
room. The pool was filled to a depth of 40 cm with water made opaque by adding white, non-
toxic paint. Water temperature was maintained at 28 ± 1 ºC by a heating pad located beneath the
pool. A circular escape platform (10 cm diameter) was submerged 0.5 cm below the water
surface, in a fixed position in one of the quadrants. The pool was surrounded by curtains, at least
1 m from the perimeter of the pool. The curtains were white and had distinct cues painted on
them.
Water maze training took place over 5 days. On each day, mice received 3 training trials
(inter-trial interval was ~15 s). For each trial, mice were released into the pool, facing the wall, at
one of 4 pseudorandomly-varied start locations. The trial was complete once the mouse found
the platform or 60 seconds had elapsed. If the mouse failed to find the platform on a given trial,
the experimenter guided the mouse onto the platform. After the completion of training, spatial
memory was assessed in a 60 s probe test with the platform removed from the pool. Behavioral
data from training and the probe tests were acquired and analyzed using an automated tracking
69
system (Actimetrics, Wilmette, IL). Using this software, we recorded a number of parameters
during training, including escape latency and swim speed. In probe tests, we measured the
amount of time mice searched the target zone (23.6 cm in radius, centered on the location of the
platform during training) vs. the average of three other equivalent zones in other areas of the
pool (Moser et al., 1993). Each zone represents 15% of the total pool surface.
Water maze (visual discrimination version). For the visual discrimination task, we
modified the water maze apparatus described above. The pool contained two visual cues. These
cues were cylindrical (4 cm in diameter, 4 cm in height), with either a vertical or horizontal
black/white striped pattern. One of these cues (counter-balanced across mice) was always
positioned above the submerged escape platform (10 cm in diameter, 0.5 cm below the surface of
the water). A transparent plastic cylindrical bar (1 cm in diameter, 13 cm in height) connected
the cue to the platform. The other, non-reinforced cue was also positioned 13 cm above the
surface of the water. For the non-reinforced cue, an identical transparent plastic cylindrical bar
connected the cue to base of the pool. Non-patterned white curtains replaced the curtains
containing distal cues in order to minimize reliance on spatial strategies.
Visual discrimination training took place over 5 days. Across training trials, the locations
of the reinforced and non-reinforced cues were varied pseudorandomly. On each day mice
received 6 training trials (inter-trial interval was ~10 min). On each trial mice were released into
the pool, facing the wall, at one of 4 pseudorandomly-varied start locations. The trial was
complete once the mouse found the escape platform or 60 s had elapsed. If the mouse failed to
find the platform on a given trial, the experimenter guided the mouse onto the platform. Three
days following the completion of training, discrimination memory was assessed in a 30 s probe
test with both cues present, but with the platform removed from the pool. As before, behavioral
data from training and the probe tests were acquired and analyzed using an automated tracking
system. During the probe test, searching was highly focused around the two cues. Accordingly,
we compared time spent in two zones (15 cm in radius) centered on the cue locations.
Additionally, heat maps representing averaged group data were generated using Matlab
(MathWorks, Natick, MA). In the heat map the average time (s) mice spent in a 6 × 6 cm area of
the pool was normalized for n = 10 mice per group. Behavioral procedures were adapted from
previous studies which established that post-training lesions of the hippocampus disrupt visual
discrimination memory (Sutherland et al., 2001; Epp et al., 2007).
70
Associative olfactory discrimination task. The apparatus and training schedule have been
described previously (Imayoshi et al., 2008). Mildly food deprived (~90% of body weight) mice
are subjected to four days of training in an associative task. Each day animals have two five-
minute training sessions, one with each of the two odours (+ or – carvone). In all trials, odorant
solution is pipetted into a filter paper inside a petri dish containing small perforations on the
cover for odour flow. The odour containing petri dish is covered in bedding. Animals are
exposed to both odours separately each day, one of which is reinforced with six sugar pellets
hidden under the bedding on top of the dish, so that animals learn to dig under the correct odour
to find the sugar. All mice are counterbalanced for reinforced odour and order or odour exposure.
On the probe day a 10 minute test takes place, when mice are placed in a cage with both odours
present but in the absence of sugar. Learning is measured as time spent digging over the correct
odour. All probe tests were recorded and manually coded. A preference index was calculated as
[(diggingreinforced odour - diggingunreinforced odour)/( diggingreinforced odour + diggingunreinforced odour)].
3.8 Specific experimental protocols
Characterization of TAM-induced recombination. Nestin-CreERT2+
/Rosa-LacZ+ or nestin-
CreERT2-
/Rosa-LacZ+ mice were treated with TAM. Seven weeks following the completion of
TAM treatment the number, distribution and cellular phenotype of recombined LacZ+ cells was
quantified using immunohistochemical methods.
Characterization of TAM-induced recombination and ablation in 2xTg mice. 2xTg mice
were treated with TAM. Seven weeks following the completion of TAM treatment, mice
received daily injections of PBS or DT for 7 days. Twenty-four hours after the final DT injection
mice were perfused and DTR, nestin, calretinin and DCX expression were quantified
immunohistochemically.
Characterization of basal proliferation rates in 2xTg mice. To evaluate whether our
tagging impacted ongoing proliferation in the adult hippocampus, we examined expression of
Ki67 in CTR and 2xTg mice 7 weeks following the completion of TAM treatment. Ki67 is a cell
71
cycle related nuclear protein, expressed by proliferating cells in all phases of the active cell cycle
(Kee et al., 2002).
Contextual fear: post-training ablation. CTR and 2xTg mice were treated with TAM.
Seven weeks following the completion of TAM treatment, mice were trained in context A.
Beginning one day later, mice received daily injections of DT for 7 days. One week after
training, freezing was assessed in contexts A and B, and then in context C in a subset of mice.
Contextual fear: pre-training ablation. CTR and 2xTg mice were treated with TAM.
Seven weeks following the completion of TAM treatment, mice were trained in context A. One
week after training, freezing was assessed in contexts A and B, and, later, in context C. In this
experiment, mice received daily injections of DT for 7 days during the week preceding training.
Conditioned taste aversion: post-training ablation. To evaluate whether post-training
DT-induced ablation impairs subsequent expression of a conditioned taste aversion memory we
trained CTR and 2xTg mice 7 weeks following the completion of TAM treatment, using
previously described methods (Ding et al., 2008). During training, mice had access to a single
bottle containing saccharin (0.2%) for 30 minutes. Forty minutes later mice were treated with
LiCl (0.15 M, 2% body weight, i.p.). Beginning the next day, mice received daily injections of
DT for 7 days. One day later, conditioned taste aversion was assessed in a choice test in which
mice had access to bottles containing either water or saccharin. An aversion index was calculated
as: saccharin consumed/total fluid consumed. An additional group of mice were treated
identically except that they received an injection of saline (instead of LiCl) during training.
Water maze, hidden platform version: post-training ablation, recent group. CTR and
2xTg mice were treated with TAM. Seven weeks following the completion of TAM treatment,
mice were trained in the hidden platform version of water maze for 5 days. Beginning one day
following the completion of water maze training, mice received daily injections of DT for 7
days. One day later, spatial memory was assessed in a probe test. Additional groups of CTR and
2xTg mice were treated identically, except that they received PBS rather than DT during the 7
days prior to the probe test.
Water maze, hidden platform version: pre-training ablation. CTR and 2xTg mice were
treated with TAM. Seven weeks following the completion of TAM treatment, mice were trained
72
in the hidden platform version of the water maze for 5 days, and spatial memory was tested in a
probe test one week later. In this experiment, mice received daily injections of DT for 7 days
during the week preceding training.
Water maze, hidden platform version: post-training ablation, remote group. CTR and
2xTg mice were treated with TAM. Seven weeks following the completion of TAM treatment,
mice were trained in the hidden platform version of water maze for 5 days. Mice were treated
identically to above except that 35 d following the completion of water maze training, mice
received daily injections of DT for 2 days. One day later, spatial memory was assessed in a probe
test.
Water maze visual discrimination version: post-training lesion. One day after training in
the visual discrimination task, wild-type mice received sham lesions or NMDA lesions of the
entire hippocampus as previously described (Wang et al., 2009). Two days later, discrimination
was assessed in a probe test. Mice were perfused after the probe test. Brains were removed, fixed
overnight in PFA, and transferred to 30% sucrose. Coronal sections (50 µm) were cut using a
cryostat. Sections were mounted on gelatin-coated slides, stained with neutral red, and cover-
slipped with Cytoseal. Using Stereo Investigator software, the entire hippocampus and the area
of the hippocampus sustaining damage were outlined separately for every fourth section. The
proportion of total hippocampal tissue damaged was 66.2 ± 7.3%.
Water maze visual discrimination version: post-training ablation. CTR and 2xTg mice
were treated with TAM. Seven weeks following the completion of TAM treatment, mice were
trained in the visual discrimination task. Beginning one day following the completion of training,
mice received daily injections of DT for 2 days. One day later, discrimination was assessed in a
probe test.
General behavioral characterization following DT-induced ablation.CTR and 2xTg mice
were treated with TAM. Seven weeks following the completion of TAM treatment, mice
received daily DT injections for 7 days and behavior was evaluated in a battery of tests. All mice
were given the following tests in the same order (open field, visual discrimination, beam
walking, hanging grip, sticky dot/adhesive removal, forced swim).
73
For open field testing, mice were placed in the center of a square-shaped arena (45 cm ×
45 cm × 20 cm height) and allowed to explore for 20 min. The open field apparatus was
constructed of Plexiglas, and was dimly-lit from above. Mouse location was tracked by a camera
located above the open field, and total distance traveled as well as time spent in 3 different zones
(outer, middle, inner) was measured (Limelight2, Actimetrics, Wilmette, IL). Total distance
traveled was used as a measure of spontaneous motor activity and distribution of activity in
different regions of the arena was used as a measure of anxiety-related behavior(Archer, 1973).
To evaluate vision we trained mice in the visual discrimination water maze task across
three consecutive days (6 trials/day). The latency to reach the platform and swim speed were
recorded.
To assess sensorimotor control and locomotor activity we used the beam walking task
(Chen et al., 2004). Mice were placed on a beam (70 cm long, 2 cm wide, elevated 30 cm above
floor) for 60 s, and paw slips (forelimb and hindlimb) were recorded. Each mouse received three
consecutive trials, and paw slips were calculated per distance traveled.
To evaluate muscle strength the hanging grip test was used (Chen et al., 2004). In this
test, mice were allowed to hang vertically from a metal wire using their forepaws. The latency to
fall was measured. Importantly, mouse weights did not differ between genotypes.
To assess somatosensory function we used the sticky dot or adhesive removal task
(Schallert et al., 2000). Briefly, a small piece of tape was placed on the plantar surface of the
mouse‘s forepaw. Time taken for mice to sense (i.e., shaking its paw or bringing its paw to its
mouth) and remove the adhesive tape were recorded. Each mouse was tested 3 times, and data
averaged. Each test lasted a maximum of 3 min.
To assess depressive-like behaviors we used the forced swim test (Porsolt, 1979). Mice
were placed in a cylinder (radius, 6.5 cm, height 20 cm) for 6 min. The cylinder was filled to a
depth of 12 cm with 25±1 ºC water. The time spent motionless was recorded for each mouse.
Associative olfactory discrimination: post-training ablation of 3 week old cells. CTR and
2xTg mice were treated with TAM. Three weeks following the start of TAM treatment, mice
were trained in the associative olfactory discrimination task for four days. 24h after mice were
74
probed to confirm they had learned the association (pre-DT). 24h later animals started five days
of DT treatment. 24h later animals were subjected to another probe trial (post-DT). A variation
of this experiment consisted of the same design except mice were injected with TAM at 8 weeks
of age (and not 4-5 weeks as with the rest of the olfactory experiments).
Associative olfactory discrimination: pre-training ablation of 3 week old cells and long-
term memory test. CTR and 2xTg mice were treated with TAM. Three weeks following the start
of TAM treatment, mice were trained in the associative olfactory discrimination task for four
days. 24h after mice were probed to confirm they had learned the association. In this experiment,
mice received daily injections of DT for 5 days immediately preceding training. Animals also
received a long-term probe test 28d after the first probe to assess long-term memory.
Associative olfactory discrimination: post-training ablation of 8 week old cells. CTR and
2xTg mice were treated with TAM. Eight weeks following the start of TAM treatment, mice
were trained in the associative olfactory discrimination task for four days. 24h after mice were
probed to confirm they had learned the association (pre-DT). 24h later animals started five days
of DT treatment. 24h later animals were subjected to another probe trial (post-DT).
3.9 Data analysis
Data were analyzed using ANOVAs followed by t-tests. Because both male and female
mice were used, sex was initially included as a factor in the ANOVAs. Consistent with previous
studies (Jonasson, 2005), we found that males performed better than females in one of the water
maze experiments (hidden platform version, post-training ablation, recent group). However, we
found no further effects of sex, and no significant interactions between sex and genotype,
therefore this factor was dropped from analysis.
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Chapter 4
Posttraining Ablation of Adult Generated Neurons Degrades
Previously Acquired Memories
4.1 Abstract
New neurons are continuously generated in the subgranular zone of the adult
hippocampus, and, once sufficiently mature, are thought to integrate into hippocampal memory
circuits. However, whether they play an essential role in subsequent memory expression is not
known. Previous studies have shown that suppression of adult neurogenesis often (but not
always) impairs subsequent hippocampus-dependent learning (i.e., produces anterograde effects).
A major challenge for these studies is that these new neurons represent only a small
subpopulation of all dentate granule cells and so there is large potential for either partial or
complete compensation by granule cells generated earlier on during development. A potentially
more powerful approach to investigate this question would be to ablate adult-generated neurons
after they have already become part of a memory trace (i.e., retrograde effects). Here we
developed a diphtheria toxin-based strategy in mice that allowed us to selectively ablate a
population of predominantly mature, adult-generated neurons either before or after learning,
without affecting ongoing neurogenesis. Removal of these neurons before learning did not
prevent the formation of new contextual fear or water maze memories. In contrast, removal of an
equivalent population after learningdegraded existing contextual fear and water maze memories,
without affecting non-hippocampal memory. Ablation of these adult-generated neurons even one
month after learning produced equivalent memory degradation in the water maze. These
retrograde effects suggest that adult-generated neurons form a critical and enduring component
of hippocampal memory traces.
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4.2 Introduction
Division of progenitor cells in the subgranular zone leads to the continuous addition of
new neurons to the adult hippocampus, a brain region that plays a central role in memory
formation (Deng et al., 2010). These newly-generated neurons initially migrate into the granule
cell layer of the dentate gyrus (DG) and, over the course of several weeks, gradually establish
functional afferent and efferent connections (Toni et al., 2008; Toni et al., 2007; Zhao et al.,
2006). Previous studies have shown that,once sufficiently mature, adult-generated neurons are
activated duringmemory formation and/or expression (Kee et al., 2007; Stone et al., 2011b;
Tashiro et al., 2007; Trouche et al., 2009), suggesting that they become integrated into
hippocampal memory traces. However, these correlative studies do not establish whether these
neurons represent an essential component of a hippocampal memory. A direct way to test this
would be to examine the impact of removingonly this population of neurons after memory
formationon subsequent expression of that memory. While transgenic, pharmacological and
irradiation-based approaches have previously been used to manipulate adult neurogenesis prior
to memory formation (Clelland et al., 2009; Deng et al., 2009; Dupret et al., 2008; Garthe et al.,
2009; Imayoshi et al., 2008; Kitamura et al., 2009; Saxe et al., 2006; Shors et al., 2001; Zhang et
al., 2008), it has been technically challenging to manipulate adult-generated neurons after
learning.
To address this question we developed a ‗tag and ablate‘ transgenic strategy which
allowed us to tag adult-generated neurons, allow them to mature, and ablate them either before or
after training (Fig. 9A). To ablate neurons, we used a diphtheria toxin (DT)-based system (Buch
et al., 2005; Han et al., 2009). Apoptotic cell death is reliably induced after DT binds to the DT
receptor (DTR). Since mice do not express functional DTRs,and are therefore normally
insensitive to DT (Middlebrook et al., 1977), we used transgenic mice that express simian DTRs
in a Crerecombinase inducible manner (iDTR mice) (Buch et al., 2005). To restrict DT-induced
apoptosis to adult-generated neurons we crossed iDTRmice with nestin-CreERT2
mice, in which a
tamoxifen (TAM)-inducible Crerecombinase is expressed under the control of a nestin promoter
(Imayoshi et al., 2008). In adult offspring from this cross, TAM administration induces
77
permanent expression of DTRs in neural progenitor cells and their progeny, and subsequent
administration of DT ablates only this tagged population of adult-generated neurons. We found
that selective ablation of these tagged, adult-generated neurons immediately (or up to one month)
after training impaired memory expression using three distinct hippocampus-dependent tasks.
Therefore, our data indicate that adult-generated neurons—if available at the time of learning—
come to form an essential and enduring component of hippocampal memory traces.
4.3 Results
4.3.1 Murine cells are insensitive to DT
We verified that murine cells are insensitive to DT using two cell lines, one derived from
mice (3T3 cells) and the other from monkey (2-2 cells). As expected, DT dose-dependently
reduced the number and viability of 2-2, but not 3T3, cells (Fig. 9B-C) (Middlebrook et al.,
1977).
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Figure 9.DT-based ablation. A. Schematic of the ‗tag and ablate‘ strategy for ablating mature, adult-generated
neurons. In adult nestin-CreERT2+
/iDTR+ mice (2xTg), TAM administration leads to permanent expression of DTRs
in neural progenitor cells and their progeny. Subsequent administration of DT ablates this tagged population of
adult-generated neurons only. B-C. In vitro assay demonstrating insensitivity of wild-type mouse cell lines to
DT.Whereas mouse-derived 3T3 cells were insensitive to increasing concentrations of DT (n = 2)(b), DT dose-
dependently reduced the number and viability of monkey-derived 2-2 cells (n = 3)(c).
4.3.2 Characterization of ‘tag and ablate’ mice
Tagging new neurons.We first characterized TAM-induced recombination
(―tagging‖) in nestin-CreERT2
mice by crossing them with rosa-LacZ reporter mice. In these
reporter mice, Cre-mediated excision of a STOP cassette induces LacZ expression under the
control of the Rosa26 promoter (the same promoter as in the iDTR mice). Consistent with
previous results, at 4 weeks of age, CreERT2
protein expression innestin-CreERT2+
mice was
robust, restricted to progenitor cells (Fig. 10a and Table 2), and limited to adult neurogenic
regions including the subgranular zone (Fig. 10b-g) (Imayoshi et al., 2008). As expected, TAM
induced recombination (―tagging‖ cells, LacZ+) in nestin-Cre
ERT2+/Rosa-LacZ
+reporter mice and
no recombination was observed in nestin-CreERT2-
/Rosa-LacZ+littermate controls (Fig.11a). We
next examined tagged cells 7 weeks after TAM administration was complete. As previously
observed (Imayoshi et al., 2008), TAM-induced recombination in the dividing progenitor
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population was highly efficient, with 86.2 ± 2.7% (mean ± s.e.m.) of Ki67+ cells and 77.7 ±7.8%
of nestin+ cells in the DG expressing LacZ. Furthermore, LacZ
+ cells were uniformly distributed
throughout the anterior-posterior extent of the DG (Fig.11b), suggesting no intra-regional
differences in TAM-induced recombination efficiency.Using stereological methods, we
estimated there were 31,709 ± 2,984 LacZ+ cells and 496,266 ± 46,556 NeuN
+ cells in the DG.
Therefore, our tagged population of cells represents approximately 6% of the entire population of
DG neurons (i.e., 31,709/496,266).
To evaluate the phenotype of tagged cells, we next stained for proteins expressed at
different stages of cell differentiation(Kempermann et al., 2004) (Fig. 11c). Ninety-four percent
of tagged (LacZ+) cells were also positive for markers of mature neurons (NeuN, calbindin) with
far fewer (<5%) that were positive for progenitor cell or immature neuronal markers (nestin,
doublecortin, calretinin) (Fig.11d and Table 3). Therefore, this predominantly mature population
of tagged neurons corresponds to the population of adult-generated neurons that are activated
during the formation and/or expression of hippocampus-dependent memories (Kee et al., 2007;
Stone et al., 2011b). Consistent with this, at this time point LacZ+ cells expressed activity-
dependent genes such as zif268 following training (Fig.11d). Importantly, basal levels of
proliferation in the hippocampus were unaltered by tagging [unpaired t-test: P> 0.05] (Fig.11e).
80
Figure 10. CreERT2
expression is restricted to progenitor cells and limited to adult neurogenic regions.(a) In nestin-
CreERT2+
mice, CreERT2
protein expression (green) was found in nestin+ and DCX
+ cells (red) but not mature neurons
(NeuN; red) in the DG (scale = 10 µm). (b-g) In these mice, CreERT2
protein expression was limited to the
subgranular zoneof the dentate gyrus (DG) and the subventricular zone of the lateral ventricle (LV) (mm relative to
bregma; scale = 250 µm). Mo = molecular layer, GCL = dentate granule cell layer, CPu = caudate putamen, Pir =
piriform cortex, Thl = thalamus, OB = olfactory bulb, Gr = granular layer, Gl = glomerular layer.
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Figure 11.Tagging new neurons. (a)TAM-induced recombination occurs only in nestin-CreERT2+
mice (scale = 50
µm). (b) Recombination occurred throughout the anterior-posterior extent of the DG (mm relative to bregma; scale
= 150 µm). (c)Schematic showing markers associated with different developmental stages of adult hippocampal
neurogenesis. (d) Seven weeks after the completion of TAM treatment, most LacZ+ cells (green) co-stained for
mature neuronal markers (NeuN, calbindin; red), with far less staining for progenitor cell orimmature neuronal
markers (nestin, DCX, calretinin; red). LacZ+ cells additionally expressed activity-dependent gene zif268 (red) after
behavioral testing. (e) Seven weeks after the completion of TAM treatment, Ki67 expression levels were similar in
control (CTR; n = 11) and 2xTg (n = 7) mice, indicating that DTR expression has no effect on ongoing proliferative
activity in the adult hippocampus (scale = 250 µm). Mo = molecular layer, GCL = dentate granule cell layer.
Ablating tagged neurons. In order to ablate these tagged neurons we crossed nestin-
CreERT2
micewith iDTR mice, in which Cre-mediated excision of a STOP cassette renders cells
sensitive to DT (Buch et al., 2005). In TAM-treated nestin-CreERT2+
/iDTR+ (2xTg) mice, DTR-
expressing cells were localized to the subgranular zone and inner-most layer of the DG
(consistent with the pattern of LacZ expression in the reporter mice above) (Fig.12a). Subsequent
systemic injection of DT (but not PBS) virtually abolished these DTR-expressing cells [100%
reduction, unpaired t-test: t8 = 1.93, P< 0.05] (Fig.12a), indicating that DT treatment efficiently
ablated the tagged neurons (Buch et al., 2005; Han et al., 2009). In the same mice, we
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additionally quantified numbers ofprogenitor cells and immature neurons in the DG following
DT vs. PBS treatment. We found that DT treatment greatly reduced overall numbers of
doublecortin+
(Fig. 12b), nestin+[~94% reduction, unpaired t-test: t7 = 4.16, P< 0.01](Fig.12c),
calretinin+[~86% reduction, unpaired t-test: t6 = 2.03, P<0.05] (Fig.12d) cells in the DG of 2xTg
mice. While this subpopulation represents only a small proportion of all tagged cells (~94% are
NeuN+ or calbindin
+), nonetheless these data are consistent with the reduction in DTR-
expressing cells and suggests that DT-induced ablation is highly efficient.
