nia neuroeconomics workshop scott huettel, duke university neuroimaging the aging brain:...
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![Page 1: NIA Neuroeconomics Workshop Scott Huettel, Duke University Neuroimaging the Aging Brain: Methodological Insights from Cognitive Neuroscience](https://reader036.vdocuments.net/reader036/viewer/2022062301/56649d985503460f94a831ee/html5/thumbnails/1.jpg)
NIA Neuroeconomics Workshop Scott Huettel, Duke University
Neuroimaging the Aging Brain: Methodological Insights from Cognitive Neuroscience
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Major Themes: Methodology and Function
How do neuroimaging methods change when studying elderly adults?
Are there general principles underlying functional changes in the elderly brain, and how can those principles be addressed using neuroimaging?
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
I. Methodological Changes
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Overview of Methodological Changes in Neuroimaging
• Functional MRI (fMRI)• MRI Volumetrics• Diffusion Tensor Imaging (DTI)• Task Logistics
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Overview of Methods in Cognitive NeuroscienceNeuronal activity vs. Metabolism
Key idea: distinguish changes in our measure from changes in function.
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Neuronal Activity: Signaling and Integration Local field potentials (LFPs) reflect the summed activity of many neurons
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
The fMRI Blood-Oxygenation-Level-Dependent (BOLD) ResponseIncreased neuronal activity results in increased MR (T2*) signal
BASELINE
ACTIVE
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Neuronal origins of the fMRI Hemodynamic ResponseThe fMRI BOLD response is predicted by dendritic activity (LFPs)
Adapted from Logothetis et al. (2002)
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Age-Related Changes in Cerebrovascular SystemStructural changes that may have functional consequences
• Thickening of vessel walls• Hypertension• Venous occlusions• Changes in capillary structure• Reduced blood flow• Reduced oxygen consumption
(CMRO2)Fang (1976)
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Do these Structural Changes Influence the fMRI BOLD Signal?
Time since stimulus onset (sec)
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BO
LD S
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nge
~1%
Huettel et al. (2001)
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Do these Structural Changes Influence the fMRI BOLD Signal?Probably not… No… and Yes
Huettel et al. (2001)
BOLD Amplitude
BOLD Refractory Effects
BOLD Signal-Noise Ratio
YE
Y
E
Y
E
Y1E1
Y2E2
Two of three studies report that BOLD amplitude is similar in young
(Y) and elderly (E) adults.
Two studies report that the BOLD signal has similar refractory
properties (i.e., to multiple events in rapid succession) in young and
elderly adults.
Two studies report that the BOLD signal has reduced signal-noise
ratio (SNR) in elderly adults.
D’Esposito et al. (1999)Buckner et al. (2000)
Y1
E1
Y2
E2
Y E E/Y
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
How does Increased Noise affect fMRI Analyses?Simulations show clear effects on spatial extent
Huettel et al., 2001
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SNR = 0.10
SNR = 0.15
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SNR = 0.52 (Young)
SNR = 0.35 (Old)
Number of Trials Averaged
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Age-related differences in how much of the brain is activated may reflect differences in SNR, not cognition.
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Conclusions: Aging and BOLD fMRIEffects not in principle, but for practice
• FMRI is a hemodynamic measure
• Aging causes cardiovascular changes
• BOLD response form unchanged with age
• BOLD response SNR decreased with age
• Problematic for between-group comparisons
• Suggestion: Group by Condition testing
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Structural Changes in the Elderly Brain: Gray MatterDifferent brain regions exhibit different patterns of lifespan change
Data from Raz et al. (2004); figure from Hedden & Gabrieli (2004)
These effects are attributable primarily to loss of synaptic density (secondarily, to cell death).
Image courtesy Gregory McCarthy
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Structural Changes in the Elderly Brain: White MatterMeasurement using diffusion tensor imaging (DTI)
Fractional Anisotropy (FA)
FA ~ 0FA ~ 1
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
White Matter Maps: Diffusion Tensor MapsDiffusion tends to be less anisotropic in elderly adults
OlderYounger
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
DTI: White-Matter Changes with Aging Reduced Fractional Anisotropy
Genu
Region of Interest
FA
Older Younger
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SFG PCF PV FFGALC Splenium PAR
Key fiber tracts in the human brain
Data from Madden et al. (2004)
White matter integrity, assessed in central voxels,
decreases in the elderly
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
DTI: White-Matter Changes with Aging Reduced Fractional Anisotropy
Data from Madden et al. (2004)
Different white matter tracts mediate performance in
young and elderly.
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Logistical Changes Differences in experimental procedures
• Reduced tolerance for time in scanner
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Elderly adults, in our experience, generally tolerate sessions of 60-75 minutes – with substantial individual variation. Younger adults tolerate sessions of 75-90
minutes. Head motion is more extensive in the elderly.Y
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Logistical Changes Differences in experimental procedures
• Reduced tolerance for time in scanner
• Reduced sensory abilities
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Logistical Changes Differences in experimental procedures
• Reduced tolerance for time in scanner
• Reduced sensory abilities
• Reduced performance on many tasks
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Excerpts from Madden et al. (2004a, 2004b, 2006)
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Logistical Changes Differences in experimental procedures
• Reduced tolerance for time in scanner
• Reduced sensory abilities
• Reduced performance on many tasks
• Biased sample selection
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
The “Super Elderly” Performance, on many scales, approximates or exceeds the young
Excerpts from Madden et al. (2004a, 2004b)
Is the typical elderly adult someone who
is college-educated,
has no significant health problems,
is taking only minimal medication,
and has a vocabulary (etc.) similar to a Duke undergraduate?
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Logistical Changes Differences in experimental procedures for elderly subjects
• Reduced tolerance for time in scanner
• Reduced sensory abilities
• Reduced performance on many tasks
• Biased sample selection
• Different motivation for participating
Excerpt from Hertwig & Ortmann (2001)
? ?
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
II. Functional Changes
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Overview of Functional Changes
• Memory
• Control processes
• Emotion and affect
• Reward evaluation
Theme I: Selective and Non-selective deficits
Theme II: Functional compensation
?
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Selective Deficits: Memory Aging has greater effects on recollection (hippocampally mediated)
Cabeza et al., 2006
Elderly: Attenuation of recollection-based
activation in hippocampus. Elderly:
Enhancement of familiarity-based
activation in rhinal cortex.
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Non-Selective Deficits: EmotionSimilar regions, but less extensive activation, in the elderly
Wright et al., 2006
< Tessitore et al., 2005
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Compensation: MemoryElderly adults recruit additional regions to maintain performance
Cabeza et al., 2002a
In a memory retrieval task, elderly adults who perform similarly to young adults (Old-High) show increased activation in left PFC,
compared to elderly adults with impaired performance.
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Compensation: Memory (and other)Frontal compensation is a robust phenomenon
Cabeza, 2002; Cabeza et al., 2004
The reductions in asymmetry are found both when hemispheric specialization is based on process (e.g., memory retrieval / encoding) and when based on stimulus domain (e.g., verbal / spatial working memory).