Figure 12. Ablating tagged neurons. (a) DT (n = 4) but not PBS (n = 6) efficiently ablated DTR-expressing cells in
the DG (scale = 10 µm).Consistent with this, DT treatment reduced overall numbers of (b) doublecortin+
(DCX;
scale = 150 µm), (c) nestin+
(scale = 10 µm), and (d) calretinin+
(scale = 10 µm) cells in the DG of 2xTg mice. Mo =
molecular layer, GCL = dentate granule cell layer. * denotes P< .05.
Following DT treatment, there were similar numbers of astrocytes [unpaired t-tests: Ps
>0.05] but increased microglia in the hippocampus (Fig.13a-c). The increase in microglia was
limited to the DG [unpaired t-test: t7 = 3.46, P< 0.01], and not observed in CA1 [unpaired t-test:
P> 0.05], and therefore likely reflects localized phagocytosis following DT-induced apoptotic
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cell death. Furthermore, TAM and DT treatment produced no changes in mouse weight
[unpaired t-tests: Ps >0.05] (Fig. 14a), or in a range of tests assessing emotion, vision, motor or
somatosensory function [ANOVAs and unpaired t-tests: Genotype effects, Ps >0.05] (Fig.14b-j).
In subsequent behavioral experiments, 2xTg and littermate control mice (either nestin-CreERT2+
or iDTR+ but not both) were used. All mice were treated with TAM and subsequently treated
with DT either before or after training. Importantly, this design ensures that group effects cannot
be attributed to non-specific effects of TAM or DT.
Figure 13.DT-induced ablation produces minimal inflammation. (a) Glial fibrillary acidic protein (GFAP; red) and
ionized calcium binding adaptor molecule 1 (Iba1; green) expression in CTR (n = 5) and 2xTg (n = 4) mice 24 h
after administration of DT. (b) GFAP levels were similar for CTR and 2xTg mice in both the DG and CA1 regions.
(c) Iba1 expression was increased in 2xTg mice only in the DG and not in the CA1 region. Note that Iba1 expression
was mainly limited to the subgranular zone and innermost layer of the DG, a pattern that matches the distribution of
tagged (i.e., DTR+ or LacZ
+) cells after TAM treatment. * denotes P< .05.
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Figure 14. General health and behavior are not altered by DT-induced ablation. Seven weeks after the completion of
TAM treatment, CTR (n = 6) and 2xTg (n =7)mice were treated with DT. (a) Body weights were not different after
the completion of TAM or DT treatments. (b-j)The behavior of TAM- and DT-treated CTR and 2xTg mice was
characterized in a battery of tests. We observed no effect on (b) time spent immobile in the forced swim test, (c)
total exploration in the open field, (d) time spent in the outer, middle and innermost regions of the open field, (e)
latency to find platform in the visual discrimination water maze, (f) swim speed during training in the visual
discrimination water maze, (g) paw slips in the beam walk test, (h) latency to fall in the bar hanging test, (i) latency
to detect adhesive tape in the sticky dot test, or (j) latency to remove adhesive tape in the sticky dot test.
4.3.3 Post-training ablation of tagged neurons degrades a contextual fear
memory
We used our tag and ablate strategy to test whether deletion of adult-generated neurons
after training would impair subsequent memory expression. To test memory,we first used a
contextual fear conditioning task in which mice learn an association between a context and an
aversive event (i.e., the delivery of a mild footshock). When returned to the same context,
contextual fear memory is inferred from an increase in freezing behavior (Kim and Fanselow,
1992). The specificity of the memory may then be evaluated by comparing freezing levels in the
trained versus alternate contexts (Wang et al., 2009). This task is hippocampus-dependent (Kim
and Fanselow, 1992) and engages dentate granule cells (including those generated during
adulthood) (Stone et al., 2011b). We trained 2xTg and control mice with a tone-shock pairing 7
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weeks following TAM treatment (Fig.15a), a time-point when the vast majority of tagged, adult-
generated neurons have matured (i.e., ~94% express the mature neuronal marker calbindin,
indicating that they are ~4 weeks of age or older (Zhao et al., 2008)). During training, both 2xTg
and control mice responded similarly to the shock [unpaired t-test: P> 0.05] (Fig.15b) and
exhibited equivalent levels of freezing immediately before and after the footshock [Genotype×
Training phase ANOVA, effect of Training phase only, F1,20 = 31.85, P< 0.001; planned
comparison for after-shock freezing indicated CTR vs. 2xTg, P> 0.05] (Fig.15c), indicating that
tagging neurons (DTR expression) alone does not alter responsivity to shock or general activity
levels. Following DT treatment, control mice exhibited robust freezing in the trained context
(context A) and less freezing in an alternate context (context B) that shared a number of
overlapping features with the training context. In contrast, 2xTg exhibited robust but equivalent
levels of freezing in both [Genotype×Context ANOVA, Genotype×Context interaction, F1,21=
17.66, P< 0.005; Newman-Keuls post-hoc tests indicatedACTR>BCTRonly, P< 0.05] (Fig. 15d),
indicating that this post-training ablation abolished the ability to discriminate two similar
contexts [unpaired t-test,t21 = 4.27, P< 0.001] (Fig.15e). To test whether this post-training
ablation abolished the ability to discriminate dissimilar contexts, we next placed mice in a third
context (context C), which had no overlapping features with the original training context. In
context C, both 2xTg and control mice exhibited similarly low levels of freezing [unpaired t-test:
P>0.05] (Fig.15f). Therefore, these results indicate that post-training ablation of adult-generated
neurons led to the degradation (but not the erasure) of a contextual fear memory: While
recognition of the training context was unaffected, the ability to discriminate between similar
(but not dissimilar) contexts was impaired.
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Figure 15. Post-training ablation of adult-generated neurons degrades contextual fear memory. (a) Mice were
treated with TAM and then trained in context A. Following DT-induced ablation of adult-generated neurons,
contextual memory was assessed in contexts A, B and C. During training, CTR (n = 12) and 2xTg (n = 11) mice
exhibited similar (b) response to shock and (c) freezing levels before and after shock delivery. (d)Following DT
treatment, CTR mice froze more in the trained context (A) vs. a similar context (B). In contrast, 2xTg mice froze
equally in both. (e) The DT-induced ablation abolished context discrimination. (f) Freezing in a dissimilar context
(C) and (g) tone fear were similar in CTR and 2xTg mice. (h) Mice were treated with TAM and then trained in a
conditioned taste aversion (CTA) task. During training, saccharin was paired with 0.15 M LiCl. Following DT-
induced ablation of adult-generated neurons, preference for saccharin vs. water was evaluated. CTR/LiCl (n = 12)
and 2xTg/LiCl (n = 11) mice exhibited equivalent preference forsaccharin. Importantly, this preference was lower
compared to mice (n = 11) for which saccharin was paired with saline (rather than LiCl) during training (CTR/Sal).
* denotes P< .05.
The present experimental design rules out several alternative interpretations of the data.
First, the absence of freezing in context C indicates that the discrimination deficit in2xTg mice
was not due to an overall increase in propensity to freeze. Second, because DT was administered
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in the home cage, memory degradation effects cannot be due to blockade of a reactivation-
induced phenomenon, such as reconsolidation (Nader et al., 2000). Third, memory for the tone-
shock association was unaltered following the post-training ablation [unpaired t-test: P>0.05]
(Fig.15g). As this type of memory is supported by the amygdala (Han et al., 2009), this suggests
that deleting adult-generated neurons affects hippocampus-dependent memory only. Consistent
with this, in a separate group of mice similar post-training ablation did not affect expression of a
previously-acquired conditioned taste aversion memory [Group ANOVA, Group effect, F4,23 =
5.53, P< 0.01; Newman-Keuls post-hoc tests indicated stronger saccharin preference in the
CTR/SAL group compared tothe CTR/LiCL and 2xTg/LiCl, groups, Ps < .05] (Fig.15h).
4.3.4 Pre-training ablation of tagged neurons does not prevent formation of
new contextual fear memory
We next tested whether ablation of a similar population of adult-generated neurons
immediately before training would impair acquisition of a new contextual fear memory. As in
the previous experiment, 2xTg and control mice were treated with TAM, trained 7 weeks later,
and tested after a one week delay. In this case, however, DT was administered during the week
prior to training rather than during the week following training (Fig.16a). This experimental
design ensures that DT targets an equivalent population of neurons (in terms of number and
maturity), and that the retention delay is identical to the first experiment. During training,
both2xTg and control mice responded similarly to the shock [unpaired t-test: P>0.05] (Fig.16b),
and exhibited equivalent levels of freezing immediately before and after shock delivery
[Genotype ×Training phaseANOVA, effect of Training phase only,F1,25 = 40.95, P< 0.0001;
planned comparison for after-shock freezing indicated CTR vs. 2xTg, P> 0.05] (Fig.16c),
indicating that the pre-training DT-induced ablation did not affect shock reactivity or general
activity levels. One week following training, both 2xTg and control mice froze more in context
A compared to context B [Genotype × Context ANOVA, effect of Context only, F1,25 = 9.41, P<
0.005; planned comparisons indicated ACTR>BCTR and A2xTg>B2xTg, Ps< 0.05] (Fig.16d), and,
furthermore, the degree of discrimination did not differ between groups [unpaired t-test: P>0.05]
(Fig.16e). As expected, both 2xTg and control mice exhibited similarly low levels of freezing in
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context C [unpaired t-test: P>0.05] (Fig.16f), and tone freezing was also unaffected by pre-
training ablation [unpaired t-test: P>0.05] (Fig.16g).
In the first experiment, ablation of a population of predominantly mature, adult-generated
neurons immediately after training impaired subsequent memory expression, presumably
because these neurons had become an integral component of the memory trace. In contrast,
deletion of an equivalent population of neurons immediately before training did not prevent the
formation of a new contextual fear memory, indicating that memory formation may be supported
by existing dentate granule cells when this population ofadult-generated neurons isabsent at the
time of training. Moreover, the preserved ability to discriminate between both similar and
dissimilar contexts suggests that pre-training removal of adult-generated neurons did not
significantly impact memory quality.
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Figure 16. Pre-training ablation of adult-generated neurons does not prevent the formation of a new contextual fear
memory. (a) Mice were trained in context A following DT-induced ablation of adult-generated neurons. Contextual
memory was assessed in contexts A, B and C one week later. During training, CTR (n = 13) and 2xTg (n = 14) mice
exhibited similar (b) response to shock and (c) freezing levels before and after shock delivery. (d) Following DT
treatment, both CTR and 2xTg mice discriminated between contexts A and B, and (e) the degree of discrimination
did not differ. (f) Freezing in a dissimilar context and (g) tone fear were equivalent in CTR and 2xTg mice. *denotes
P< .05.
4.3.5 Post-training ablation of tagged neurons degrades spatial memory
The hippocampus is engaged by multiple forms of learning. To evaluate the
generality of our findings, we next asked whether similar post-training ablations would impact
spatial memory. To address this, we used the hidden platform version of the water maze task, in
which both acquisition and expression depend on the hippocampus (Riedel et al., 1999; Teixeira
et al., 2006). As before, we trained 2xTg and control mice in the water maze 7 weeks following
TAM treatment (Fig.17a). During training, latency to find the platform declined similarly in both
groups [Genotype × Training day ANOVA, effect of Training day only, F4,22 = 19.21, P<
0.0001], indicating that tagging (DTR expression) does not interfere with swimming, motivation
and vision required for acquisition of a spatial memory (Fig.17b). Following the completion of
training, 2xTg and control mice were administered DT and their spatial memory assessed in a
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probe test 7 days later. In this test, 2xTg mice searched less selectively than control mice,
spending less time in the target zone [Genotype × Zone ANOVA, Genotype × Zone interaction
F1,22 = 5.67, P< 0.05; planned comparisons indicated TCTR > T2xTg, TCTR > OCTR, and T2xTg >
O2xTg, Ps < 0.05] (Fig. 17c). We additionally conducted a similar experiment in which TAM-
treated 2xTg and control mice were trained in the water maze but were administered PBS rather
than DT prior to the probe test (Fig.17d). During training, latency to find the platform declined
similarly in both groups [Training day × Genotype ANOVA, effect of Training day only, F4,23 =
22.93, P< 0.0001] (Fig.17e), and in the probe test both 2xTg and control mice exhibited robust
spatial memory [Genotype × Zone ANOVA, effect of Zone only, F1,22 = 38.50, P< 0.0001;
planned comparisons indicated TCTR > OCTRand T2xTg > O2xTg, Ps < 0.05, TCTR vs. T2xTg, P> 0.05]
(Fig.17f). Together, these findings indicate that neither DTR tagging (in the absence of DT) nor
DT administration alone (in the absence of DTR tagging) impairs memory. Instead a
combination of DTR tagging and DT is necessary to induce memory loss.
Consistent with our fear conditioning data, these results indicate that selective
removal of adult-generated neurons following training impairs subsequent memory expression.
In contrast, DT-induced ablation of an equivalent population of adult-generated neurons
immediately before training had no effect on the formation of a new spatial memory (Fig.17g).
Following DT treatment, both 2xTg and CTR mice learned to find the platform with
progressively shorter latencies [Genotype × Training day ANOVA, effect of Training day only,
F4,23 = 9.48, P < 0.01] (Fig.17h). Likewise, in the probe test one week later, both 2xTg and CTR
mice searched selectively, spending equivalent amounts of time in the target zone [Genotype ×
Zone ANOVA, effect of Zone only, F1,23 = 8.14, P< 0.01; planned comparisons indicated TCTR >
OCTR, T2xTg > O2xTg, Ps < 0.05, TCTR vs. T2xTg, P > 0.05] (Fig.17i). This suggests that new spatial
learning may be supported by existing dentate granule cells when adult-generated neurons are
not present at the time of training. Importantly, this pre-training ablation did not affect
swimming, navigation, vision, or motivation required for acquisition and expression of spatial
memory. Therefore, as pre- and post-training ablations targeted equivalent populations of adult-
generated neurons, these results exclude the possibility that such performance factors could
account for spatial memory loss following post-training ablations.
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Figure 17. Post-training (but not pre-training) ablation of adult-generated neurons impairs spatial memory
expression. (a) Mice were treated with TAM and then trained in the water maze. Following DT-induced ablation of
adult-generated neurons, spatial memory was assessed in a probe test. (b) During training, latency to find platform
declined equivalently in CTR (n = 12) and 2xTg (n = 12) mice. (c) Following DT-induced ablation, 2xTg mice
searched less selectively compared to CTR mice, spending less time in the target zone (T). (d) Additional groups of
TAM-treated mice were trained in the water maze. However, mice were treated with PBS (rather than DT) during
the week preceding memory testing. (e) During training, latency to find platform declined equivalently in CTR (n =
11) and 2xTg (n = 14) mice. (f) In the probe test, both CTR and 2xTg mice searched selectively, spending more time
in the target zone compared to other (O) non-target zones in the pool. (g) Mice were trained in the hidden version of
the water maze after the completion of TAM treatment. During the week before training mice were treated with DT.
(h) During training, latency to find the platform declined equivalently in CTR (n = 14) and 2xTg mice (n = 11). (i)
In the probe test, both CTR and 2xTg mice searched selectively at the target zone. (j) Mice were treated with TAM
then trained in the water maze. One month later mice were treated with DT, and then spatial memory was assessed
in a probe test. (k) During training, latency to find platform declined equivalently in CTR (n = 14) and 2xTg (n =
12) mice. (l) Following DT-induced ablation at the remote time point, 2xTg searched less selectively compared to
CTR mice, spending less time in the target zone.* denotes P< .05.
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4.3.6 Post-training ablation of tagged neurons degrades remote spatial
memory
Expression of water maze memory depends on the hippocampus for at least one
month after training (Clark et al., 2005; Teixeira et al., 2006). To address whether adult-
generated neurons play a persistent role in memory expression, we next treated additional groups
of control and 2xTg mice with DT one month (rather than one day) after training (Fig.17j). As
before, both groups learned to locate the platform during training [Genotype × Training day
ANOVA, effect of Training day only, F4,24 = 26.83, P< 0.0001] (Fig.17k) and control mice
exhibited robust spatial memory even when tested more than onemonth later. In contrast, at this
remote time point, 2xTg mice searched less selectively compared to control mice, spending less
time in the target zone [Genotype × Zone ANOVA, Genotype × Zone interaction, F1,24 = 3.53, P
= 0.07; planned comparisons indicated that TCTR > T2xTg, TCTR > OCTR,and T2xTg > O2xTg, Ps <
0.05] (Fig.17l). These findings indicate that adult-generated neurons play an integral and
enduring role in the expression of a spatial memory.
4.3.7 Post-training ablation degrades visual discrimination memory
Post-training ablation of adult-generated neurons impaired the ability to discriminate
between two similar contexts in the fear conditioning experiment. To further explore the nature
of this deficit, we next developed a water maze visual discrimination task. In this task, two
similar cues (one vertically-striped, the other horizontally-striped) were positioned above the
surface of the water. Across training trials, the locations of these two cues varied
pseudorandomly. However, one of the cues was always located above a hidden platform (e.g.,
horizontal stripes). In order to evaluate whether this form of visual discrimination memory
depends on the hippocampus, we first examined the impact of post-training cytotoxic
hippocampal lesions (Fig.18a). During training, both groups of mice learned to discriminate
between the reinforced and non-reinforced cues [Lesion × Training day ANOVA, effect of
Training day only, F4,68 = 52.69, P< 0.0001] (Fig.18b). Mice received lesion or sham surgery one
day following training and then discrimination memory was subsequently assessed in a probe
test in which both cues were present, but neither reinforced. In this probe test, control mice spent
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significantly more time searching close to the previously reinforced cue than the non-reinforced
cue[planned paired t-test, t8 = 4.27, P< 0.05]. In contrast, mice with cytotoxic hippocampal
lesions spent similarly little time close to either cue[planned paired t-test, P> 0.05] (Fig.10c).
Our lesions affected ~66±7% of hippocampal tissue (Fig.18d). Similar hippocampal lesions in
rats produce equivalent deficits (Clark et al., 2007), and indicate that an intact hippocampus is
necessary for the expression of this form of visual discrimination memory.
We next evaluated whether post-training ablation of adult-generated neurons would
similarly impairthe expression of a visual discrimination memory (Fig.10e). During training,
2xTg and control mice learned to discriminate between the reinforced and non-reinforced cues
[Genotype × Training day ANOVA, effect of Training day only, F4,21 = 24.44, P< 0.0001]
(Fig.18f). After training, both groups of mice were administered DT and discrimination memory
was assessed in a probe test. As before, control mice spent more time searching close to the
previously reinforced cue compared to the non-reinforced cue in the probe test [planned paired t-
test, t11 = 3.02, P< 0.01]. Interestingly, DT-induced ablation produced a more subtle deficit than
cytotoxic hippocampal lesions. While discrimination was abolished in the 2xTg mice [planned
paired t-test, P> 0.05], their propensity to search close to either of the cues remained intact
(Fig.18g-h).Therefore, these results indicate that post-training ablation of a population of
predominantly mature, adult-generated neurons led to the degradation (rather than complete
erasure) of a visual discrimination memory: Some general features of the memory were retained
(e.g., cue-platform association), but the ability to discriminate between similar cues was
impaired.
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Figure 18. Post-training ablation of adult-generated neurons impairs visual discrimination memory. (a) During
training, a submerged platform was located beneath one of two visual cues (e.g., horizontal stripes). After training,
the hippocampus was lesioned, and discrimination between the reinforced and non-reinforced cues was evaluated in
a probe test. (b) Before surgery, latency to locate the platform declined at similar rates in Lesion (n = 10) and Sham
(n = 9) mice. (c) After surgery, whereas Sham mice searched selectively at the reinforced cue, HPC lesion mice did
not search at either cue. (d) Representative images of brains from Sham and Lesion mice. (e) CTR (n = 12) and
2xTg (n = 11) mice were treated with TAM and then trained in the visual discrimination task. Following DT-
induced ablation of adult-generated neurons, visual discrimination memory was assessed in a probe test. (f) Across
training days, latency to locate the platform declined at similar rates in CTR and 2xTg mice. (g) In the probe test,
whereas CTR mice searched selectively at the reinforced cue, 2xTg mice spent equivalent amounts of time close to
the reinforced and non-reinforced cues. (h) Heat maps reflect preferential searching close to previously reinforced
(left peak) vs. non-reinforced (right peak) cue in CTR but not 2xTg mice. Note that the peak at top of pool
corresponds to the release point at the start of the probe test. * denotes P< .05.
Table 2: CreERT2
expression analysis in 4 week old Nestin+ mice
Cell maturity marker Nestin DCX NeuN
Percent of CreERT2+
cells
expressing marker (±
s.e.m.)
97 ± 0.94 85 ± 2.3 0.72 ± 0.26
Cells analyzed 490 460 474
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Table 3: Maturation profile characterization of tagged population at the time of training
Cell Type Type 1, 2a,
2b
Type 2b, 3,
immature neuron Immature neuron
Immature to
mature neuron
Postmitotic mature
neuron
Cell maturity marker Nestin DCX Calretinin NeuN Calbindin
Percent of LacZ+ cells
expressing marker (±
s.e.m.)
3.1 ± 1.1 5.1 ± 1.8 0.72 ± 0.46 94 ± 1.4 94 ± 2.1
Cells analyzed 455 513 457 374 461
4.4 Discussion
In these experiments we used a ‗tag and ablate‘ transgenic strategy to examine the role of
adult-generated neurons in hippocampal memory. This approach offered two key advantages.
First, unlike previous approaches that targeted neural stem or progenitor cells to produce a global
disruption of neurogenesis (Clelland et al., 2009; Deng et al., 2009; Dupret et al., 2008; Garthe et
al., 2009; Imayoshi et al., 2008; Kitamura et al., 2009; Saxe et al., 2006; Shors et al., 2001;
Zhang et al., 2008), our ‗tag and ablate‘ system allowed us to specifically target a population of
adult-generated neurons that were predominantly born several weeks prior to training, without
impacting ongoing proliferative activity in the adult hippocampus. Second, whereas previous
approaches largely manipulated neurogenesis before learning, our strategy allowed us control
over the timing of the ablation. Therefore, using this system we were able to ablate adult-
generated neurons before or after memory formation. We found that selective ablation of adult-
generated neurons immediately (or up to one month) after training impaired subsequent memory
expression in three distinct hippocampus-dependent tasks. Previous studies provided correlative
evidence that adult-generated neurons are activated during the formation and expression of
hippocampal memories. The present findings—that their post-training ablation disrupts
expression of a previously acquired memory—provides direct experimental evidence that these
neurons, if available at the time of learning, come to form an essential and enduring component
of hippocampal memory traces.
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To ablate populations of adult-generated granule cells in a temporally-specific manner,
we took advantage of the well-characterized DT system (Buch et al., 2005). DT reliably induces
apoptosis following receptor-mediated endocytosis (Dorland and Middlebrook, 1979), but wild-
type mouse cells are 10,000 fold less sensitive to DT than human or monkey cells (Middlebrook
et al., 1977; Eidels et al., 1983; Stenmark et al., 1988). We exploited the insensitivity of mouse
cells to DT by using a transgenic line of mice in which a functional simian DTR receptor is
expressed in a Cre-recombinase inducible fashion (iDTR mice). Crossing iDTR mice with mice
that express an inducible Cre-recombinase in nestin+ cells allowed us to permanently express
DTRs in neural progenitor cells and their progeny. Importantly, we found that neither DT
administration nor DTR expression alone affected memory, consistent with previous findings
(Han et al., 2009). Rather, only the combination of DTR tagging and DT administration induced
retrograde memory loss, showing the specificity of the system.
The cells targeted for ablation included progenitor cells, immature neurons and mature
neurons. Therefore, our post-training ablation effects on memory might be due to loss of any (or
all) of these different cell populations. Indeed, genetic deletion of predominantly immature adult-
generated neurons is associated with long-term retention deficits in a water maze task (Deng et
al., 2009), suggesting that this population of cells contributes to memory robustness. However,
cellular imaging approaches suggest that adult-generated neurons are not maximally activated
during memory formation and/or expression until they reach a more mature stage (> 4 weeks of
age; (Kee et al., 2007; Stone et al., 2011b)). In our experiments the majority of tagged cells were
mature (e.g., 94% were calbindin+ and therefore >4 weeks in age (Zhao et al., 2008)), and
therefore it is very likely that loss of this population of mature, adult-generated neurons
contributed significantly to memory loss.
In contrast to the impairment produced by post-training ablation of adult-generated
neurons, similar pre-training ablation did not prevent the formation of new memories. These
effects parallel those of partial hippocampal lesions in water maze (both hidden (Moser and
Moser, 1998) and visual discrimination (Epp et al., 2008) versions) and contextual fear tasks
(Maren et al., 1997; Frankland et al., 1998; Wiltgen et al., 2006). For example, whereas chemical
lesions ablating ~30% of hippocampal tissue disrupt the expression of a previously-acquired
water maze memory, similar-sized lesions do not prevent the acquisition of a new water maze
memory (Moser and Moser, 1998). This suggests that, while spatial memories may normally be
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distributed throughout the hippocampus, new learning may be supported by residual tissue when
the lesion precedes training. Analogously, here we show that in the absence of a large population
of adult-generated neurons, memory formation may be supported by existing dentate neurons
without an obvious impact on memory quality. This potential for compensation by existing,
developmentally-generated granule cells may account for variable impact of pre-training
disruptions of adult neurogenesis on memory formation. While memory formation may be
impaired by pre-training suppression of adult neurogenesis (Clelland et al., 2009; Deng et al.,
2009; Drew et al., 2010; Dupret et al., 2008; Garthe et al., 2009; Imayoshi et al., 2008; Saxe et
al., 2006; Shors et al., 2001; Tronel et al., 2010; Zhang et al., 2008), sometimes the effects of
these types of manipulations are mild or even nonexistent (Hernández-Rabaza et al., 2009;
Jaholkowski et al., 2009; Deng et al., 2010). Many factors differ across studies, and likely
contribute to the discrepant results. The advantage of the current approach is that we were able to
directly contrast pre- and post-training ablations under identical conditions (i.e., method of
ablation, number and type of cells targeted, training paradigm, apparatus, etc.). Our finding that
post-training lesions had greater impact than pre-training lesions is consistent with the idea that
targeting neurons after memory formation is likely more disruptive because these neurons have
already become committed to the memory trace.
Because cell death is induced by apoptosis, rather than necrosis, using our DT system,
impact on surrounding cells is minimized. Indeed, following DT-induced ablation there was no
hippocampus-wide increase in astrocyte number, and the increase in microglia number was
restricted to the DG. Nonetheless, our ablation affected a large number of cells (>30,000), and
therefore might non-specifically impact hippocampal function. However, the dissociable effects
of pre- and post-training ablation on memory suggest that such off-targeteffects cannot account
for the results. For example, the absence of pre-training effects in our water maze experiment
indicates that DT-induced ablation did not simply affect swimming, navigation, vision or
motivation necessary for the expression of a spatial memory. Likewise, in our contextual fear
experiment, the absence of pre-training effects indicates that DT-induced ablation did not simply
affect the ability to perceive differences between similar contexts. Finally, it is worth noting that
our DT-induced ablation should additionally lead to loss of subventricular zone-generated cells
in the olfactory bulb. However, it is unlikely that the loss of these neurons can account for our
retrograde memory effects since we observed consistent memory loss in three different tasks,
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each with different stimulus properties and performance demands. In particular, the two water
maze-based tasks do not depend on olfactory information (Morris et al., 1982).
Neurogenesis in the DG can be classified into three broad periods: embryonic, postnatal
and adult. Embryonic and postnatal neurogenesis occurs as a result of proliferation in the
primary, secondary and tertiary dentate matrices. However, these germinal regions decline by
postnatal day 10. By postnatal day 20-30, and continuing throughout adulthood, neurogenesis
becomes restricted to the subgranular zone (Altman and Bayer, 1990). Therefore, in our
experiments we initiated TAM treatment in mice at 4 weeks of age (for similar experimental
strategies see: (Ables et al., 2010; Sierra et al., 2010)). As proliferation rates are higher in this
post-juvenile period, this approach enabled us to ‗tag‘ large numbers of granule cells. Even so
this tagged population (including both cells generated during a post-juvenile period as well as
during adulthood) represents no more than 6% of the entire population of granule cells at the
time of ablation. That deletion of this relatively small proportion of dentate neurons was
sufficient to produce robust retrograde memory deficits across three different tasks is perhaps
surprising, and suggests that this population of subgranular zone-generated neurons plays an
especially important role within a broader network of dentate neurons supporting contextual fear,
water maze and visual discrimination memories. Indeed, it is necessary to lesion >15% of the
entire hippocampus to produce similar retrograde memory deficits in the water maze (Moser and
Moser, 1998). Since cells generated at different stages of development and adulthood appear to
be integrated into hippocampal memory circuits at similar rates (Stone et al., 2011b), this
suggests that this population of subgranular zone-derived neurons may disproportionately
influence hippocampal memory function, and raises the possibility that granule cells derived
from the subgranular zone may make distinct contributions to hippocampal memory relative to
those generated in the primary, secondary and tertiary matrices earlier on during development.
What is the nature of this role? In the fear conditioning and visual discrimination tasks, post-
training ablation led to memory degradation rather than erasure. In both tasks, while some
general features of the memory were retained (e.g., context-shock, cue-platform associations),
the ability to discriminate between similar contexts and patterns was impaired. Consistent with
recent reports (Clelland et al., 2009; Sahay et al., 2011), these deficits may suggest a specialized
role for adult-generated neurons in disambiguating similar (but nonetheless discrete)
representations (or pattern separation).
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Chapter 5 Post-training Ablation of Adult Generated Olfactory Interneurons
Impairs Associative Odour Memory Expression
5.1Abstract
In the adult brain, new neurons are continuously generated in the subventricular zone
(SVZ) and migrate into the olfactory bulbs (OB), where they mature and integrate into OB
circuitry. Previous studies have implicated adult-generated OB interneurons in olfactory
function, although their precise contribution to olfactory processing remains unclear. Here, we
examined whether adult-generated OB neurons play a role in the expression of an associative
odor memory. We used a tag and ablate strategy in which tamoxifen treatment of double
transgenic mice (nestin-CreERT2
-iDTR) leads to permanent expression of the diphtheria toxin
receptor exclusively in nestin-positive neural progenitor cells and their progeny (tagging).
Subsequent treatment with diphtheria toxin (DT) leads to highly efficient ablation of adult-
generated OB interneurons with precise temporal control. Three weeks after tagging, adult mice
were trained to associate a particular odor with a reward by consistently pairing one odor (+
odor) but not another odor (- odor) with sugar pellets located under the bedding. Post, but not
pre-training ablation of tagged neurons impaired olfactory associative memory expression. Our
finding that ablation of OB interneurons leads to a retrograde impairment in an olfactory
associative memory task indicates that adult-generated OB interneurons form an essential
component of olfactory memory traces.
5.2 Introduction
Olfaction is a critical sensory modality necessary for danger detection, food retrieval,
maternal and social behaviours. The subventricular zone (SVZ) is a site of continuous
neurogenesis throughout adulthood (Altman, 1969; Kaplan and Hinds, 1977; Bayer, 1983).
Neuroblasts originated from the SVZ migrate through the rostral migratory stream into the
olfactory bulb, where they differentiate into olfactory interneurons and integrate into the circuitry
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(Altman, 1969; Lois and Alvarez-Buylla, 1994; Doetsch and Alvarez-Buylla, 1996; Petreanu and
Alvarez-Buylla, 2002; Winner at al., 2002; Belluzzi et al., 2003; Carleton et al., 2003; Belnoue et
al., 2011). Activation of olfactory interneurons through the excitation of mitral/tufted cells leads
to lateral inhibition of neighbouring mitral/tufted cells and synchronization of network
oscillations (Laurent, 2002; Lledo and Lagier, 2006). Both these functions have been shown to
mediate olfactory perception (Kay and Laurent, 1999; Beshel et al., 2007; Cleland et al., 2007;
Mandairon and Linster, 2009) and discrimination (Yokoi et al., 1995; Stopfer et al., 1997; Nusser
et al., 2012). Investigation of the role adult generated olfactory interneurons play in these
processes has yielded mixed results, with some (Breton-Provencher et al., 2009; Lazarini et al.,
2009; Moreno et al., 2009; Sultan et al., 2010) but not others (Kim et al., 2007; Imayoshi et al.,
2008; Breton-Provencher et al., 2009; Lazarini et al., 2009) finding a deficit in olfactory function
due to ablation of neurogenesis. These studies vary in terms of ablation method, age of the cells
affected and behavioural protocol, but have one commonality: they all consist of pre-training
manipulations, exclusively examining effects on acquisition. Presently, it is unclear whether one
or all of these factors are responsible for the contradictory findings, and decisive evidence
concerning the role of adult-generated olfactory interneurons in olfactory function is lacking.
To address this issue, we have devised a transgenic strategy to achieve temporal control
over adult neurogenesis ablation, so that it is possible to compare the ablation of a same cell
population done before or after training (Arruda-Carvalho et al., 2011). Using this ‗tag and
ablate‘ strategy, tamoxifen (TAM) treatment of double transgenic nestin-CREERT2
-iDTR mice
leads to exclusive expression of diphtheria toxin receptor (DTR) in nestin expressing progenitor
cells and their progeny (tagging) (Lagace et al., 2007; Imayoshi et al., 2008; Arruda-Carvalho et
al., 2011). Subsequent treatment with diphtheria toxin (DT) leads to highly efficient ablation of
these cells (Buch et al., 2005; Arruda-Carvalho et al., 2011). We found that post- (but not pre-)
training ablation led to a deficit in an associative odour memory task, showing that adult-
generated olfactory interneurons are necessary for the expression of olfactory associative
memory.
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5.3 Results
5.3.1 CREERT2 expression is restricted to neural stem cells
We used a nestin-CREERT2
mouse line with higher recombination in the SVZ (line 5-1 in
Imayoshi et al., 2008). Consistent with previous reports (Imayoshi et al., 2008), we confirmed
that CREERT2
expression at the time of tamoxifen treatment colocalized exclusively with neural
progenitor cell markers such as nestin and not with the neuroblast (type A cells) marker DCX
(Fig. 19 and table 4).
Figure 19: CreERT2
expression is restricted to neural stem cells. (a) In nestin-CreERT2+
mice, CreERT2
protein
expression (green) was found in nestin+ (red) cells, but not in (b) DCX
+ cells (red) in the SVZ (scale = 10 µm).
5.3.2 Characterization of the tagging
To facilitate the visualization of tagged cells we crossed nestin-CREERT2
mice with a
Rosa26-lacZ reporter line (which uses the same promoter as the iDTR mouse line). It has been
previously described that TAM-induced recombination in this system is specific, only occurring
when both nestin-CREERT2
and Rosa26-LacZ (or Rosa26-iDTR) transgenes are present (Arruda-
Carvalho et al., 2011). Recombined cells were distributed throughout the OGCL and in the GL
(Fig. 20).
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Figure 20: Distribution of tagged neurons in the OB. Recombination (LacZ+ cells, green) was distributed in the
OGCL and GL.
At around 2-3 weeks of age, adult olfactory granule cells display a window of
hyperplasticity in which synaptic strength (Nissant et al., 2009) and response to novel odours
(Magavi et al., 2005) are enhanced. Given this critical period of plasticity, we wanted to
investigate whether 3 week old adult generated olfactory interneurons were necessary for
olfactory memory expression. First, we phenotyped these cells 3 weeks after tamoxifen
treatment, at the time of behavioural training. Our tagged granule cell population still retained a
considerable amount of immature cells, with approximately 33% of cells expressing the
immature cell marker doublecortin (DCX), and 63% the cell marker NeuN (Fig. 21, table 5), as
expected (Petreanu and Alvarez-Buylla, 2002; Winner at al., 2002). LacZ-positive cells located
close to the glomerular layer - consistent with periglomerular cells - were also observed but were
a minority (roughly around 10% of total tagged population) (Fig. 20).
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Figure 21: Maturation analysis of adult born olfactory granule cells. Three weeks after the start of TAM treatment,
roughly a third of LacZ+ cells (green) co-stained for immature neuronal marker DCX (a), whereas most tagged cells
colabeled with NeuN (red) (b).
5.3.3 Post-training ablation of adult born olfactory interneurons impairs associative olfactory memory expression
Manipulations of adult neurogenesis in olfactory tasks have so far been done before
training (Gheusi et al., 2000; Enwere et al., 2004; Kim et al., 2007; Bath et al., 2008; Imayoshi et
al., 2008; Breton-Provencher et al., 2009; Lazarini et al., 2009; Mouret et al., 2009; Moreno et
al., 2009). Evidence from lesion (Moser and Moser, 1998) and hippocampal neurogenesis
(Arruda-Carvalho et al., 2011) studies suggests that compensation may mask the effects of pre-
training manipulations. Hence, we were interested in exploring whether a post-training
manipulation would be more efficient at disrupting an olfactory associative memory.
To do this, we treated control (either nestin-CREERT2
or iDTR single positive mice, CTR)
and 2xTg animals (nestin-CREERT2
-iDTR double transgenic animals, 2xTg) with tamoxifen and
waited three weeks to train them in a hippocampus independent (Akers et al., 2011) associative
olfactory task (Imayoshi et al., 2008). In this associative olfactory discrimination task, food
deprived mice were trained for four consecutive days to discriminate between two similar odours
[the enantiomers (+) and (–) carvone], one of which was reinforced with sugar pellets. Mice
learned to dig over the correct odour to find the pellets, which was assessed in a probe trial when
both odours were present in the absence of sugar. Both control and 2xTg learned the association
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between the correct odour and the reward, as seen by spending more time digging on the
previously reinforced odour [planned comparisons: Pre-DTCTR t10 = 5.80, P < 0.0001; Pre-
DT2xTg t15 = 4.77, P < 0.001] (Fig. 22c-d, Pre-DT), thus excluding the possibility that tagging had
a detrimental effect on the motivation or motor skills necessary to perform this task.
Animals were then treated with DT for five consecutive days and probed 24h after (Fig.
22a). DT treatment has been previously shown to promote highly efficient and specific ablation
with minimal inflammation (Buch et al., 2005; Han et al., 2009; Arruda-Carvalho et al., 2011).
Nevertheless, to account for non-specific effects of the drug treatments, we used a genotype
control to ensure all animals are treated with both TAM and DT.
During a probe test following DT treatment, control animals were still able to remember
the odour-reward association, but 2xTg mice lost that association, as they spent an equivalent
amount of time digging over either odour (Fig.22b, c; Post-DT) [CTR: Odour × Probe ANOVA,
effect of Odour, F1,30 = 17.20, P< 0.001 and Probe F1,30 = 12.14, P< 0.01; planned comparisons:
Post-DTCTR t10 = 2.56, P < 0.05; 2xTg: Odour × Probe ANOVA, Interaction F1,30 = 13.55, P<
0.001; planned comparisons: Post-DT2xTg P > 0.05]. This post-training ablation deficit was
confirmed through a preference index, in which 2xTg, but not control animals, experience a drop
in their preference for the previously reinforced odour after DT treatment (Fig.22d) [Genotype ×
Probe ANOVA, no significant effect, planned comparison 2xTg t15 = 2.23, P < 0.05].
Importantly, this deficit cannot be attributed to impairment in anxiety or motor function, since
ablation did not interfere with performance in the open field (Fig. 23) [Genotype × Zone
ANOVA, effect of Zone only, F2,32 = 525.5, P< 0.0001; unpaired t-test: t16 = 2.16, P <0.05].
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Figure 22: Post-training ablation of adult-generated olfactory interneurons impairs expression of an associative
olfactory memory. (a) 8 week old animals were treated with TAM and then trained in an associative olfactory
memory task. After 4 days of training animals performed a probe test (Pre-DT) in the presence of both the
previously reinforced odour (+ odour, black bars) and its enantiomer (-odour, white bars). Following 5 days of DT-
induced ablation of adult-generated interneurons, associative memory was assessed in a probe test (Post-DT).
Control (n = 11) (b) and 2xTg (n = 16) (c) mice learned to associate an odour with the reward equivalently (Pre-DT).
Following DT-induced ablation, 2xTg mice lost the preference for the previously reinforced odour (Post-DT), as can
be visualized through their preference index (d). * denotes P< .05.
Figure 23: Open field performance following DT-induced ablation of adult generated olfactory interneurons. Three
weeks after the start of TAM treatment, CTR (n = 14) and 2xTg (n =4) mice were treated with DT for five days. (a)
We observed no effect on time spent in the outer, middle and innermost regions of the open field, but there was a
significance difference in (b) total exploration in the open field. * denotes P< .05.
Interestingly, TAM treatment started at 4-5 weeks of age (Fig.24a), a strategy used in
order to maximize the number of tagged neurons (see Ables et al., 2010; Sierra et al., 2010;
Arruda-Carvalho et al., 2011 for a similar strategy), yields a similar deficit (Fig.24b,c) [CTR:
Odour × Probe ANOVA, effect of Odour, F1,26 = 28.18, P< 0.001 and Probe F1,26 = 5.18, P<
0.05; 2xTg: Odour × Probe ANOVA, effect of Odour only F1,22 = 12.70, P< 0.01; planned
comparisons: Post-DTCTR t13 = 4.88, P < 0.001; Post-DT2xTg P > 0.05], which can also be
visualized in terms of a preference index (Fig 22d) [Genotype × Probe ANOVA, effect of Probe
only F1,24 = 5.72, P< 0.05; planned comparisons: 2xTg t11 = 2.61, P < 0.05 ]. Together, these data
suggest that adult born olfactory interneurons play an important role in olfactory associative
memory expression.
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Figure 24: Post-training ablation of adult-generated olfactory interneurons impairs expression of an associative
olfactory memory. (a) 4-5 week old animals were treated with TAM and then trained in an associative olfactory
memory task. After 4 days of training animals performed a probe test (Pre-DT) in the presence of both the
previously reinforced odour (+ odour, black bars) and its enantiomer (-odour, white bars). Following 5 days of DT-
induced ablation of adult-generated interneurons, associative memory was assessed in a probe test (Post-DT).
Control (n = 14) (b) and 2xTg (n = 12) (c) mice learned to associate an odour with the reward equivalently (Pre-DT).
Following DT-induced ablation, 2xTg mice lost the preference for the previously reinforced odour (Post-DT), as can
be visualized through their preference index (d). * denotes P< .05.
5.3.4 Pre-training ablation of adult born olfactory interneurons does not interfere with associative olfactory memory acquisition
The majority of studies fail to see a deficit in olfactory associative memory acquisition
following reduction of adult neurogenesis (Kim et al., 2007; Imayoshi et al., 2008; Breton-
Provencher et al., 2009; Lazarini et al., 2009), with one exception (Enwere et al., 2004).
However, since the Enwere study uses global knockouts it is possible that its effects on memory
acquisition are consequence of embryonic events and thus do not pertain to adult neurogenesis.
Next, we wanted to perform a pretraining ablation of adult olfactory interneurons in order to
compare it with our post-training ablation and previous published results.
When the ablation was performed before training, both control and 2xTg animals
acquired the olfactory association similarly (Fig. 25b-c, 1 day; Fig. 25d), and were able to retain
that association for at least 28 days (Fig. 25b-c, 28 days; Fig. 25d) [CTR: Odour × Probe
ANOVA, effect of Odour only, F1,28 = 22.57, P< 0.0001; planned comparisons: 1DayCTR t14 =
5.32, P < 0.001; 28DaysCTR t14 = 4.31, P < 0.001; 2xTg: Odour × Probe ANOVA, Interaction
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F1,28 = 4.62, P< 0.05; planned comparisons: 1Day 2xTg t14 = 5.14, P < 0.001; 28Days 2xTg t14 =
2.71, P < 0.05; Preference index Genotype × Zone ANOVA, no significant effect; planned
comparisons P > 0.05]. Our pre and post-training ablations target the same population of cells,
ensuring that the only difference between them is the timing of the ablation. Hence, this data
excludes the possibility that the ablation interferes with motivation, odour detection or motor
skills necessary to express this associative memory, and reinforces the idea that posttraining
elimination of this cohort of cells, and not tagging or DT treatment alone, causes the olfactory
memory expression deficit. These data suggest that, if present at the time of training, adult
generated olfactory interneurons are necessary for associative olfactory memory expression.
Figure 25: Pre-training ablation of adult-generated olfactory interneurons does not impair acquisition of an
associative olfactory memory. (a) 4-5 week old animals were treated with TAM. Five days before training animals
were given daily DT injections. 24h. after the last DT injection animals were trained in an associative olfactory
memory task. After 4 days of training animals performed a probe test (1 Day) in the presence of both the previously
reinforced odour (+ odour, black bars) and its enantiomer (-odour, white bars). Another probe test was conducted 28
days later to assess long-term memory (28 Days). Control (n = 15) (b) and 2xTg (n = 15) (c) mice showed no deficit
in acquiring the olfactory association (1 Day), nor in the long-term retentionof that memory (28 Days), as can be
visualized through their preference index (d). * denotes P< .05.
Table 4: SVZ
Cell maturity marker Nestin DCX
Percent of CreERT2+
cells
expressing marker (± s.e.m.) 96 ± 1.2 2.6 ± 0.3
Cells analyzed 537 536
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Table 5:OB
Cell maturity marker
DCX
NeuN
Percent of LacZ+ cells
expressing marker (± s.e.m.)
33 ± 2.7
63 ± 2.3
Cells analyzed
836
658
5.4 Discussion
Using a tag and ablate double transgenic strategy we assessed the contribution of adult
generated olfactory interneurons to the acquisition and retrieval of an associative olfactory
memory task. We confirmed that CREERT2
expression was restricted to neural progenitor cells in
our system and that recombination occurred uniformly throughout the OB. At three weeks of
age, our tagged population was composed of cells expressing a mixture of DCX and NeuN
positive cells. Post-training ablation of three week-old cells led to deficits in associative olfactory
memory expression, while pre-training ablation of the same cell population did not impair
acquisition of the olfactory association or its long term retention. The fact that the ablation of this
population of young OB interneurons after associative learning produces a retrograde
impairment in task performance suggests that adult-generated OB interneurons form an essential
component of olfactory memory traces.
Our tag and ablate strategy allows for high recombination efficiency, targeting a
considerable population of cells, and their specific and highly efficient elimination (Buch et al.,
2005; Arruda-Carvalho et al., 2011). This DTR approach offers a few advantages: its specificity
and lack of side effects reduces the opportunity for compensation, and the separation between the
tagging and ablation steps gives temporal flexibility to target different stages of memory
processing. Additionally, the dissociation between pre- and post-training ablation further
excludes the possibility that the deficit in olfactory associative memory found after post-training
ablation is due to non-specific effects in vision, odour detection, motivation or sensorimotor
function. Although this strategy targets cells in both the SVZ-OB and hippocampus, our task has
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been shown to be hippocampus independent (Akers et al., 2011), restricting the functional effects
of our ablation to the olfactory system. Our tagged population consisted predominantly of
granule cells, but periglomerular cells were also tagged. Presently, we are unable to assess the
different contributions of these cell types to our findings, and further studies will be needed to
examine the individual role of periglomerular cells to odour memory and discrimination tasks.
Our DT-induced ablation allowed us to select a population of cells and manipulate the
ablation timing to eliminate them before or after memory acquisition. We found that pre-training
ablation did not disrupt acquisition of an associative olfactory memory, suggesting that plasticity
of the remaining olfactory interneurons was sufficient to encode the association. Post-training
ablation of the same cohort of cells disrupted task performance. This dissociation mirrors that of
hippocampal lesions (Moser and Moser, 1998) and adult hippocampal neurogenesis (Arruda-
Carvalho et al., 2011) in which posttraining lesions seem to be more disruptive than pre-training
ones, likely due to commitment of the tagged neurons to that representation during learning.
Given that previous manipulations of adult olfactory neurogenesis were done prior to training, it
is possible that compensation from the remaining olfactory interneurons contributed to the lack
of effect in these studies (Kim et al., 2007; Imayoshi et al., 2008; Breton-Provencher et al., 2009;
Lazarini et al., 2009).
The interpretation of adult olfactory neurogenesis loss of function studies could be
divided into behavioural tasks assessing odour memory and odour discrimination. Often an
associative task similar to ours is used as an assessment of both olfactory discrimination and
long-term memory (Imayoshi et al., 2008; Breton-Provencher et al., 2009; Lazarini et al., 2009).
Most ablation studies fail to see an effect in olfactory discrimination (Imayoshi et al., 2008;
Breton-Provencher et al., 2009; Lazarini et al., 2009), but some see a deficit in long-term odour
memory (Lazarini et al., 2009; Sultan et al., 2010). We interpreted our retrograde deficit in
associative memory performance as an odour memory deficit for the following reasons: (1) we
did not test the animals using different concentrations or mixtures of our odours i.e. in a protocol
in which fine discrimination could be directly assessed, and (2) pre-training ablation did not
impact the animal‘s ability to discriminate between the two odours and form an association,
suggesting that what is lost in the post-training ablation group is the association between the
odour and the reward, and not the mere ability to distinguish between both odours.
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The literature concerning functional implications of adult olfactory neurogenesis
comprises different tasks for assessing associative olfactory memory, that range from a go/no-go
task (Lazarini et al., 2009; Mouret et al., 2009), mixtures in drinking water (Enwere et al., 2004;
Kim et al., 2007), digging tasks as the one used here (Imayoshi et al., 2008; Breton-Provencher
et al., 2009) and its variation (Sultan et al., 2010). The difference in nature and degree of
difficulty of those tasks could account for differential involvement of higher order structures and,
as shown in the hippocampus (Drew et al., 2010), a varying degree of adult neurogenesis
dependency. Therefore, exploiting variables within a same task, as done here, could prove
especially insightful in overcoming this challenge.
In this study, we chose to target adult olfactory interneurons at 3 weeks of age, because
this stage corresponds to the critical period of granule cells, during which they are more
responsive to novel odours (Magavi et al., 2005) and are more plastic (Nissant et al., 2009). Post-
training ablation of 3 week old cells impaired performance in our associative task. Belnoue and
colleagues described preferential recruitment of 5-9 weeks old granule cells in an associative
go/no-go task (Belnoue et al., 2011). Our data suggests this recruitment might start around the 3
week old stage, a time point unexplored by those authors. Using the flexibility of design in our
tag and ablate strategy, it would be very interesting to explore different stages of cell maturation,
e.g. younger cells, at a stage in which they have reached the OB but lack spines and are mostly
non-spiking (Petreanu and Alvarez-Buylla, 2002; Carleton et al., 2003), thus likely not involved
in odour processing; and older cells past the hyperplastic period, when they are described to
behave similarly to developmentally generated OGCs (Carleton et al., 2003; Nissant et al., 2009).
With this approach we would be able to determine, within the same task, whether the
contribution of olfactory interneurons to associative memory expression is age-dependent.
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Chapter 6 General Discussion
6.1 Summary of Results
In this thesis we have applied a transgenic tag and ablate strategy to specifically target
adult born neurons in the hippocampus and olfactory bulb and look at their contribution to
memory function. This enabled us to characterize our tagged population in terms of number,
distribution and maturation stage. Importantly, the temporal versatility of our approach allowed
us to compare adult born neuron ablations done before and after training.
In the hippocampus, we targeted a population of predominantly mature cells evenly
distributed throughout the anterior-posterior axis of the DG comprising approximately 6% of
total dentate granule cell population. Ablation of this cell population before training did not
impair acquisition of two hippocampal dependent tasks, CFC and MWM, suggesting that the
remaining DGCs may support memory formation when in the absence of aDGCs. Immediate (or
up to four weeks) postttraining ablation of this cell population led to memory degradation in
three hippocampal dependent tasks (CFC, MWM and visual discrimination WM), showing that
aDGCs, if present at the time of training, come to form an integral and enduring part of the
memory trace.
In the olfactory system, we investigated whether 3 week old olfactory interneurons, a
time point in which cells are hyperplastic, were involved in a hippocampus independent
associative olfactory task. Ablation of these cells before training did not prevent acquisition of an
olfactory associative memory. Posttrainign ablation of that same cohort of cells, however,
impaired expression of the olfactory association, suggesting that, as with the hippocampus, adult
olfactory interneurons form an essential component of olfactory memory traces.
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6.2 Pre vs. Posttraining
Due to technical limitations, prior to the studies reported in this thesis, manipulations of
adult neurogenesis happened before training. The basic experimental design in those papers
consisted of ablation of neurogenesis, followed by a recovery period (typically around 4-8
weeks), then training in a memory task, and a probe test (Snyder et al., 2005; Meshi et al., 2006;
Saxe et al., 2006; Winocur et al., 2006; Hernández-Rabaza et al., 2009).
Although important in establishing a connection between hippocampal neurogenesis and
memory, these results are quite mixed (Deng et al., 2011), and fail in directly establishing
whether adult born neurons functionally support memory encoding for two main reasons. First,
homeostatic response to the ablation likely leads to a change in proliferation and survival levels,
thus DG circuitry 4-8 weeks after ablation is not necessarily comparable to its normal
(physiological) state. Second, plasticity in the system might mask the involvement of these cells,
i.e. if the remaining cells are able to encode a memory in the absence of the aDGCs it does not
necessarily mean aDGCs are not normally involved in this process. Particularly, the size of the
ablation (number of cells affected) compared to the existing DGC population could be crucial in
predicting the behavioural outcome of the manipulation (see discussion below).
Therefore, our group speculated that a direct way of determining whether aDGCs
functionally support memories would be to ablate them after learning: if aDGCs form a critical
part of that memory trace, posttraining ablation will lead to a memory deficit during retrieval. To
do this, we developed a transgenic tag and ablate strategy, in which tamoxifen injection led to
permanent expression of DTR in neural progenitors and their progeny. Subsequent DT treatment
before or after learning led to the specific ablation of the tagged population. We showed that post
(but not pre) training ablations led to memory degradation in three hippocampus dependent
tasks: fear conditioning, MWM and visual discrimination WM. Since pretraining ablations did
not prevent acquisition of these tasks, we could rule out non-specific effects on vision,
motivation, sensorimotor function, inflamation or overall circuit disturbance as alternative
explanations for our findings.
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A similar dissociation between pre- and posttraining is found in the hippocampal lesion
literature. Moser and Moser investigated the proportion of hippocampus necessary for
acquisition vs. retrieval of MWM memory. They found that complete hippocampal lesions
impaired both encoding and retrieval of MWM memory (Morris et al., 1982, 1990b). However,
whereas ~20% of the hippocampus (from the dorsal end) is sufficient for MWM learning, 70%
of dorsal hippocampus was necessary for retrieval (Moser and Moser, 1998). Their main
conclusions were that (1) posttraining ablations were more disruptive that pre-training ones, i.e.
hippocampal function is more sensitive to posttraining manipulations, and (2) memories seem to
be distributed in the hippocampus, since lesions located in different hippocampal subregions
mostly did not impair acquisition (Moser and Moser, 1998).
We believe the same is happening in our system, since our posttraining ablations were
consistently more disruptive than equivalent pretraining ones. A likely explanation for this
phenomenon relates to the aforementioned issue of plasticity of the system. In an extremely
simplistic model, memory encoding consists of the recruitment of X number of cells into a
memory trace, and proper retrieval requires reactivation of a proportion of that same population
of cells (see Reijmers et al., 2007 and discussion below). Accepting this model, encoding is
possible as long as the total number of available cells (Y) exceeds or is the same as X. Once the
trace is formed, however, it can only be retrieved if a sufficient proportion of those specific X
cells remains. Therefore, encoding has more cells to spare (Y-X) than retrieval (X), hence the
potential for compensation and consequent increased resilience of the system to pretraining
lesions, explaining why the establishment of a network (during encoding) makes a memory more
sensitive to disruption by posttraining manipulations.
Interestingly, we saw a trend towards impairment in acquisition in some of our
experiments, particularly in the MWM (see Fig. 17). Two points are relevant to that observation.
First, drawing from the Moser and Moser study, an effective pretraining lesion not only needs to
be larger than a posttraining lesion but also needs to be large enough. This might be a key point
in understanding some of the inconsistencies in the pretraining ablation literature. The fact that
the size of the ablation in a pretraining design needs to be so large could explain the absence of
deficits found in many studies (Shors et al., 2002; Madsen et al., 2003; Raber et al., 2004; Meshi
et al., 2006; Saxe et al., 2006; Dupret et al., 2008; Zhang et al., 2008; Deng et al., 2009),
including our own. It is possible that, had we tagged a larger population of cells, a pretraining
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deficit would have appeared. Second, it has been shown that different behavioural protocols have
different sensitivities to aDGC ablation (Drew et al., 2010), which could account, in our data, for
the impairment trend being present in the MWM but not in fear conditioning.
6.3 Erasure vs. Degradation
The quest for the memory engram has permeated the cognitive neuroscience field for
decades. Karl Lashley‘s search for a cortical area responsible for memory was unsuccessful,
leading him to deny the existence of a memory engram (Lashley, 1950), an assumption that
remained unrefuted for many years. Later research showed that areas outside of the cortex are
involved in memory and that the choice of behavioural task is critical in this quest (Squire, 2004;
see introduction), which may underlie Lashley‘s failure in his search.
The last two decades have brought immense advancement to this pursuit. Technical
developments allowed for the identification of neurons involved in encoding and retrieval,
mainly through expression of immediate early genes (reviewed in Guzowski et al., 2005). Mark
Mayford‘s group developed a model to genetically tag c-fos active neurons (Reijmers et al.,
2007), which allowed quantification of the overlap between the neuronal populations activated
during encoding versus retrieval, strengthening the claim that memories might be restricted to a
specific subset of neurons. Another strong indication came from an auditory fear conditioning
task, in which blockade of AMPA receptor incorporation in as little as 10-20% of lateral
amygdala (LA) neurons was sufficient to reduce memory (Rumpel et al., 2005).
The premise of our studies followed this reasoning: if aDGCs encode memory traces,
retrieval can be disrupted if enough cells are ablated. Confirmation of that premise (and of the
existence of memory engrams) came from the work of Sheena Josselyn‘s group. First, they
showed that CREB overexpressing LA neurons were preferentially recruited to an auditory fear
memory trace (Han et al., 2007). Next, the specific ablation of that subset of neurons led to
complete erasure of the fear memory (Han et al., 2009). This phenomenon has been confirmed
through inactivation of CREB overexpressing neurons (Zhou et al., 2009), and, in a recent study,
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sheer activation of neurons encoding a previous memory trace (tagged through their c-fos
expression) interfered with new memory acquisition, generating a new (hybrid) memory that
differed from the initial encoded association, which the authors referred to as a synthetic memory
(Garner et al., 2012).
In our study, we tagged a subset of DGCs (80-90% of the aDGC population born after 4
weeks of age), allowed them to be incorporated into a memory trace (by training animals in a
memory task), and subsequently ablated those tagged cells, hoping to see a similar memory
erasure effect found by Han and colleagues (Han et al., 2009). In our experiments, we saw a
consistent effect in posttraining ablations amongst all three hippocampus dependent tasks:
although the bulk of the memory remained, degradation occurred. Collectively, this data
reinforces the claim that a memory trace can be sustained by a restricted set of cells.
The structure of memory is multidimensional: it encompasses different categories of
information. For instance, to learn the visual discrimination water maze task used in our study,
animals need to recognize the existence of a submerged platform, their need to swim to it, the
fact that it is signaled by a cue, its distinction from another cue, etc. Hence, it is conceivable that
memory loss may also follow a gradient in its degradation, when some but not all of these
memory elements are lost. Regarding our observations, unlike the Han study, in which freezing
was greatly reduced by neuronal elimination (Han et al., 2009), our 2xTg animals preserved: (1)
the association between context and shock in the fear conditioning (2xTg mice froze similar to
controls in context A), and (2) the association between cue and platform in the visual
discrimination task (2xTg swam mostly around the two cues). In both these tasks 2xTg
performance was clearly impaired, the memory degraded. The partial nature of this degradation
was particularly obvious in the visual discrimination water maze, since in clear contrast with our
2xTg animals, hippocampal lesioned animals swim aimlessly near the border of the pool, the
embodiment of complete memory erasure.
Ablation of a subset of DGCs in our study consistently led to memory degradation, which
to our knowledge is the first indication that aDGCs support the expression of memory traces, and
that engrams may be found in the DG. Consistent with our observations, optogenetic activation
of DGCs previously tagged to a fear memory trace led to freezing behaviour (Liu et al., 2012),
providing further evidence that memory engrams can also be formed by DGCs.
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6.4 Drowning by numbers1
An interesting common point raised by these ‗memory engram‘ type studies (Han et al.,
2009; Zhou et al., 2009; Garner et al., 2012; Liu et al., 2012) is how ablation of only a few cells
(less than 20% of all LA cells in most studies) has such a significant impact on memory. In our
manipulation, we calculated that approximately 6% of total granule cell population was ablated.
The notion that a small subset of cells can have large impact on a system is not
unprecedented. In fact, it is a common feature in several networks. Graph theory predicts that
highly connected self-organizing complex networks, such as the World Wide Web or neuronal
networks, may behave as small world networks (in reference to the ‗small world phenomenon‘ or
6 degrees of separation), which are characterized by a preserved and highly connected topology,
so that any two units in the network can be connected through just a few links (Watts and
Strogatz, 1998).
Some small world networks are scale-free, which means that in a growing network newly
added units connect preferentially to the more highly connected units in the network (Barabási,
1999; Amaral et al., 2000), referred to as nodes or hubs (see Boccaletti et al., 2006 for a review).
A common analogy for this phenomenon comes from airplane routes, when comparing the
impact of closing down an airport such as Chicago O‘Hare versus the airport in Buffalo, NY.
Human brain functional networks also have small world architecture and hub regions
(Achard et al., 2006). Accordingly, targeted attack of the hub regions is more effective at
disrupting the system than an attack on random units (Achard et al., 2006). In the cellular level,
these hubs could represent neurons that are more connected than others and whose impact on the
network as a whole is larger. Indeed, functional neuronal hubs have been demonstrated in the
hippocampus (Bonifazi et al., 2009), and exemplify how a small group of cells can have a large
impact on a system.
1 Reference to the1988 Peter Greenaway movie of the same name
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In our study, we see a consistent impact on memory expression after the ablation of a
small subset of cells. In the hippocampal lesion literature, a minimum of 30% of hippocampal
tissue had to be removed in order to cause retrograde amnesia (Moser and Moser, 1998). The
disparity between our 6% and the 30% in the Moser and Moser study raises a few interesting
possibilities regarding the function of aDGCs. A tempting hypothesis is that these aDGCs are
over-represented in the memory trace. A few studies hint at that possibility, through immediate
early gene analysis (Ramirez-Amaya et al., 2006; Kee et al., 2007). However, more recent
evidence has shown that aDGCs are equally as likely to be incorporated into a memory trace as
their developmentally generated counterparts (Stone et al., 2011b).
Another possibility is that, even though aDGCs are recruited at the same rate as other
DGCs, they are functionally over-represented in memory encoding/retrieval, i.e. they behave as
neuronal hubs. If so, the hyper excitable period (Espósito et al., 2005; Ge et al., 2007a; Marín-
Burgin et al., 2012) displayed by aDGCs during maturation could be key in contributing to
higher connectivity and hub formation. Consistent with this, it has been suggested that immature
DGCs have a larger number of MF boutons when compared to mature DGCs, but this analysis
was performed in P15 mice (Yasuda et al., 2011). A thorough assessment of aDGC connectivity
(e.g. spine and bouton numbers) compared to developmentally generated DGCs would prove
insightful in answering this question, as would a functional network analysis of the circuit.
We have shown that aDGCs are capable of sustaining expression of a memory trace, but
our data cannot presently determine whether aDGCs are functionally distinct from any other
DGC. It is plausible that the only reason we saw memory impairment with our ablation is
because we targeted enough DGCs, regardless of when they were generated. An interesting
experiment to test this hypothesis is to perform a posttraining ablation of similar size and
distribution as ours but targeting exclusively developmentally generated DGCs. Unfortunately,
achieving a method to target a similar number and distribution of cells in the DG is still
technically challenging.
6.5 Avenues for silencing neurons
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Elucidating the function of a specific neuronal population is a frequent challenge in
various fields of neuroscience. A critical step to achieve this goal involves ensuring the isolation
and targeting of a given population with minimal interference to the surrounding cells. In the
neurogenesis field, a trait that discerns developmentally born from adult born neurons is that, in
the adult brain, only the latter are proliferating. Hence, a common ‗loss of function‘ approach in
the field has been to kill proliferating cells, either through pharmacological treatment with
methylazoxymethanol acetate (MAM), Arabinofuranosyl Cytidine (AraC) or temozolomide
(Shors et al., 2002; Breton-Provencher et al., 2009; Garthe et al., 2009; Moreno et al., 2009;
Sultan et al., 2010), or X-ray irradiation (Madsen et al., 2003; Raber et al., 2004; Meshi et al.,
2006; Saxe et al., 2006; Winocur et al., 2006; Warner-Schmidt et al., 2008; Hernández-Rabaza et
al., 2009; Ko et al., 2009; Lazarini et al., 2009; Snyder et al., 2009a; Valley et al., 2009).
Arguably the greatest advantage of both pharmachological and irradiation strategies is
their large impact on neurogenesis [up to 90% in some cases (Valley et al., 2009)], which can be
permanent (Wojtowicz, 2006). Additionally, these manipulations allow for focal intervention, i.e.
independent targeting of SVZ versus SGZ neurogenesis (Wojtowicz, 2006). Their main
disavantage is the possible side effects, described for MAM (Dupret et al., 2005), AraC (Odaimi
and Ajani, 1987) and irradiation (Monje and Palmer, 2003). Although the degree of side effects
caused by irradiation can be minimized with lower doses (Wojtowicz, 2006), it still incurs in
inflamation (See Fig. S21 of Kitamura et al., 2009) and overall health impacts that require a
recovery period. As discussed previously (see section 6.1), it is arguable whether losing the
homeostatic turnover of proliferation and cell death compromises these manipulations as
physiologically-relevant models.
Another distinction between developmentally and adult generated cells in the adult brain
is the expression of immature markers, such as nestin. Recent technical developments allow the
genetic ablation of adult born neurons, a more targeted approach when compared to irradiation
and pharmachological agents. Ablation studies using transgenic approaches kill cells at the
immature nestin expressing stage (Saxe et al., 2006; Dupret et al., 2008; Deng et al., 2009;
Snyder et al., 2011; Wei et al., 2011) or at the start of neuronal differentiation, such as at the
neuron-specific enolase 2 expressing stage (Imayoshi et al., 2008). These studies have two main
strengths: (1) they are more specific than pharmacological and irradiation manipulations, and (2)
they are inducible, therefore excluding embryogenesis-related effects previously unavoidable in
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transgenic methods of neurogenesis decrease. Interestingly, the nestin-TK transgenic approach
also has the advantage of being reversible (Deng et al., 2009).
Genetic manipulations of adult neurogenesis represented a large technical advance in the
field, but also have limitations. These include side effects of the drugs administered to induce
trangene expression, in particular ganciclovir (Biron, 2006) and tamoxifen (Vogt et al., 2008)
(although these can be overcome by properly designed controls and/or longer recovery delays),
and lack of temporal control over the age of the cells/ablation, thus restricting the manipulations
to pretraining experimental designs (and the associated issues previously discussed).
Our double transgenic strategy enabled the dissociation between the ‗tag‘ and ‗ablate‘
stages of the manipulation, making it distinct from all previous adult neurogenesis loss of
function strategies in two ways: (1) it conferred temporal control over the ablation, so that a
posttraining design could take place, and (2) this permitted the ablation of mature adult generated
cells, which had never previously been done. This distinction allowed us to provide for the first
time direct evidence of the participation of aDGCs in memory retrieval, and, through the pre vs.
post comparison, offer some insight into some of the contradictory results found in the
pretraining literature. Additionally, the choice of a DTR approach for inducing apoptotic cell
death of aDGCs offered both specificity and low side effects. Our three levels of controls (pre vs.
posttraining dissociation, genotype control and DT vs. PBS control) further excluded any non-
specific effects of drugs, ablation or genotype in our behavioural results.
One limitation of our approach consisted of the simultaneous ablation of SVZ/OB
neurons. Our choice of tasks that were hippocampal dependent and don‘t rely on olfactory cues
(MWM, visual discrimination water maze) reduced concerns with the issue of SVZ
neurogenesis. Another constraint was the heterogeneity of cell ages of the affected population. In
spite of our efforts to target predominantly mature cells (which represented around 94% of our
tagged population), given the nature of our transgenic approach and our high recombination
efficiency, a high proportion of immature cells was also tagged (around 80-90% of the total
nestin or calretinin positive population). Although these cells corresponded to a minority within
the total tagged population (around 6%), we were still targeting most immature cells. Therefore,
our system is not able to determine whether immature cells play a role in supporting memories.
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Recently, two new techniques have emerged with promising applications to the adult
neurogenesis field: optogenetics and designer receptor exclusively activated by designer drug
(DREADD) receptors. These allow for selective silencing of a specific neuronal population,
representing a step forward from the killing-type approaches previously available. Chapter 7
includes an in depth discussion of these new techniques and their application to adult generated
neurons.
6.6 The unbearable lightness of inconsistencies2
6.6.1 In the hippocampus
Loss of function studies of adult hippocampal neurogenesis have yielded mixed results,
with some finding no effect (Shors et al., 2002; Madsen et al., 2003; Raber et al., 2004; Meshi et
al., 2006; Saxe et al., 2006; Dupret et al., 2008; Zhang et al., 2008; Deng et al., 2009; Drew et al.,
2010), and others finding impairment in memory task performance (Saxe et al., 2006; Snyder et
al., 2005; Winocur et al., 2006; Dupret et al., 2008; Imayoshi et al., 2008; Warner-Schmidt et al.,
2008; Zhang et al., 2008; Deng et al., 2009; Garthe et al., 2009; Hernández-Rabaza et al., 2009;
Ko et al., 2009; Snyder et al., 2009a; Drew et al., 2010; Denny et al., 2011).
Reconciling these findings is a hard task, but we can start by enumerating the elements
that vary among them, which include ablation technique, degree of ablation, age of the cells
affected, animal species (and strain) and behavioural protocol; and what they have in common:
they are all pre-training interventions. The last topic has already been discussed in length (see
section 6.1). The following paragraphs review other factors possibly underlying the
contradictions found in this literature.
2 Reference to Milan Kundera‘s ―The Unbearable Lightness of Being‖, 1984
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The mixture of strategies used to ablate neurogenesis in these studies include
pharmacological treatment (Shors et al., 2002; Garthe et al., 2009), X-ray irradiation (Madsen et
al., 2003; Raber et al., 2004; Meshi et al., 2006; Saxe et al., 2006; Winocur et al., 2006; Warner-
Schmidt et al., 2008; Hernández-Rabaza et al., 2009; Ko et al., 2009; Snyder et al., 2009a), and
transgenic mice (Saxe et al., 2006; Zhang et al., 2008; Dupret et al., 2008; Deng et al., 2009).
Lack of specificity and side effects in the pharmacological and irradiation approaches and effects
of compensation in the transgenic studies could contribute to the contradictory findings (see
previous section for a detailed discussion).
Irrespective of the ablation method, the efficiency of that ablation is likely to influence its
behavioural outcome. In fact, dose-related effects of neurogenesis ablation on behavior have
been reported, with only larger ablations leading to behavioural deficits (Shors et al., 2002; Ko et
al., 2009). Notably, the age of the animal at the time of ablation is a determining factor: given
the well known decay of neurogenesis levels with age, an effect is more likely to be seen in
younger animals due to their larger basal neurogenesis levels (Kuhn et al., 1996).
Furthermore, evidence suggests that the difference in the age of the cells affected/spared
in these manipulations could account for some of the mixed results, with the possibility that
immature cells exert unique contributions to memory processing (Shors et al., 2002; Snyder et
al., 2005; Deng et al., 2009; Marín-Burgin et al., 2012; Nakashiba et al., 2012). Interestingly,
abrupt differentiation induced by PC3 expression led to a deficit in CFC and MWM, even when
induced after training (Farioli-Vecchioli et al., 2008, 2009). Together, these reports accentuate a
possible role for 3-4 week old cells in memory processing, which deserves deeper and careful
exploration. Particularly, it is necessary to establish that it is the immature cells themselves that
are supporting the memories, as opposed to a memory impairment caused by disruption in the
homeostatic balance of neurogenesis.
Animal species is another variable in neurogenesis ablation studies, with some studies
done with rats and other studies done with mice. Snyder and colleagues performed a systematic
comparison between rats and mice on a series of common neurogenesis measurements, from
cellular to behavioral (Snyder et al., 2009a). Overall, they found a higher tendency to see a
behavioural effect of neurogenesis reduction in rats compared to mice, possibly due to a greater
functional representation of aDGCs in that species (Snyder et al., 2009a). Also, when dealing
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with mice, large variations in neurogenesis levels have been shown among mouse strains
(Kempermann et al., 1997b), which could also contribute to differences found in behaviour
following ablation.
Behavioural protocol is also likely to influence whether performance impairments are
observed after neurogenesis ablation. As has been demonstrated by Drew and colleagues, who
examined the impact of X-ray mediated adult neurogenesis ablation in a series of design
variations commonly used for fear conditioning, certain experimental designs seem to be more
sensitive in revealing disruption following ablation of neurogenesis (Drew et al., 2010). Since the
number of papers reporting a deficit in fear conditioning is higher than in the MWM, it would be
interesting to know, from a similar systematic comparison between memory tasks commonly
used in these studies, which behavioural tasks are more sensitive to neurogenesis ablation.
The last few years have brought on a different trend in the loss of function studies of
adult hippocampal neurogenesis. Instead of piling on conflicting reports, a couple of research
groups have tried to tackle factors that could help make sense of that literature (Snyder et al.,
2009a; Drew et al., 2010). We believe our study also contributes to that effort and provides a
technical step forward in directly assessing the role of aDGCs in memory retention. Hopefully,
combining critical analysis of the literature with new technologies (see previous section) will
ease the journey of elucidation of the physiological function of aDGCs into fruitful and
comprehensive research.
6.6.2 In the olfactory system
Loss of function studies in the adult olfactory neurogenesis literature are fewer than in the
hippocampus, but also comprise contradictory findings. A prominent (and confusing) feature of
the olfactory neurogenesis loss of function literature is that, in addition to the factors that vary
among studies of hippocampal neurogenesis (pre-training design, ablation method, size of the
ablation, age of the cells affected, behavioural protocol), the myriad of behavioural tasks is larger
than that used in hippocampal studies, and often the cognitive interpretation of the task varies
between research groups.
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Variables such as ablation method, size and pretraining designs have already been
discussed at length in the hippocampal context, and can be directly translated to the olfactory
literature. Thus, this discussion focuses primarily on the issues of behavioural protocol
(comprising categories of olfactory function, behavioural task design and interpretation) and age
of the cells affected by the manipulation, given their particular resonance in the olfactory
context.
Overall, in spite of one study not finding an effect (Imayoshi et al., 2008), most studies
find deficits in olfactory function following neurogenesis ablation (Breton-Provencher et al.,
2009; Lazarini et al., 2009; Moreno et al., 2009; Sultan et al., 2010). A first step when
interpreting these studies is to make a distinction between odour memory and odour
discrimination. Odour memory relates to the animal‘s ability to remember a given scent and/or to
associate it with reward or punishment (after a short or long delay), and odour discrimination
pertains to the ability to perceptually distinguish between odours. While most of these studies see
a deficit in a form of odour memory (Breton-Provencher et al., 2009; Lazarini et al., 2009; Sultan
et al., 2010), only one sees impairment in odour discrimination (Moreno et al., 2009).
These adult olfactory neurogenesis studies use different behavioural tasks that vary in
nature (associative vs non-associative), degree of training and level of difficulty. For instance,
odour discrimination tasks vary from a simple cross-habituation task (Gheusi et al., 2000; Bath et
al., 2008; Lazarini et al., 2009; Moreno et al., 2009) to associative tasks involving digging
(Imayoshi et al., 2008; Breton-Provencher et al., 2009; Lazarini et al., 2009; Sultan et al., 2010),
licking go/no-go tasks (Lazarini et al., 2009; Mouret et al., 2009), or mixtures in drinking water
(Enwere et al., 2004; Kim et al., 2007). Importantly, the degree of dependency on higher order
structures such as the piriform and orbitofrontal cortices in these tasks is not known, which could
be crucial in influencing behavioural outcome after neurogenesis reduction.
An additional level of complexity is the fact that the same behavioural task is often
interpreted differently depending on the research group. For instance, a habituation-cross
habituation task is used as a measure of olfactory discrimination by the Lledo group (Gheusi et
al., 2000; Lazarini et al., 2009) and of olfactory perceptual learning by the Didier/Mandairon
group (Moreno et al., 2009). Additionally, within a same category, i.e. odour memory,
completely different tasks are used to measure short and long-term memory. Whereas short term
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memory is measured through a simple odour habituation task, long-term odour memory is often
assessed by an associative olfactory discrimination task, rendering the interpretation of these
results difficult. One such example is the study by Breton-Provencher and colleagues, that
reports impaired short term memory but no deficit in long-term memory (Breton-Provencher et
al., 2009). This seems like an oxymoron, otherwise how could a memory be present seven days
after training if it is lost after an hour?
Mandairon and colleagues recently proposed an explanation of these discrepancies by
classifying associative digging tasks into either operant (Lazarini et al., 2009; Sultan et al., 2010)
or non-operant (Imayoshi et al., 2008; Breton-Provencher et al., 2009, present study) versions,
and finding that only the first version of the task led to an increase in survival of adult generated
olfactory interneurons (Mandairon et al., 2011). This argument, however, has theoretical
weaknesses. First, both tasks involve digging over an odour to retrieve a reward, the only
difference being that the first version requires more digging than the second version. According
to Thorndike‘s law of effect, instrumental learning implies a change in behaviour (digging on the
correct odour) due to a reinforcement (sugar pellet) (see section 1.1.1), making it hard to justify
how the second version could be non-operant. Second, the amount of training is not comparable
between the two tasks: although the number of trials is the same between tasks, there is a
difference in the number of exposures to the reinforced odour. The first version has 4 reinforced
trials per day, whereas the second version only has 2 reinforced trials per day (Mandairon et al.,
2011). This surplus of reinforced trials may have a greater effect on cell survival.
Given all this diversity in tasks and their interpretation, it is very challenging to translate
conclusions from one study to another, especially between different research groups. This was an
incentive when designing our study, in which we sought to manipulate factors within the same
task, so that our conclusions could cease to be contingent on the task in hand and become about
the cellular mechanisms behind it.
As with the hippocampal neurogenesis studies, the cell population targeted in the
manipulation should be taken into account when interpreting results across studies. Adult
generated olfactory interneurons display a critical period of heightened plasticity at around 2
weeks of age (Nissant et al., 2009). Olfactory granule cells 2-3 weeks of age also seem to be
preferentially activated in response to a novel odour when compared to pre-existing cells
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(Magavi et al., 2005). Hence, ablation strategies differentially targeting progenitors/transit
amplifying cells (Breton-Provencher et al., 2009; Lazarini et al., 2009; Moreno et al., 2009;
Valley et al., 2009; Sultan et al., 2010) versus maturing cells (Imayoshi et al., 2008) could lead to
different behavioural phenotypes.
Belnoue and colleagues reported a task-dependent recruitment of cells at particular
maturation stages: whereas simple odour exposure led to preferential recruitment (measured by
Fos expression) of 2-week old cells, olfactory discrimination training led to recruitment of 5-9
week old cells (Belnoue et al., 2011). This dissociation might underlie some of the conflicting
findings between odour memory (many of which use simple odour exposure tasks) and
discrimination.
Our results have shown that postraining ablation of 3 week old olfactory interneurons
impairs performance in an associative odour discrimination task. It is possible that at 3 weeks
granule cells are already preferentially recruited to the trace, since Belnoue and colleagues did
not examine recruitment at any time point between 2 and 5-9 weeks (Belnoue et al., 2011).
Given the flexibility of our experimental design we intend to assess other time points to establish
whether we see a similar critical period for functional integration of these interneurons.
Particularly, we want to explore the age of 10 days, when neuroblasts have reached the OB and
finished tangential migration, but lack spines, and 8 weeks, when cells are mostly similar to their
developmentally generated counterparts.
6.7 What are aDGCs (and DGCs) really good for?
While several papers point towards a role for the DG in pattern separation, and
computational models predict a contribution of aDGCs to the process (see section 1.3.2.3.1),
Clelland and colleagues were the first to apply pattern separation-type methodology within
neurogenesis ablation studies. Using two spatial tasks, one using the radial arm maze and the
other using the touchscreen, they showed that animals with reduced neurogenesis (through
irradiation or lentivirus) displayed specific deficits in distinguishing between proximal stimuli,
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which did not occur when stimuli had a higher degree of separation (Clelland et al., 2009). The
authors interpreted this as a deficit in spatial pattern separation.
Sahay and colleagues devised a transgenic model with genetic deletion of the pro-
apoptotic gene Bax exclusively in adult progenitors (iBax mice), which leads to a decrease in cell
death and an overall increase in neurogenesis (Sahay et al., 2011a). This was a method to
augment neurogenesis without the non-specific effects on mood found with extrinsic regulators
such as running (Sahay et al., 2011a). Increased neurogenesis in the iBax mice led to improved
performance in a contextual discrimination task, to which the authors also conferred pattern
separation-type properties (Sahay et al., 2011a).
Similarly, Tronel and colleagues showed that inducible ablation of neurogenesis (through
overexpression of Bax in neural precursors, as in Dupret et al., 2008) led to a deficit in
contextual discrimination in the same task (Tronel et al., 2012), which the authors argued
reinforced the role aDGCs play in pattern separation and in decreasing interference (Tronel et al.,
2012) as has been predicted by some computational models (Wiskott et al., 2006). Interestingly,
it has been reported that ablation of neurogenesis leads to an increase in the amplitude of
spontaneous gamma frequency bursts and in the synchronization of firing to these bursts
(Lacefield et al., 2012), thus implicating aDGCs in modulation of network inhibition, which
could underlie these pattern separation-type functions.
Recently, Nakashiba and colleagues found intriguing results. Using a transgenic strategy
in which MFs of all DGCs older than 3 weeks of age were silenced, they saw a facilitation of the
contextual discrimination task used by Sahay and colleagues and a deficit in a version of the WM
in which some distal cues were missing during the probe (referred to as a pattern completion
task) (Nakashiba et al., 2012). The authors concluded that cells younger than 3 weeks have a
primary role in pattern separation, whereas mature neurons have a greater role in pattern
completion (Nakashiba et al., 2012). They argued that because old DGCs have been involved in
encoding memories for longer they have accumulated more overlapping representations, and thus
are more efficient at pattern completion, whereas young DGCs with no memory encoding
experience are more effective at pattern separating (Nakashiba et al., 2012).
Our findings are also in general agreement with those described in these studies.
Posttraining ablation of aDGCs led to a contextual discrimination deficit that shares many
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characteristics of the methodology used by the groups of Sahay and Tronel (Sahay et al., 2011a;
Tronel et al., 2012), and our visual discrimination water maze relies on the discrimination
between two very similar cues (or patterns), which may be interpreted as a pattern-separation-
like task.
This recent surge of studies has turned the role of aDGCs in pattern separation into quite
a consensus in the field. However, some caution is due when drawing big conclusions from a
handful of studies that use quite different behavioural tasks. The idea that the DG has pattern
separation potential was derived largely from modeling work and DG anatomical and functional
characteristics (such as MF anatomy and sparse coding) (see sections 1.2.2.4 and 1.3.2.3.1).
However, the behavioural translation of pattern separation is not that straightforward.
Behaviourally, pattern separation is broadly interpreted as the ability to distinguish
between two similar inputs. Two main avenues of behavioural tasks have currently become the
standard: a fear conditioning task in which animals learn to discriminate between two similar
contexts through several sessions of daily shocks received exclusively in one of the contexts
(McHugh et al., 2007; Sahay et al., 2011), and a battery of ‗spatial pattern separation tasks‘,
ranging from an arena in which objects are moved (Gilbert et al., 2001), to radial arm maze and
touchscreen based tasks (Clelland et al., 2009). The basic premise for the latter experiments is
that animals with deficits in pattern separation will be impaired in instances in which objects are
close together, but have no difficulty in discerning between objects far apart.
A major issue arises regarding the interpretation of these tasks. Although rationally akin
to the concept of pattern separation, there is currently no evidence that pattern separation-like
cellular mechanisms actually underlie the resolution of any of these behavioural tasks. In fact,
their behavioural phenotypes can be explained through different mechanisms. In a recent critique
of this literature, Aimone and colleagues point out that, although consistent with a pattern
separation phenotype, the fear conditioning and spatial pattern separation tasks also involve
elements of inhibitory learning and working memory, not to mention that it is impossible to rule
out that different neural circuits are recruited depending on the degree of dissimilarity between
the input patterns (Aimone et al., 2011). Two additional confounds should be taken into
consideration: the stress generated by 9-17 days of daily shocks in the fear conditioning task, and
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the fact that varying the length of object separation in the spatial tasks could be simply an issue
of task difficulty.
Aimone and colleagues also emphasize that pattern separation is not an exclusive
function of the DG. In fact, the ability to encode similar inputs as distinct representations is a
basic feature of neural networks, one present in most brain circuits (Aimone et al., 2011).
Instead, they propose that a ‗memory resolution‘ type interpretation is more suited for these
studies, since most of these tasks depend on the animals comparing the present situation they
need to solve with their memory of a previous experience, which resonates with Gray and
McNaughton‘s theory of the hippocampus as a conflict solver (Gray and McNaughton, 2003).
Interestingly, a few papers have also proposed a function for aDGCs in memory
clearance and systems consolidation. In 2001, Feng and colleagues proposed that aDGCs are
involved in forgetting or memory clearance, from an experiment with post-learning EE. They
saw that in a fear conditioning probe after EE, wild type mice froze less compared to transgenic
mice with a deficit in EE-driven neurogenesis (Feng et al., 2001), and postulated that increasing
neurogenesis through EE after learning accelerates memory clearance, making the memory
weaker. This finding is perhaps echoed in Meltzer and colleagues‘ computational model, which
shows that excess neurogenesis could be detrimental to pre-existing memories (Meltzer et al.,
2005).
Consistent with this idea, Kitamura and colleagues implicated aDGCs in systems
consolidation, in modulating the hippocampal dependent period of fear memories (Kitamura et
al., 2009). In their paper, reduction of neurogenesis, through irradiation or a transgenic mouse
with suppressed neurogenesis, extended the period in which hippocampal inactivation would
lead to amnesia. In contrast, running turned retrieval hippocampus-independent sooner,
accelerating the process of systems consolidation (Kitamura et al., 2009). Together, these papers
suggest that the addition of new neurons in the hippocampus may interfere with recently
acquired memories and facilitate their exodus from the hippocampus to cortical structures.
Furthermore, an interesting way of looking at these pattern separation and systems
consolidation/memory clearance studies is to consider the possibility that they represent
complementary roles of aDGCs within hippocampal circuits. It is possible that aDGC addition
initially disturbs previously acquired memories but, once these neurons survive and incorporate
129
into the circuit, they serve as decorrelators and contribute to solving discrimination and pattern
separation-type situations. Presently it seems one thing is clear, that studies of aDGC function in
a circuit level would prove extremely insightful to both pattern separation and systems
consolidation debates.
6.8 What are aOGCs (and OGCs) really good for?
Single unit recordings of OB (mitral/tufted cells) and piriform cortex cells have shown
that while OB neurons optimally decorrelate mixtures of odorants with very small variations,
piriform cortex ensembles collapse these similar mixtures into the same representation, in a
pattern separation/pattern completion function similar to that of the DG/CA3 areas (Barnes et al.,
2008; Wilson, 2009). Olfactory interneuron inhibition of mitral/tufted cells contributes to this
input separation (Yokoi et al., 1995; Stopfer et al., 1997; Luo et al., 2001; Schoppa and Urban,
2003; Abraham et al., 2010).
Interestingly, olfactory discrimination interferes with aOGC cell survival (Alonso et al.,
2006; Mandairon et al., 2006; Mouret et al., 2008), and characteristics of young aOGCs [their
hyperplasticity (Nissant et al., 2009) and increased response to novel odours (Magavi et al.,
2005)] are consistent with a role in facilitating pattern separation. Altogether, this evidence
points towards a function of OGCs (and aOGCs) in olfactory discrimination, and has led
researchers to speculate that pattern separation might be a general function of adult neurogenesis,
given the similarities between the two main circuits in which it exists (i.e. OB and DG)(Sahay et
al., 2011b).
However, despite the strong indications of the contribution of olfactory interneurons to
olfactory discrimination, very few studies that manipulate adult neurogenesis see a
discrimination deficit. Lazarini and colleagues suggested that olfactory discrimination is
impaired only by manipulations that disrupt neurogenesis from embryogenesis onward (e.g.
Gheusi et al., 2000; Enwere et al., 2004; Bath et al., 2008), and thus may not be mediated by
adult-generated neurons (Lazarini and Lledo, 2011). Still, although developmental perturbations
130
could definitely play a role in these studies, this cannot explain the impairment in fine
discrimination observed during normal aging (Enwere et al., 2004) or in the facilitation of
olfactory discrimination following increased neurogenesis during adulthood (through odour
enrichment) (Moreno et al., 2009).
Most deficits following neurogenesis ablation are observed in some category of odour
memory (Breton-Provencher et al., 2009; Lazarini et al., 2009; Moreno et al., 2009; Sultan et al.,
2010). Although there is evidence correlating bulbar network activity (and olfactory
interneurons) with odour representation/olfactory perception (Mandairon and Linster, 2009), it is
less clear how olfactory interneuron function could affect odour memory per se. Importantly, it is
unclear which brain regions (and their hierarchy) are critically involved in the olfactory
perception and olfactory conciousness functions necessary for establishing short and long-term
odour memories (Li et al., 2010; Wilson and Sullivan, 2011). Without a good understanding of
the circuit underlying odour memory it is challenging to interpret the impact of neurogenesis
ablation in certain behavioural tasks (see section 6.4.2).
In the case of our study, it is not clear how posttraining ablation of adult olfactory
interneurons impairs an associative odour memory. Our prediction is that the loss of these
interneurons alters the representation of that odour, losing the link between odour and reward
likely stored at higher order structures. Presently, however, we have no concrete evidence that
this is the case. Hopefully, further elucidation of the olfactory network as a whole will soon help
lay the groundwork for future adult neurogenesis queries.
It is possible that aOGCs are necessary for olfactory discrimination, and adult born
neurons for pattern separation across systems. Nevertheless, as tempting as general theories of
adult neurogenesis function might be, caution must always be taken not to overstate conclusions,
and not to fall too in love with a hypothesis. As with the hippocampus, multiple lines of
definitive evidence must emerge to establish the importance of aOGCs in olfactory pattern
separation, and especially to prove that this is not just a general function of OGCs. Importantly,
even if aOGCs (and aDGCs) turn out to be just the same as any developmentally generated cell,
their renewal in the adult brain is in itself unique, and their presence can still open different
therapeutic avenues.
131
Chapter 7 Future Directions
In the studies described in this thesis we used a new transgenic approach to explore the
role of adult generated neurons in hippocampal and olfactory memory expression. This tag and
ablate strategy allowed, for the first time, to selectively ablate adult generated neurons after
memory encoding, and represents a more direct way of looking at adult born neuron contribution
to memory expression.
Nevertheless, although our current transgenic method represents a step forward in terms
of specificity and reduction of side effects, killing neurons, even through apoptosis, recruits and
activates phagocytic cells, whose response is still quite disruptive to the system. Ideally, neurons
could be reversibly silenced without inflammation. Two recent technological developments offer
promising new options for loss of function studies: optogenetics and designer receptor
exclusively activated by designer drug (DREADD) receptors.
Optogenetic technology combines genetic engeneering and light to manipulate neural
function in behaving organisms with exquisite spatial and temporal control. The first
demonstration of this was done in hippocampal neurons with the light-responsive channel
channelrhodopsin-2 (ChR2) (Boyden et al., 2005). ChR2 is a sensory photoreceptor derived
from the green algae Chlamydomonas reinhardtii (Nagel et al., 2003). ChR2 contains a
chromophore which, upon absorption of blue light, undergoes a conformational change that
causes the transmembrane channel to open, an influx of sodium and consequent neuronal
depolarization and generation of action potentials (Nagel et al., 2003; Boyden et al., 2005).
Since this demonstration of light-induced control of neuronal spiking with millisecond
precision, several optogenes were discovered and optimized, now comprising a vast toolbox
varying in wavelength, ion conductance and speed (Gradinaru et al., 2010; Fenno et al., 2011).
One such example is Archaerhodopsin-3 (Arch), an outward proton pump derived from
Halorubrum sodomense. Yellow light shone onto Arch expressing neurons activates proton
pumps, rapidly hyperpolarizing, or silencing, neurons with very high efficiency and a very short
recovery time (Chow et al., 2010). Importantly, these are completely reversible manipulations.
132
Optogenetic manipulations, therefore, allow for gain and loss of function approaches, even
within the same neuronal population.
Currently there are two paths to targeting adult born neurons with optogenes: retroviral
vectors expressing the optogene of choice, or transgenic mice expressing inducible optogenes
that can be activated by CRE recombinase activity (driven by progenitor specific promoters).
Once the optogene is expressed, specific neuronal activation or inactivation is achieved through
light pulses delivered by surgically implanted optrodes (Aravanis et al., 2007). The strongest
advantages of an optogenetic approach are its temporal control, reversibility and the ability to
assess the function of a subset of neurons online, as a behavior is occurring, which renders it
potentially more disruptive. Still, this strategy is restricted by the spread of the light beam and
incurs in significan tissue damage from optrode implantation.
Unfortunately, these delivery methods still incur some of the same limitations as earlier
transgenic methods: retroviral delivery is restricted in terms of total number of cells infected, and
a nestin-CREERT2
-type transgenic approach, although targeting more cells, lacks the control over
the age of cells affected. Still, the application of optogenetic technology to the adult neurogenesis
field should yield very interesting results. In effect, we have recently had the opportunity to
collaborate with Dr. Shaoyu Ge‘s group in Stony Brook, NY, and do just that (the paper resulting
from that collaboration is in appendix 1).
Dr. Ge‘s group developed a protocol for high titer retrovirus production to induce Arch
expression specifically in aDGCs. After an initial eletrophysiological characterization of the
optogenetic manipulation of aDGCs we were able to silence these cells online as animals were
performing a behavioural probe. Similar to our results using the DTR system, we saw that
silencing of a small subset of aDGCs (around a thousand cells) after training led to memory
degradation in the MWM and CFC (Gu et al., unpublished data; appendix 1). Interestingly, this
effect was more pronounced when cells were 4 weeks of age (Gu et al., unpublished data;
appendix 1), consistent with the view that these immature cells are functionally distinct from
both developmentally generated and mature adult generated DGCs. Very recently, a paper by the
Lledo group applied this technology to the SVZ/OB system. They showed that optogenetic
activation of aOGCs (using channelrhodopsin-2) facilitated learning of a difficult (but not an
easy) olfactory associative memory task (Alonso et al., 2012). Interestingly, light-induced
133
activation of these cells did not influence olfactory discrimination acuity (Alonso et al., 2012).
The conclusions in that study bear close resemblance to ours, and it will be exciting to see the
effects of a loss of function study using the same technology.
Another interesting new tool that could help in that effort came from Bryan Roth‘s group,
which generated a family of altered G-protein coupled receptors (GPCRs) designed to lose
responsivity to their original agonist and be activated exclusively by a pharmachologically inert
synthetic compound, clozapine-N-oxide (CNO) (Armbruster et al., 2007). This line of altered
muscarinic receptors is referred to as designer receptors activated by designer drug (DREADD),
their main advantages being the ability to silence or depolarize neurons in response to CNO in a
remote and non-invasive manner (Armbruster et al., 2007; Alexander et al., 2009), and, in double
transgenic mice with a tetracycline transactivator system (Mayford et al., 1996), reversibly
(Alexander et al., 2009).
Although lacking the extreme temporal precision of optogenetic approaches, this
technique allows for targeting brain areas inaccessible to optrodes (deeper areas of the brain),
with no tissue damage and not limited by light diffusion. Recently, this technology was coupled
to genetic tagging of c-fos expressing neurons (Reijimers et al., 2007) to specifically re-activate
tagged neurons that were engaged during encoding of a memory trace (Garner et al., 2012, see
discussion above).
Both these techniques could be applied to investigate key remaining questions in the
field. For instance, the question of whether aDGCs are special, or different from developmentally
generated DGCs. Differential silencing of adult vs. developmental populations could be achieved
through retroviral infection of optogenes activated by different wavelengths (one injected at P10
and another during adulthood). Alternatively, application of the technique used by Garner and
colleagues to adult born neurons (using nestin or DCX instead of CamKII as a promoter) could
be insightful in exploring functional integration of aDGCs.
Another important question is that of whether immature aOGCs (and aDGCs) are
involved in memory processing. Tagging and silencing through a retro-optogenetic approach
offers more control over the age of the targeted cells, and our experiments suggest that the small
134
number of cells infected is nevertheless enough to impact memory. Still, before we have access
to that technology in house, we intent to complement our olfactory data with a few experiments.
The data shown in chapter 5 indicates that 3 week old olfactory interneurons play a role
in olfactory memory expression. With our two-step tag and ablate strategy we can also
manipulate the timing of the ablation, i.e. vary the age of the cells at the time of the ablation. The
morphological, eletrophysiological and chemical sequence of steps taken by adult born cells as
they mature have been extensively studied, and differences in plasticity levels during this process
have been hypothesized to underlie function. We intend to examine the impact of ablating cells
at different maturation stages in our associative memory task. Particularly, we are interested in
looking at 8 week old cells, a time point in which most of the heightened plasticity has been lost
(Nissant et al., 2009), and 10 days, an age in which the cells have arrived at the bulb but still lack
spines (Petreanu and Alvarez-Buylla, 2002).
135
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Appendix 1
A critical time window for adult-born dentate granule cells in hippocampal function
revealed by studies of optically-controlled newborn neurons
Yan Gu1, Maithe Arruda-Carvalho
3,4, Jia Wang
1, Stephen Janoschka
1,2, Sheena Josselyn
3-5, Paul
Frankland3-5,*
and Shaoyu Ge1,2,*
1Department of Neurobiology and Behavior, SUNY at Stony Brook, Stony Brook, NY 11794
2Program in Neuroscience, SUNY at Stony Brook, Stony Brook, NY 11794
3Program in Neurosciences and Mental Health, Hospital for Sick Children, 555 University Ave,
Toronto, Ontario, Canada, M5G 1X8
4Institute of Medical Science,
University of Toronto, Toronto, Ontario, Canada, M5S 1A8
5Department of Physiology, University of Toronto, Toronto, Ontario, Canada, M5S 1A8
*Correspondence can be addressed to:
Shaoyu Ge Ph.D.
Department of Neurobiology and Behavior
SUNY at Stony Brook
Stony Brook, NY 11794, USA
E-mail: [email protected]
Tel: 631-632-8799
Fax: 631-632-6661
Or
Paul Frankland Ph.D.
Hospital for Sick Children
Neurosciences & Mental Health
Hospital for Sick Children
Toronto, Ontario, Canada, M5G 1X8
E-mail: [email protected]
Tel: 416-813-7654 x1823
Fax: 416-813-7717
218
Abstract
Neurogenesis persists into adulthood in the hippocampus. Accumulating evidence
suggests that global depletion of adult neurogenesis influences hippocampal function and
the timing of the depletion impacts the severity of the observed deficits. However,
behavioral roles of adult-born neurons during their circuit integration, specifically during
the establishment of projections to CA3 pyramidal neurons, remain largely unknown. Here
we combined retroviral and optogenetic approaches to birth-date and reversibly excite or
inhibit a group of adult-born neurons. We show that young adult-born neurons form
functional synapses on target CA3 pyramidal neurons as early as 2 weeks after birth, and
that this projection to the CA3 area becomes stable by 4 weeks in age. Newborn neurons at
this age exhibit enhanced plasticity compared to other stages. Strikingly, we found that
reversibly silencing this cohort of ~4 week-old cells after training, but not cells of other
ages, substantially disrupted retrieval of hippocampus-dependent memory. Our results
identify a restricted time window for adult-born neurons during which time they exhibit an
essential role in hippocampal memory retrieval.
Introduction
The adult hippocampus continues to give rise to several thousand new dentate granule
cells each day and less than half of them survive 1-3
. Since the discovery of neurogenesis in the
adult brain, the question of how newborn neurons contribute to hippocampal function has been
raised. The hippocampus is important for many forms of memory 4-7
, and accumulating evidence
from studies using global perturbation or ablation of adult hippocampal neurogenesis has
revealed deficits in some forms of hippocampal memory in rodents 8-12
. As the morphological
and physiological phenotypes of adult-born cells change dramatically as they mature, they may
play distinct roles at different stages following integration into hippocampal circuits.
Accordingly, while manipulations of adult neurogenesis may disrupt hippocampal memory
function, it is not clear whether the observed memory deficits are due to loss of immature vs.
mature adult-born neurons or, more simply, due to a global disruption of neurogenesis. Some
recent work from our and several other groups shows that surviving adult-born dentate granule
(DG) cells extend dendrites and receive functional input from the existing neural circuits as early
as 2 weeks after birth 13-17
. In contrast to many studies on input synapses, little is known about
the establishment of functional projections of adult-born DG cells to pyramidal neurons in CA3.
219
Anatomical studies have established that young newborn DG cells gradually extend axonal fibers
into the CA3 area. Two to three weeks after birth, terminals of these axons form bouton-like
structures similar to mature granule cells 18-21
, suggesting that they may form functional
connections 3. A recent study demonstrated that mature (two months old) newborn neurons
exhibit synaptic responses in the CA3 area 19
. However, the precise timing for functional output
synapse formation and maturation remains unknown.
We previously found that input (dendritic) synapses of adult-born neurons show
enhanced plasticity between 4-6 weeks after birth compared to other stages 22
, during which time
they presumably also exhibit heightened intrinsic excitability 16,23
. This coincides with the timing
when newborn neurons are recruited into adult neural circuits mediating behavior 24-27
. These
findings suggest that a cohort of young adult-born neurons of similar age may form a
hypersensitive unit that preferentially responds to stimuli during hippocampal memory
formation. A related interesting question is whether output synapses, if formed and functional,
also exhibit heightened plasticity.
Combining retroviral birth-dating and gene delivery 13-14
with optogenetic stimulation28
,
here we examine the behavioral roles of adult-born neurons during their output circuit
development. We found that adult-born DG cells establish functional synapses with CA3
pyramidal neurons as early as 2 weeks after birth and synaptic responses remain stable by 4
weeks in age. Fully established output synapses of adult-born neurons exhibit enhanced plasticity
at ~4 weeks after birth. Importantly, optogenetic silencing of a cohort of 4 but not 2 or 8 weeks
old newborn neurons substantially impacted the retrieval of hippocampal dependent memory
following the completion of training. These data characterize the development of output circuit
function for adult-born DG cells, revealing a precise time window where newborn neurons
exhibit enhanced plasticity at CA3 synapses and play a critical role in processing hippocampal
memories.
Results
The development of functional output synapses of adult-born neurons
To examine a role of adult-born neurons in hippocampal function during their circuit
integration, we first determined the timing for newborn neurons to establish functional
projections to CA3 pyramidal neurons. We previously found that adult-born DG cells start to
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receive functional glutamatergic inputs as early as 2 weeks after birth 14
. Anatomical studies
show that adult-born DG cells gradually form synapses on CA3 neurons 18-21
. However, because
of the sparse targeting of DG cells and the difficulty in electrically stimulating a population of
newborn neurons simultaneously, little is known about the development of functional synaptic
projections of adult-born neurons within the hippocampal trisynaptic circuit 3. Here, we elected
to use an optogenetic method to excite a group of adult-born DG cells simultaneously to
determine the development of functional output circuit in the CA3 area 19,28
. We constructed a
retroviral vector expressing EGFP-tagged Channelrhodopsin 2 (ChR2-EGFP), a gene encoding a
light-sensitive channel 28-29
, to birth-date and specifically express ChR2-EGFP in adult-born
hippocampal neurons 13-14,19
. ChR2-EGFP retroviruses were microinjected into the hilus of the
DG in adult mice and acute brain sections were prepared 1-8 weeks post infection (wpi) using
previously described methods (Supplememtary Fig. 1; Fig. 1a; Methods; 14
). As expected, ChR2-
EGFP was specifically expressed in newborn neurons (Supplementary Fig. 2), and brief, 5 ms
pulses of blue light reliably induced action potentials in infected DG cells but not in non-infected
neighbors (Fig. 1b), indicating that this population of cells could be optically controlled. Because
infected cells were not illuminated during development, and ChR2 remained silent, we did not
observe changes in intrinsic properties in newborn neurons expressing ChR2 at different ages
compared to those expressing EGFP only (Supplementary Table 1), consistent with previous
findings where optogenes have been expressed in other cell types 28
.
Next, we used whole-cell recording to examine postsynaptic currents in CA3 pyramidal
neurons while optically stimulating ChR2-EGFP positive mossy fibers of newborn DG cells
(Fig. 1c). Postsynaptic activity increased with the age of infected adult born DG cells (Fig. 1d).
At 1 wpi, a time-point when mossy fibers have not yet reached the CA3 region, no postsynaptic
responses were observed following optical stimulation. However, at 2 wpi and older (a stage
where mossy fibers have reached the CA3 region), stimulation produced excitatory postsynaptic
responses (EPSCs). Maximal responses were observed at 4 wpi (Fig. 1d, e). These optically
evoked EPSCs, with a latency of ~4ms, were blocked by an AMPA receptor antagonist (CNQX)
and metabotropic glutamate receptor agonists (L-AP4 and LY354740, specifically blocking
mossy fiber-CA3 synapses 30
), indicating a glutamatergic mono-synaptic response (Fig. 1f, g).
These results show young adult-born DG cells form functional synapses with CA3 target cells
which become stable around 4 weeks after birth. These current results, together with previous
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studies showing newborn neurons to be functionally innervated by entorhinal cortical projections
13-15, indicate that adult-born DG cells fully integrate into the hippocampal trisynaptic circuits by
~4 weeks of age.
Heightened plasticity of output synapses of young adult-born neurons
We next characterized functional properties of these output synapses. Plasticity, such as
long-term potentiation (LTP), has been considered as an essential functional property of a
synapse 31
. Accordingly we next examined synaptic plasticity of young adult-born DG cells in
the CA3 using a more physiological relevant, but milder induction paradigm, as previously
described 16,22
. To stimulate CA3 synapses of a group of adult-born neurons optically at high
frequency, we replaced the ChR2 construct with ChR2 variants ChETA-EYFP 32
and ChIEF-
dTomato 33
, which respond more reliably to high frequency optical stimulation.Because we
reserved dTomato for labeling adult-born neurons, we selected ChIEF-dTomato for the following
study. As expected, 3, 4 and 8 week-old adult-born DG cells expressing ChIEF responded
reliably to high frequency optical stimulation to their soma (Supplementary Fig. 3a, b).
Recordings from axonal boutons indicated that following optical stimulation action potentials
propagated reliably to the axonal terminals (Supplementary Fig. 3c, d). To assess global circuit
output of newborn neurons, we then implanted an optic fiber in the DG to deliver optical
stimulation and recorded field excitatory postsynaptic potentials (fEPSPs) in the CA3 region in
vivo (Fig. 2a; Supplementary Fig. 4a-c). fEPSPs were successfully induced by short pulses of
optical stimulation (Fig. 2b). Similar to postsynaptic activity in vitro (Fig. 1c), fEPSPs recorded
in vivo were blocked by local application of CNQX (Fig. 2b). As expected, high frequency
optical stimulation (~5 mW/mm2 intensity, 50Hz, 2s) evoked consistent fEPSPs (Fig. 2b).
Together with the reliable responses to theta-burst optical stimulation recorded from the soma or
axonal terminals of newborn neurons ( Supplementary Fig. 3) this result suggests that the
experimental system is sufficient for characterizing output synaptic plasticity of newborn dentate
granule cells using a theta burst optical induction paradigm (Supplementary Fig. 4d; 16,22,32-33
).
Therefore, we next delivered theta burst optical stimulation (TBS), and measured fEPSPs slope
before and after the TBS using methods previously described (Methods; 22
). We found that
optical TBS stimulation at 3 and 4 wpi induced LTP of fEPSPs in the CA3 area in nearly all
tested animals (Fig. 2c,d). When the same induction paradigm was used to induce LTP at 8 wpi,
only half of tested animals exhibited potentiation (Fig. 2c-d). Therefore, output synapses of
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adult-born DG cells at 4 wpi exhibit a lower induction threshold for LTP, sharing a similar
property to their input synapses as previously reported 16,22
. We then analyzed LTP amplitude at
3, 4, and 8 wpi, and found that robust LTP amplitude was maximal at4 weeks. Relatively
smaller LTP was observed in mice that were stimulated at 3 and 8 wpi (Fig. 2c, e). To determine
whether the reduced LTP at 8 wpi resulted from lack of plasticity in the axonal synapses of
newborn neurons around this age, we induced LTP in this circuit with stronger induction
paradigm, tetanic optical stimulation (50Hz, 2s). We performed whole cell patch clamp
recording from their target neurons (Supplementary Fig. 5a). After establishing stable whole cell
recordings in the CA3 area by optically stimulating mature newborn DG cells, we applied a
tetanic optical stimulation. As shown in Supplementary Fig. 5b, c, we recorded a sustained
potentiation in response after induction, suggesting the output synapses remain plastic but with
higher induction threshold. We further examined if stimulated young newborn with the tetanic
paradigm whether the heightened axonal plasticity could be still observed. We then did whole
cell recording on CA3 pyramidal cells while stimulating young newborn neurons with the tetanic
stimulation. We found a significantly higher level of LTP expression compared to that induced
from stimulating mature newborn neurons (Supplementary Fig. 5b, c, d), consistent with our
observation using theta-burst induction in Fig. 2. Our results here indicate that young newborn
neurons exhibit heightened plasticity that peaks ~4 wpi (Fig. 2e).
We next asked what might contribute to the heightened plasticity in young newborn
neurons. A recent study found that T-type Ca2+
channels generate isolated Ca2+
spikes and boost
fast Na+ action potential firings and facilitate dendritic synaptic plasticity in young, newborn
(but not mature) DG cells16
. According to previous studies 34,35
, the heightened activation by T-
type Ca2+ channel of young adult-born neurons should be able to efficiently propagate to axonal
terminals to regulate their output synaptic activity. We then examined whether the activity of T-
type Ca2+
channels contributed to the heightened plasticity. After establishing reliable recordings
from the animals at 3, 4 and 8 wpi, we blocked T-type Ca2+
channels with mibefradil, a specific
T-type Ca2+
channel blocker (Methods; 34
). Mibefradil showed no effect on the basal synaptic
transmission (Supplementary Fig. 6). Interestingly, theta burst optical stimulation failed to
induce an enhancement of synaptic transmission from mibefradil-treated animals 3 and 4 wpi
(Fig. 2e), at time-point at which we observed robust potentiation in control animals using the
same induction paradigm (Fig. 2e). In the animals at 8 wpi, the weaker LTP was unaffected by
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mibefradil application(Fig. 2e), suggesting the activity of T-type Ca2+
channels in young adult-
born DG cells likely plays an important role in the heightened axonal synaptic LTP. Together
with previous studies on intrinsic excitability and input synapses 16,22,35
, these results reveal that a
cohort of fully-integrated (~4 weeks old) young newborn DG cells have more excitable
membranes and enhanced input/output synaptic plasticity.
Reversible silencing a cohort of 4 weeks old adult-born neurons influences hippocampal
memory retrieval
Accumulating evidence suggests that the effectiveness of ablations of adult neurogenesis
depend on their timing3,9,11,12,27
. This suggests that as adult-born DG cells mature they may
assume distinct behavioral roles, and these distinct behavioral roles may coincide with changes
in their synaptic integration and plasticity (Fig. 2e). To test this hypothesis, we used optogenetic
stimulation to temporarily and reversibly silence groups of different aged adult-born neurons
during memory retrieval. We generated a retrovirus to express inhibitory optogenes,
Halorhodopsin (NpHR-EYFP; 28
) or archaerhodopsin-3 (Arch-EGFP; 36
). We found that both
NpHR and Arch could suppress the activity of newborn neurons when optically stimulated as
previously reported 28,36
. To maximize infection of adult-born neurons, we performed two
retroviral injections (spaced 10 h apart) per animal using a standard protocol as we previously
reported (Methods, 14
). We successfully labeled ~1700 newborn DG cells per animal at 4 weeks
after viral injection (Supplementary Table 2). The Arch expression in labeled adult-born DG
cells showed no observable effect on the development of newborn neurons as shown in
Supplementary Table 1. In acutely prepared brain sections, pulses of optical stimulation
specifically silenced Arch expressing adult-born DG cells, indicating that these neurons can be
reliably and reversibly inhibited by light (Fig. 3a)36
.
To examine the role of a group of newborn neurons in hippocampal memory we used a
hidden platform version of the water maze task, a well-established hippocampal-dependent task
37. We microinjected Arch retroviruses into the hilus of the hippocampus in adult mice, and
implanted customized optrodes to ensure sufficient light delivery into the dorsal hippocampus
bilaterally (Methods; Supplementary Fig. 7). At 4 wpi, mice were trained in the water maze with
optic fibers connected to an orange light source via an optic-rotatory joint half with light off (―no
light‖ group) and half with light on (―light‖ group) during training (Fig. 3b, Supplementary Fig
8a). Across the training trials, latencies to locate the hidden platform declined. There was no
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difference in escape latencies in control (no light) vs. inactivated (light) groups, indicating that
silencing this cohort of ~4 week-old adult-born DG cells does not interfere with task acquisition.
We then assessed the effect of silencing newborn neurons on memory retrieval. As
before, after microinjection of Arch or EGFP control retroviruses we implanted optrodes into the
dorsal hippocampus bilaterally. At ~4 wpi, mice were trained in the water maze with optic fibers
connected to an inactive light source (―no light ―condition) via an optic-rotatory joint, and the
mice learnt to locate the hidden platform (Fig. 3b-d). Following the completion of training,
spatial memory was assessed in two probe tests (with the platform absent from the pool). During
the first probe, half the animals received light stimulation for the duration of the test and half
were tested without the light. On the following day, the animals were re-tested in a second probe
trial with the light conditions reversed (Fig. 3c, d). Using this within-subject design, we found
that reversible inactivation of this cohort of 4 weeks old adult-born neurons significantly
decreased the percent time in the target quadrant (Fig. 3e). Importantly, light illumination of 4
week-old EGFP-labeled newborn neurons did not affect the percent time in the target zone
(Supplementary Fig. 9). Furthermore, light-induced inactivation did not impact motor
coordination, as swim speed (Fig. 3f) and distance traveled (Supplementary Fig. 10a) did not
significantly differ from the control condition. Memory impairments depended upon both
retroviral expression of Arch and light illumination since neither retroviral expression of Arch
alone (without illumination) nor illumination alone (in the absence of Arch) impaired memory
(Supplementary Figure 2; 13
) (Fig. 4d).
These results suggest that a cohort of ~4 week-old newborn cells plays a key role in
memory expression. By examining expression of the activity-regulated gene, c-fos, we next
asked whether this population of cells was normally activated by memory recall, and whether
this activation was absent following light-induced inactivation. Mice received injections of Arch
or EGFP retrovirus into the dentate, and 4 weeks later were trained in the water maze. At the
completion of training, half the mice were given a probe test with the light on and the other half
with no light (Supplementary Fig. 11a). Using standard procedures24
, 90 minutes after the probe
tests, we sacrificed the mice and performed c-fos staining. We imaged c-fos+ and Arch+ DG
cells (Supplementary Fig. 11b). In the Arch/no light and EGFP/light groups, about 4% of labeled
adult-born DG cells were c-fos positive (Supplementary Fig. 11c), consistent with our previous
findings24
. This result suggests labeled adult-born DG cells at ~4wpi have been recruited and are
activated by retrieval of a spatial memory. Mice in the Arch/light group searched non-selectively
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in the probe test (similar to deficits observed in Fig. 3d). Furthermore, very few Arch-labeled
adult-born DG cells expressed c-fos (Supplementary Fig. 11b & c), confirming the efficiency of
optical inhibition, and additionally, providing support for the conclusion that labeled ~ 4 week-
old adult-born DG cells regulate spatial memory retrieval.
We next evaluated whether silencing these neurons interfered with the expression of a
non-hippocampus-dependent water maze memory. The same mice were trained in a visible
version of the water maze in which the platform was located in the opposite quadrant of the pool
and marked by a visible cue. Across two days of training, mice learned to navigate to the cue
from different start positions (Fig. 3c, d). During two subsequent probe tests (light on and light
off conditions, counterbalanced), we found that light inactivation did not interfere with the
ability to find the visible platform (Fig. 3g), swimming (Fig. 3h) or distance traveled
(Supplementary Fig. 10b).
To ask whether our results would generalize to another form of hippocampus-dependent
memory, we next trained a new group of animals in a fear conditioning paradigm (Fig. 4a), in
which a tone is paired with a mild footshock in a training context. When replaced in the training
context or presented with the tone in an alternate context, mice typically exhibit a range of
species-typical fear behaviors, including freezing (the cessation of all but respiratory-related
movement) 38
. Mice were trained with a single tone-shock pairing and placed back in the training
context 1 day later. In this test, optogenetic silencing significantly reduced levels of conditioned
freezing (Fig. 4b, c), indicating that inactivating 4 week-old adult-born neurons impaired the
retrieval of contextual fear memory. The following day, we placed mice in an alternate context
and presented the tone. In contrast, optogenetically silencing these neurons did not affect
conditioned freezing to the tone (Fig. 4d). As the retrieval of contextual, but not tone, fear
memories depend on hippocampal function 38
, these results suggest that silencing a cohort of 4
week-old adult-born DG cells impaired retrieval of a hippocampus-dependent contextual fear
memory.
Reversible silencing of 2 or 8 weeks old newborn neurons show no significant effect on
hippocampal memory retrieval
We next asked whether silencing different aged cohorts of newborn neurons would have
similar impact on hippocampus-dependent memory retrieval. To address this, we trained mice 2
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or 8 weeks following retroviral injections. Silencing cells that were ~2 weeks-old at the time of
training did not disrupt subsequent expression of a spatial or fear memory (Fig. 5a;
Supplementary Fig. 12). Similarly, silencing cells that were ~8 weeks old at the time of training,
an age at which they are considered mature (Fig. 1, 14-15,20
), did not significantly affect
expression of a spatial memory (Fig. 5b) or contextual fear memory (Supplementary Fig. 12).
Not all adult-generated granule cells survive and therefore the absence of effects of silencing at 8
weeks might be because there are fewer Arch+ cells. Accordingly, we counted Arch positive
newborn DG cells after behavioral tests. As shown in Supplementary Table 2, we found that
there was no significant decrease in number from 4 to 8 weeks after birth, consistent with
previous studies 1,8,39
, and, furthermore, infected cells have similar dendritic complexity at ~4
and 8 wpi (Supplementary Fig. 13).
These results indicate ~4 week-old newborn neurons are recruited, and play a key role in
subsequent memory retrieval. To further explore the specificity of these effects we designed a
within subject experiment where mice were tested water maze at 4 wpi and contextual fear
conditioning at 8 wpi, or vice versa (Supplementary Fig. 14). We found that silencing newborn
neurons at 4 wpi, but not 8 wpi, disrupted memory retrieval in both tasks, consistent with our
above observations (Fig. 3-5).
Finally, we next asked whether the coincidentally heightened plasticity (Fig. 2)
contributes to the role of young newborn neurons in retrieval of hippocampal-dependent
memories (Fig. 5d). Since we found that the activity of T-type Ca2+
channels plays an essential
role in the heightened plasticity, we tested hippocampal memory of the Arch-injected animals at
4 wpi in the presence of mibefradil. Interestingly, the application of mibefradil substantially
decreased the searching time in the target quadrant compared to the saline-light off groups (Fig.
5d). In another group of animals, when we applied mibefradil and optical inhibition, we observed
a similar deficit in memory retrieval in the mibefradil treated animals (Supplementary Fig. 15).
Because T-type Ca2+
channels are also required for the heightened plasticity in dendritic
synapses, these data suggest that heightened plasticity in young newborn neurons may play a key
role in memory retrieval. Together, our data suggest that adult-born neurons may transiently play
a critical role in memory retrieval, but the impact, at least in spatial and contextual memory
retrieval, may decline as these adult-born neurons continue to mature.
Discussion
227
We used optogentic methods to evaluate how adult-born DG cells functionally integrate
into hippocampal circuits. We found that newborn DG cells form functional glutamatergic
synapses in the CA3 area as early as 2 weeks after birth and these synapses become functionally
stable by 4 weeks in age. Our in vivo recording from CA3 area following stimulation of a group
of newborn DG cells revealed that output synapses of 4-week old newborn neurons exhibit
enhanced plasticity. Interestingly, reversibly silencing a population of 4 but not 2 or 8 weeks old
significantly impacted hippocampal memory retrieval. These data indicate that adult-born
neurons influence hippocampal function and hippocampal-mediated behaviors in a maturation-
dependent manner. Together with the finding that young newborn cells have more excitable
membranes 16
and enhanced dendritic synaptic plasticity 22
, our results suggest that cohorts of
newborn neurons transiently represent a unique population of granule cells and may
disproportionately influence hippocampal-mediated behaviors.
Functional output circuit development
The retroviral method has been widely used to birth-date and deliver genes to adult-born
neurons by many groups including ours 13-14,19
. In the current study, we successfully employed
this method to deliver optogenes to cohorts of adult-born DG cells. As we previously reported 13-
14, infection with these retroviruses did not appear to affect the development of labeled newborn
neurons or the physiology of surrounding mature neurons (Supplementary Fig. 2 and Table 1).
By using optogenetic stimulation, in vitro and in vivo physiology and imaging methods, we
established that young adult-born neurons functionally project to the CA3 neural circuitry.
Although we did not fully characterize the pharmacological properties of these synapses (Fig.
1e), blockade of post synaptic responses by applying AMPA receptor or metabotropic glutamate
receptor agonists suggests that they are typical mossy fiber synapses as previously reported 30
.
The functional projection of young newborn neurons to interneurons remains to be examined,
although it is well-established that mature DG cells form such synapses 4,19
. Together with
several previous studies 13-15,20
, it now appears to be clear that adult-born DG cells fully
incorporate into the hippocampal trisynaptic neural circuit around 4 weeks after birth.
Using optogenetic and retroviral methods, we revealed a restricted time window for
newborn neurons during which time they exhibit enhanced plasticity at CA3 synapses. We found
output synapses of adult-born DG cells exhibit enhanced plasticity at ~4 weeks of age (Fig. 2),
228
similar to the time during which we observed hyper-sensitive input synapses, and when these
cells have more excitable membranes 16,22
. Input synapses of 4-8 week-old newborn neurons
exhibit a high level of anatomical plasticity, with dendritic spine motility peaking at ~4 weeks
and declining thereafter 11,20
. However, the motility of axonal synapses remains unknown.
Mechanistically, we found that mibefradil, a T-type Ca2+
channel blocker, could abolish the
heightened axonal plasticity of young newborn neurons, similar to what has been previously
reported in their dendritic synapses 16
. We previously found that the switch of NMDA receptor
components from 2A to 2B may account for the enhancement of dendritic synaptic plasticity
during 4 and 6 weeks after birth 22
. The essential roles for Ca2+
Channels in axonal synaptic
plasticity of dentate granule cells have been extensively studied 28,41
. However, the roles of
NMDA receptors in synaptic plasticity in the CA3 area remains controversial although some
recent studies suggest their involvement 30,42
. Furthermore, we recently found that continuous
increase in the strength of inhibitory circuits may decrease the power of plasticity in dendritic
synapses 43
, which raises another possibility for the observed enhanced plasticity of output
synapses. A very recent finding showed that the activity may differentiate continuously-
generated newborn neurons into groups to serve hippocampus-related pattern separation 23
. The
heightened axonal plasticity together with the enhanced dendritic plasticity 16,22
of young
newborn may be involved in facilitating this process.
Time-dependent role of young adult-born neurons
Chemical, genetic and irradiation-based methods have been widely used to ablate
neurogenesis and explore the role of adult neurogenesis in hippocampal function 9,44
. While these
studies suggest that adult neurogenesis plays an important role in hippocampal memory, a
limitation is that these manipulations typically affect a broad range of adult-born cells and so it is
unclear whether depletion of immature or mature newborn neurons is responsible for observed
memory deficits. By retrovirally expressing optogenes we were able to address this issue by
silencing distinct of adult-generated neurons. This optogenetic silencing of adult-born neurons by
high frequency light stimulation is likely to result from ―effective but not excessive‖
hyperpolarization, rather than potentially harmful changes in internal chloride levels 36
. Our
experiments indicated that silencing of ~4 week-old newborn neurons led to memory deficits. In
contrast silencing this same population before training did not prevent the acquisition of a
hippocampal memory. The dissociation is consistent with our recent findings using a diphtheria
229
toxin-based ablation system to study the role of adult-generated neurons in hippocampal memory
(Arruda-Carvalho et al., 2011), and suggests that learning may occur in the absence of newborn
neurons. However, if newborn neurons are present at the time of training, they are recruited into
hippocampal memory circuits and silencing (or ablating) these ‗memory-committed‘ cells
reveals that they play an essential role in memory retrieval. While memory retrieval deficits were
only observed after silencing of 4 week-old newborn neurons, we cannot exclude the possibility
that silencing 8 week-old newborn neurons also impacts hippocampal function, albeit to a lesser
degree. It is noteworthy that the retroviral approach only labels a relatively small group of
newborn neurons (Supplementary Table 2), and so even the activity of this small population of
cells strongly influences hippocampal function. Mechanistically, young newborn neurons are
more excitable and exhibit heightened plasticity at around 4 weeks16,22
, and these properties
likely increase their likelihood of being recruited into hippocampal memory circuits23-24,27
. This
also has been suggested by our finding that mibefradil, which blocks the heightened plasticity,
affects the behavioral role of newborn neurons.
Methods
Retroviral production and stereotaxic injection
Engineered self-inactivating murine oncoretroviruses were used to deliver genes of
interest specifically to proliferating cells and their progeny 13-14
. The optimized ChR2 and
ChETA constructs were obtained from Karl Deisseroth and ChIEF construct from Roger Tsien.
The Arch construct from Edward Boyden was purchased from Addgene.
Purified engineered retroviruses were stereotaxically injected into ~5 weeks old adult
female C57BL/6 mice (Charles River). All animal procedures were conducted in accordance
with institutional guidelines.
Optrode implantation and behavioral procedures
All mice were housed under standard conditions. Optrodes (Doric Lenses Inc., Canada,
modified to increase light spread) were implanted bilaterally into the dorsal dentate gyrus
(coordinates: 3.0 mm rostral from bregma, 2.6 mm lateral from the midline and 2.5 mm ventral)
14 days after two retroviral injections (~10 hours interval) unless we specifically addressed in the
main text. After implantation, animals received at least 2 weeks recovery before any behavioral
experiment.
230
After behavioral experiments, mice were perfused transcardially with PBS followed by
4% PFA. Brains were sectioned and the optrode implantation sites were verified and numbers of
retroviral-labeled adult-born neurons were counted. Mice were excluded if the implantation site
was incorrectly positioned. Mice with missed viral injections were discarded. Mice with correct
injections all had 1500 ~2000 newborn DG cells and all of them have been selected for
behavioral analysis.
Water maze (hidden platform version). The apparatus and behavioral procedures have
been previously described 24,45
. Behavioral testing was conducted in a circular water maze tank
(120cm in diameter, 50cm deep), located in a dimly-lit room. The pool was filled to a depth of
40cm with water made opaque by adding white, non-toxic paint. Water temperature was
maintained at approximately 26oC. A circular escape platform (10 cm diameter) was submerged
0.5 cm below the water surface, in a fixed position in one of the quadrants. The pool was
surrounded by curtains, at least 1 m from the perimeter of the pool. The curtains were white with
distinct cues painted on them.
Water maze training took place across 6 days. Each training session consisted of 3
training trials (inter-trial interval was ~15 s). On each trial, mice were placed into the pool,
facing the wall, in one of 4 pseudorandomly-varied start locations. The trial was complete once
the mouse found the platform or 40 seconds had elapsed. If the mouse failed to find the platform
on a given trial, it was guided onto the platform by the experimenter. Following training, spatial
memory was assessed in two probe tests with the platform removed from the pool. The probe
tests were 40 s in duration and conducted 24 h and 48 h after the last training session. Animals
performed training and probes attached to the optic fibers and rotatory joint. Each animal
experienced one probe with light stimulation and one without, the order of which was
counterbalanced between animals. Behavioral data from training and the probe tests were
acquired and analyzed using an automated tracking system (Ethovision XT, Noldus,
Wageningen, Netherlands). Using this software, we recorded a number of parameters during
training, including escape latency and swim speed. In probe tests, we measured the amount of
time mice searched in the target quadrant vs. the three other quadrants.
Water maze (visible platform version). For the visible platform task, the platform was
moved to the opposite quadrant and marked by a visual cue. The cue consisted of a plastic
cylinder (4 cm in diameter, 4 cm in height) with a horizontal black/white vertical striped pattern
and was placed on top of the platform. Visible platform training started 24h after the last hidden
231
platform probe and consisted of one training session of 3 trials per day (inter-trial interval was
~15 s) across two days. On each trial mice were placed into the pool, facing the wall, in one of 4
start locations (pseudorandomly-varied). The trial was complete once the mouse found the
escape platform or 40 s had elapsed. Similar to the hidden version of the water maze, animals
were divided into two groups to perform two probe tests, counterbalanced for order of light
stimulation. The probes started 24h after training and were conducted on consecutive days. As
before, behavioral data from training and the probe tests were acquired and analyzed using an
automated tracking system.
Context fear conditioning. The fear conditioning chamber consisted of a stainless steel
conditioning chamber (18 cm × 18 cm × 30 cm; Coulbourn, Whitehall, PA), containing a
stainless steel shock-grid floor. Shock grid bars (diameter 3.2 mm) were spaced 7.9 mm apart.
The grid floor was positioned over a plastic drop-pan, which was lightly cleaned with 70% ethyl
alcohol to provide a background odor. The front of the chamber was made of clear acrylic and
the top, back and two sides made of modular aluminum. Animals were subjected to two probes, a
context test and a tone test. For the context testing animals were placed in the fear chamber,
where they were originally shocked. For tone testing mice were put in a modified version of the
fear chamber that consisted of a white, plastic floor covering the shock grid bars and a plastic,
triangular insert placed inside the same conditioning chamber used for training. One of the walls
of this insert had a black/white striped pattern. The other two walls were white. After each test
the plastic floor was cleaned with water. Mouse freezing behavior was monitored via overhead
cameras and scored manually.
During training, mice were placed in the fear conditioning chamber for a total of 3 min.
After 2 min of free exploration mice were presented with a 30 s tone (2800 Hz, 85 dB) that co-
terminated with a 2 s footshock (0.5 mA). Mice remained in the chamber for a further 30 s before
being returned to their home cage.
Twenty four hours after training, freezing was assessed in two 5 min tests, in the fear
chamber and its modified version, respectively. In the second probe, the tone was presented after
a 2 min delay. Animals were divided into two groups, so that half received light stimulation
during the context test and half during the tone test. Data is presented as function of time for the
context test. For the tone test we measured freezing to the tone for 60 seconds.
Slice and in vivo physiology
232
Mice were processed at 1, 2, 3 and 4 wpi and electrophysiological recordings performed
at 32°C - 34°C, as previously described 14
. For efferent CA3 synapse slice experiments, short
pulses of blue light were generated by a 50mW 473 nm laser under the control of a standard TTL
board and launched into a Zeiss upright microscope through the epifluorescence light path. The
ending power on brain slices was ~5 mW/mm2 and synaptic transmission was recorded at -
65mV.
For in vivo recording, mice received injections of ChIEF-dTomato retrovirus 3, 4 and 8
weeks prior to in vivo recordings. Briefly, animals were anesthetized and mounted on a
stereotaxic frame. An optrode was inserted into dorsal dentate gyrus (coordinates: 3.0mm rostral
from bregma, 2.6mm lateral from the midline and 2.5mm ventral). Pulses of blue light controlled
by recording software (pClamp10.0) was generated from a 50mW 473nm laser and delivered
thought an optic fiber. A recording electrode was inserted into CA3 molecular layer (coordinates:
2.0mm rostral from bregma, 2.2mm lateral from the midline and 2.2mm ventral), and field
excitatory postsynaptic potentials were recorded upon optical stimulation of the dentate gyrus.
After recording, mice were perfused transcardially with PBS followed by 4% PFA. Brains were
sectioned to check for the presence of retroviral-labeled adult-born neurons, and the sites of
stimulation in dentate gyrus and recording in CA3 (Supplementary Fig. 4). Mice were excluded
if the recording site was out of CA3.
Fos immunohistochemistry and analysis
Neuronal activity during memory retrieval was analyzed by imaging immediate-early
gene c-fos expression as previously described 24
, and illustrated in Supplementary Figure 11a.
Briefly, ninety minutes following the completion of behavioral testing, mice were deeply
anesthetized and perfused transcardially with PBS and then 4% paraformaldehyde (PFA). Brains
were removed, fixed overnight in PFA and then transferred to 30% sucrose solution and stored at
4 °C. Brains were sectioned into 50 µm coronal sections of covering the full anterior-posterior
extent on the dentate gyrus. Immunohistochemistry was performed using primary antibodies to
Fos (rabbit anti-Fos polyclonal antibody; 1:1,000, Calbiochem), and Alexa-568 goat anti-rabbit
(1:500, Molecular Probes) as secondary antibodies. Sections were incubated in primary
antibodies overnight, and then with secondary antibodies and anti-NeuN primary antibody for 2
hours at room temperature, in the presence of 2% goat serum, 1% bovine serum albumin and
0.2% Triton X-100. Sections were mounted on slides with Permafluor anti-fade medium
233
(Lipshaw Immunon). Images of the dentate gyrus were taken on an Olympus FLV1000 confocal
microscope, and we quantified Fos+ and EGFP+/Arch-EGFP+ cells throughout the anterior-
posterior extent of the granule cell layer. Number of Fos+ cells and EGFP+/Arch-EGFP+ cells
quantify from two-dimensional images of the entire dentate gyrus, and the ratio of Fos+EGFP+
in EGFP+ cells was calculated for each animal.
Staining and and reconstruction of biocytin-filled neurons
Brain sections with biocytin-filled neurons were fixed in 4% PFA overnight and stained
using a alexa 647-conjugated streptavidin from Invitrogen. Images were acquired on an
Olympus FLV1000 confocal system and biocytin-filled neurons were reconstructed afterwards
using Olympus FluoView10 software.
Statistical analysis
Data were analyzed using ANOVAs followed by t-tests. Significance was considered when p <
0.05. ANOVAs and most t tests are described in the figure captions. For all other planned t tests
see supplementary table 3. In the water maze, animals were considered to be searching
selectively if percent search in NE was significantly greater than each of the other quadrants (i.e.,
NE>NW, NE>SE, NE>SW). If NE was not greater than all other quadrants the search was
considered not selective.
ACKNOWLEDGEMENTS
We thank Gary Matthews, Lorna Role, Hongjun Song and Josef Bischofberger for their
critical comments, Qiaojie Xiong and Jason Tucciarone for technical support. We thank Fred
Gage‘s laboratory for sharing their retroviral packaging system and behavioral protocols. This
work was supported by NIH (NS065915) and AHA (0930067N) grants to S.G. and Canadian
Institutes of Health Research grants to P.W.F. (MOP86762) and S.A.J. (MOP74650).
Figure legends
Figure 1. Adult-born neurons stably form functional synapses on CA3 pyramidal neurons
by 4 weeks of age. (a) Upper: Experimental time-line. Adult mice were injected with high-titer
ChR2-EGFP retrovirus and recordings were made on acute brain slices at 1, 2, 3, 4, 6 and 8 wpi.
234
Lower: Image showing adult-born DG cells (4 wpi) and their axonal fibers (EGFP+). Scale bar:
50 m. (b) Pulses of light (5 ms, 473 nm) elicit action potentials in ChR2-EGFP-infected, but not
neighboring (EGFP-) DG cells. Left: Image showing recorded DG neurons (white, biocytin filled
from the recording pipette) on an acute brain slice (4 wpi). i, ChR2-EGFP+ newborn neurons
(green and white) and ii, non-infected neighbor (white). Right: Light induced action potentials in
EGFP+ (i) but not in EGFP- (ii) DG cell. Scale bar: 100 m. (c) Optically-evoked EPSCs from
adult-born DG cells. Left: Image showing ChR2-EGFP+ axonal terminals (green) of adult-born
DG cells (4 wpi) and a recorded CA3 pyramidal neuron (white). Right: a sample opticallyevoked
EPSCs recorded from this cell, subsequently blocked by 50 M CNQX. Scale bar:
10m. (d) Time-course of axon integration (left, EGFP) and formation of functional synapses on
CA3 neurons (right) by newborn neurons at 1, 2, 3 and 4 wpi. Scale bar: 10 m. (e) Amplitude of
EPSCs. Shown is a summary of mean amplitude of EPSCs at 1, 2, 3, 4, 6 and 8 wpi. (f) Latency
of EPSCs at 2, 3, 4, 6 and 8 wpi. (g) Shown is a summary of EPSCs which were inhibited by 50
M L-AP4 (n=5, p=0.012) or 1 M LY354740 (n=6, p=0.008), and blocked by 50 M CNQX
(n=15, p<0.001). All values represent mean±SEM (*, p<0.05, t-test).
Figure 2. Adult-born neurons at 4 weeks of age show enhanced plasticity at output
synapses. (a) Experimental time-line. Adult mice were injected with retrovirus expressing a
ChR2 variant optimized for reliability under high frequency stimulation (ChIEF-dTomato, Suppl.
Fig.3), and post-synaptic responses in CA3 were recorded in vivo at 3, 4 and 8 wpi by optically
stimulating adult-born neurons in dentate gyrus (Suppl. Fig.4). (b) Optically stimulating
adultborn neurons produces fEPSPs in the CA3 area. Left, fEPSPs blocked by infusion of 50M
CNQX (but not saline). Right, optical stimulation (50 Hz pulses of 5 ms) reliably induced
fEPSPs. Scale bars: 5 ms and 0.1 mV. (c) Theta-burst optical stimulation of adult-generated
neurons produces long-term potentiation at CA3 synapses in an age-dependent manner. Top row,
examples of fEPSPs LTP from a single animal at 3, 4 or 8 wpi (newborn neurons). Insets:
Averaged traces of fEPSPs from 5 consecutive recordings before (1), immediately following (2),
and after (3) LTP induction using physiologically relevant theta burst stimulation (TBS, blue
arrow, Suppl. Fig.4). Shown at the bottom is a summary of LTP from groups of animals,
respectively. (d) Percentage of mice (3, 4 and 8 wpi) exhibiting reliable LTP. (e) Summary of the
mean potentiation of fEPSPs amplitude 45-60 min following TBS from mice under control
condition (3 wpi, n=6; 4 wpi, n=8; 8 wpi, n=8; t-test between groups: 3 wpi vs. 4 wpi, p=0.024; 8
wpi vs. 4 wpi, p=0.007) or after application of mibefradil (3 wpi, p=0.007, n=4; 4 wpi, p<0.001,
n=5; 8 wpi, p=0.41, n=4; t-test between control and mibefradil conditions). In each group, all
animals tested were included. All values represent mean±SEM (*, p<0.05 comparing between
groups under control condition; #, p<0.05 comparing between control and mibefradil conditions;
n.s., p>0.05).
Figure 3. Specifically and reversibly silencing 4 week-old adult-born neurons impairs
hippocampal memory retrieval. (a) Optical stimulation (589 nm light) silences Arch-EGFP
expressing adult-born neurons. Optical stimulation (20 Hz pulses of 5 ms) prevented action
potentials induced by current injection (50 pA) (black bars) in Arch-EGFP+ DG cells (4 wpi) in
acutely-prepared hippocampal sections. Scale bars: 100 ms and 30 mV. (b) Schematic drawing
showing a mouse with implanted optrodes connected to an orange light source via optic fibers
and an optic rotatory joint. (c) Time-line of watermaze experiment. Adult mice were infused with
Arch-EGFP retroviruses, implanted with optrodes and trained in the hidden version of the water
maze at 4 wpi. Spatial memory was assessed in two probe tests with (orange) and without (black)
235
optical stimulation (counterbalanced, within-subject design). Mice were then trained in a visible
version of the water maze with a visible cue, followed by probes with and without optical
stimulation. (d) During training (no light), latency to find the platform declined. (e) Optically
inactivating a cohort of 4 week-old adult-born neurons impaired hippocampal memory retrieval.
During the probe, mice in the ―no light‖ condition searched selectively – spending more time in
the target quadrant (NE) compared to the other quadrants: (One-way repeated measures ANOVA
F3,39=7.139, p<0.001; NE>NW, SW, SE by paired t-test planned comparison, n=14), showing
robust spatial memory. In contrast, mice in the light on condition (inactivation) spent equivalent
time in NE compared to other quadrants (One-way repeated measures ANOVA F3,39=0.9655,
p=0.4187; p>0.05 NE vs. NW, SW, SE by paired t-test planned comparison; n=14), showing a
disruption of spatial memory (NEno light>NElight t13=2.153, p=0.0253 by planned comparison) . (f-
h) Optical inactivation did not alter swim speed in hidden probe tests (P1 and P2) (f, t13=1.046,
p=0.3145; n=14). In the visible version of the water maze, optical stimulation did not alter the
latency to find the platform (g, t13=0.1215, p=0.4526; n=14) or swim speed (h, t13=0.6464,
p=0.2646; n=14) in the probe tests (P1 and P2). All values represent mean±SEM (*: p<0.05).
Figure 4. Temporary silencing of 4 week-old newborn neurons impairs expression of a fear
conditioning memory. (a) Time-line of fear conditioning test. Adult mice were infused with a
retroviral vector (Arch-EGFP), implanted with optrodes and trained in fear conditioning (single
tone-shock pairing). Twenty-four hours after training, contextual fear memory was assessed. An
additional tone test was performed in which mice were placed in a novel context and the tone
replayed. Animals were divided into two groups and optical silencing was counterbalanced in
contextual and tone freezing tests. (b) Silencing of adult-born DG cells at 4 wpi reduced freezing
to the context compared to control (n=7, 7). (c) Averaged freezing time in the first 2 minutes of
the context test (t12=2.239, p=0.0224; n=7, 7). (d) Optically inactivating these neurons had no
effect on tone fear memory (t12=1.675, p=0.0599; n=7, 7). To avoid potential interference from
with-in session extinction, we measured freezing time in the first 2 minutes. All values represent
mean±SEM (*: p<0.05).
Figure 5. Silencing 2 or 8 week-old adult-born neurons did not interfere with hippocampal
memory retrieval. (a-b) Optically inactivating a cohort of 2 or 8 week-old adult-born neurons
showed no significant effect on hippocampal memory retrieval. During the probe similar to that
described in Fig. 3d, e, mice at 2 (a) or 8 (b) wpi spent more time searching in the target
quadrant (NE) compared to the other quadrants in both ―no light‖ (One-way repeated measures
ANOVA 2 wpiNo light: F3,15=15.25, p<0.0001; 8 wpiNo light: F3,15=8.081, p=0.0019; NE>NW, SW,
SE by paired t-test planned comparison in both groups; n=6,6 in both) and ―light‖ conditions
(One-way repeated measures ANOVA 2 wpiLight: F3,15=9.125, p=0.0011; 8 wpiLight: F3,15=14.20,
p=0.0001; NE>NW, SW, SE by paired t-test planned comparison in both groups; n=6 in both),
showing no disruption of spatial memory expression. (c) Reversible silencing of adult-born DG
cells altered hippocampal memory retrieval in a restricted time window. Shown is a summary of
percent of time the animals spent in the target quadrant (NE) under ―light‖ condition. (d)
Another two groups of mice were tested at ~4 wpi, with application of saline/mibefradil 1 hour
before testing. Mibefradil mimicked the deficit in spatial memory retrieval induced by optical
silencing of 4 week old neurons. Shown is a summary of percent of time the animals spent in
Target (NE) vs. Off Target (average of SE, NW, and SW). (Refer to Supplementary Figure 15
for detailed statistic information.) All values represent mean±SEM (*: p<0.05).
236
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Supplementary Information
A critical time window for adult-born dentate granule cells in hippocampal
function revealed by studies of optically-controlled newborn neurons
Yan Gu1, Maithe Arruda-Carvalho3,4, Jia Wang1, Stephen Janoschka1,2, Sheena
Josselyn3-5, Paul Frankland3-5,* and Shaoyu Ge1,2,*
1Department of Neurobiology and Behavior, SUNY at Stony Brook, Stony Brook, NY 11794
2Program in Neuroscience, SUNY at Stony Brook, Stony Brook, NY 11794
3Program in Neurosciences and Mental Health, Hospital for Sick Children, 555 University Ave,
Toronto,
Ontario, Canada, M5G 1X8
4Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada, M5S 1A8
5Department of Physiology, University of Toronto, Toronto, Ontario, Canada, M5S 1A8
Contents:
Supplementary Figures 1-15
Supplementary Tables 1-3
246
Supplementary Figure 1. Sites and tracks of viral infection in the adult hippocampus. a,
Schematic drawing in the left panel shows the viral injection sites in the dentate gyrus. Right
panel shows the injection coordinates in mm. b and c, Images showing the injection tracks 1week
(b) and 2 weeks (c) after viral injection. Note that injection tracks (arrow) were hardly seen at 2
weeks after injection, as shown in c. A: anterior; P: posterior; M: medial; L: lateral;D: dorsal; V:
ventral. Scale bar: 200μm.
247
Supplementary Figure 2. Specific labeling of newborn DG cells with high-titer retrovirus.
Shown on the left in a1, b1 and c1 are sample images of newborn neurons at 7, 14 and
28 days after high-titer retroviral infection. Shown on the right in a2, b2 and c2 are enlarged
view of these newborn neurons, respectively. Note that, morphologically, there are no mature
DG cell-like cells at 7 and 14 dpi. Scale bars: 100um.
248
Supplementary Figure 3. Responses recorded from ChIEF-expressing newborn neurons
following theta-burst optical stimulation. We performed whole cell patch clamping recording
from ChIEF-dTomato expressing newborn neurons at 3, 4, and 8 wpi. Responses were recorded
following theta-burst optical stimulation. a, Schematic diagram depicting theta burst stimulation
(TBS). TBS was used to induce LTP in output synapses of adult-born DG cells in vivo. TBS is
composed of four stimulation episodes at 0.1 Hz. Each episode is a burst of ten 100 Hz, 5ms
pulses delivered at the theta frequency (5 Hz). b, A sample image showing a recorded newborn
DGC filled with biocytin through the recording pipette. Scale bar: 50_m. c, Optical-induced
currents (upper traces) and action potentials (lower traces) recorded from newborn neurons at
3, 4 and 8 wpi in response to theta-burst optical stimulation (blue bars). Scale bars: vertical
50 pA or 20 mV; horizontal 100 ms. In boxes are enlarged traces of one burst (100 Hz, 10
pulses). Scale bars: vertical 50pA or 20 mV; horizontal 50ms. d, A sample image showing a
mossy fiber terminal of newborn neurons filled with biocytin through the recording pipette. Scale
bar: 20um. e, Optical-induced currents (upper traces) and action potentials (lower traces)
recorded from newborn neurons at 3 wpi. Scale bars: vertical 50 pA or 20 mV; horizontal 100
ms. In boxes are enlarged traces of one burst. Scale bars: vertical 50pA or 20mV; horizontal
50ms.
249
Supplementary Figure 4. Sites of stimulation and recording in the DG-CA3 fEPSPs
examination in vivo. a, Schematic drawing shows the optical stimulation site in the DG and
recording site in the CA3. A: anterior; P: posterior; M: medial; L: lateral; D: dorsal; V: ventral. b,
Sample DIC images showing the tracks of optical stimulation site in the DG (left panel) and
recording site in the CA3 (right panel). Scale bar: 50 μm. c, Two-photon images showing ChIEF-
dTomato expressing adult-born neurons in the DG (left panel) and CA3 (axonal terminals, right
panel). Scale bar: 50 μm.
250
Supplementary Figure 5. Enhanced plasticity in output synapses of young adult-born neurons
using a titanic induction paradigm. a, Schematic drawing shows whole-cell recording from a
CA3 pyramidal neuron while blue light stimulation was delivered on ChIEF expressing adult-
born DGCs. b-d, Excitatory postsynaptic responses were recorded from CA3 pyramidal neurons
by optically stimulating young (~4 wpi) or old (~ 8 wpi) ChIEF expressing adult-born DGCs.
LTP was induced by a tetanic optical stimulation (50 Hz, 2 s). b, Shown are traces before (black
trace) and after (red trace) LTP induction. Scale bars: vertical: 20 pA; horizontal: 5 ms. c, LTP
expression. d, Histogram showing the amplitudes of LTP measured between 45 and 60 minutes.
All values represent mean±SEM (*: p<0.05, t-test).
251
Supplementary Figure 6. Mibefradil does not alter basal synaptic transmission. a, Traces of
fEPSPs before and after mibefradil application. Scale bar: vertical 0.05 mV; horizontal 10 ms. b,
Histogram showing normalized fEPSPs slopes before and after application of mibefradil (n=6,
n.s.:p>0.05, t-test). All values represent mean±SEM.
252
Supplementary Figure 7. Site for optrode implantation in the dorsal hippocampus. a,
Sample image of a sagittal section from mouse brain showing the location of optrode
implantation. Arrowhead: track of optrode implantation. Scale bar: 2mm. b, A sample
two-photon image showing Arch-EGFP expressing adult-born neurons after behavioral
tests. Scale bar: 20μm. c, Shown is a global view of infected neurons in the hippocampus
after viral injection. Diagrammatic drawing roughly illustrates illumination area with the
implanted optrode. Scale bar: 2mm.
253
Supplementary Figure 8. Optical silencing of newborn DGCs does not influence acquisition
of spatial memory. a, Schematic drawing shows 2, 4,or 8 weeks after injection of Arch-EGFP
retrovirus. Mice were trained in the hidden platform version of the water maze. Half of the
animals were trained with light on in the dentate gyrus during training (―light‖ group), while the
other half were trained with no light (―no light‖ group). b, During training, latency to find the
platform declined normally both in the ―no light‖ and ―light‖ groups at 2 (Two-way ANOVA,
significant effect of Training session only, F5,50=22.08, p<0.0001; n=6,6), 4 (Two-way
ANOVA, significant effect of Training session only, F5,50=44.61, p<0.0001; n=6,6) and 8wpi
(Two-way ANOVA, significant effect of Training session only, F5,50=34.54, p<0.0001; n=6,6).
All values represent mean±SEM (n=6 in each group at each time point).
254
Supplementary Figure 9. Light illumination of EGFP-labeled newborn DG cells does not
interfere with hippocampal memory retrieval. a-b, Light illumination of a cohort of 4 week-old
adult generated neurons labeled with EGFP showed no effect on hippocampal memory retrieval.
a, During training (no light), latency to find the platform declined normally in both groups. b,
During probe tests, both control (―no light‖) and ―light‖ groups searched selectively (One-way
repeated measures ANOVA No light: F3,21=8.438, p=0.0007; Light: F3,21=14.83, p<0.0001;
NE>NW, SW, SE by paired t-test planned comparison in both groups; n=8) – spending more
time in the target quadrant (NE) compared to the other quadrants, displaying robust spatial
memory. Visible platform tests were also performed, showing no difference of latency in finding
the platform (data not shown). All values represent mean±SEM (*: p<0.05).
255
Supplementary Figure 10. Swimming distance in hidden and visible platform water maze probe
tests. a, Inactivating adult-born DG cells at 4 wpi showed no effect on swimming distance in
hidden platform water maze probe tests (t13=1.008, p=0.1660; n=14). b, Inactivating adult-born
DG cells at 4 wpi showed no effect on swimming distance in visible platform water maze probe
tests (t13=0.0173, p=0.09867; n=14). All values represent mean±SEM.
256
Supplementary Figure 11. c-fos staining showing the involvement of newborn neurons in the
spatial memory retrieval during the water maze test. a, Schematic drawing: 4 weeks after
Arch- or EGFP-retrovirus injection and optrode implantation, mice were trained in the water
maze. After training, half of the mice were tested with light illumination, while the other half
with no light. 90 minutes after the probe tests, mice were transcardially perfused with PFA and
brains were fixed. c-fos expression was then stained, imaged and analyzed. b, Shown is c-fos
expression in the EGFP+ or Arch+ 4-week-old newborn neurons. Arrows: c-fos+EGFP+/c-
fos+Arch+ neurons. Scale bar: 50_m. c, Histogram showing activity-induced expression of c-fos
in EGFP+/Arch+ newborn neurons during water maze test. Optical illumination significantly
reduced the number of c-fos+Arch+ newborn neurons. All values represent mean±SEM (*:
p<0.05 and n.s.: p>0.05, t-test).
257
Supplementary Figure 12. Silencing of adult-born DG cells at 2 or 8 wpi did not interfere with
contextual fear memory expression. Percent freezing of animals in the training context while
light illuminating adult-born neurons expressing Arch at 2 wpi (t4=0.2029, p=0.4246; n=5), 8wpi
(t7=0.3824, p=0.3568; n=8) or EGFP at 4wpi (t5=0.4593, p=0.3326; n=6). All values represent
as mean±SEM of the first two minutes of the context test, comparison was made between ―No
light‖ and ―Light‖conditions.
258
Supplementary Figure 13. Similar dendritic complexity of labeled adult-born neurons
at 4 and 8 weeks after high-titer viral infusion. a, Example images showing dendritic
density of Arch-EGFP labeled neurons at 4 and 8 wpi. A 50•~50μm2 square area was randomly
selected around the middle molecular layer (dotted line square). The number of dendritic
branches in this area was counted. Scale bar: 50μm. b, Shown is the averaged number of
dendrtic branches at 4 and 8 wpi (p=0.7766, n=10, 8, t-test). All values represent mean±SEM
(n.s.: p>0.05).
259
Supplementary Figure 14. Task-switching experiments showing adult-born DG cells at 4 weeks
of age are important for memory retrieval. a, Animals were injected with Arch retrovirus and
implanted with optrodes. One group of animals was trained at 4 wpi in the water maze task and
at 8 wpi in contextual fear conditioning (upper panel). Lower panel: At 4wpi, WM trained
animals in the no light condition searched selectively (One-way repeated measures ANOVA
F3,12=9.487, p=0.0017; NE>NW, SW, SE by paired t-test planned comparison; n=5), whereas
when in the light condition they did not (One-way repeated measures ANOVA F3,12=4.004,
p=0.0345 but NE vs. NW t4=0.0702, p=0.43; NE vs. SW t4=1.792, p=0.077). When trained in
the contextual fear conditioning at 8wpi, animals failed to display a contextual fear deficit
(t4=0.3600, p=0.3685). b, After Arch retrovirus injection and optrode implantation, a different
group of mice was trained and tested at 4 wpi for contextual fear conditioning and at 8 wpi in the
water maze (upper panel). Lower panel: At 4wpi animals showed a deficit in contextual fear
conditioning (t4=3.046, p=0.0191). At 8wpi, both No light and Light groups showed intact WM
memory, searching selectively in the target quadrant (One-way repeated measures ANOVA No
light: F3,12=14.48, p=0.0003; Light: F3,12=9.644, p=0.0016; NE>NW, SW, SE by paired t-test
planned comparison in both groups; n=5). All values represent mean±SEM (*: p<0.05).
260
Supplementary Figure 15. Mibefradil produced similar defect in spatial memory retrieval as
optical silencing of the young neurons. Two groups of mice were tested at ~4 wpi, with
application of saline/mibefradil 1 hour before testing. Mibefradil mimicked the deficit in spatial
memory retrieval induced by optical silencing of 4 week old neurons. (One-way repeated
measures ANOVA SalineNo light: F3,9=10.43, p=0.0027; NE>NW, SW, SE by paired t-test
planned comparison; SalineLight: F3,9=2.849, p=0.0975; MibefradilNo light: F3,9=1.173,
p=0.3730; MibefradilLight: F3,9=1.061, p=0.4128; n=4,4 for all). All values represent
mean±SEM (*: p<0.05).
261
Supplementary Table 1. Expression of optogenes does not change intrinsic properties of
newborn neurons along time. Mice were injected with retrovirus expressing EGFP,
Channelrhodopsin 2 (ChR2), Channelrhodopsin 2 variant ChIEF, or Archeorhodopsin (Arch),
and acute brain slices were cut at 2, 3, 4 and 8 week post viral injection (wpi). Fluorescent
adult-born neurons were whole-cell patched and intrinsic properties were recorded. Shown are
the Membrane Capacitance, Membrance Resistance, Resting Membrane Potential, Action
Potential (AP) Theshold, AP Peak, AP Amplitude and AP Halfwidth of adult born DG cells at
2wpi (a), 3wpi (b), 4wpi (c) and 8wpi (d). All values represent mean±SEM, and there is no
statistical difference between groups at each time stage (p>0.05 by t-test).
262
Supplementary Table 2. High titer of Arch-EGFP retrovirus infected a cohort of newborn
DG cells per animal. Mice were perfused after behavior experiments and Arch-EGFP+ adultborn
DGCs were counted in each animal. Shown are the average numbers per mouse of Arch- EGFP+
newborn DG cells in 2wpi, 4wpi, 8wpi and EGFP groups. All values represent mean±SEM, and
there is no statistical difference between groups (p>0.05 by t-test).
263
Supplementary Table 3. Statistic analysis for Water Maze probe tests. All water maze
probe tests were analyzed using ANOVAs followed by t-test planned comparison between
target quadrant (NE) and all other quandrants (NW, SW, SE). Animals were considered to be
searching selectively if percent search in NE was significantly greater than each of the other
quadrants (i.e., NE>NW, NE>SE, NE>SW). If NE was not greater than all other quadrants the
search was considered not selective. This table shows the t, p and df values for every t-test
comparison in the water maze probe tests shown in Figures 3E, 5A, B, C and Supplementary
Figures 9B, 14A, B and 15.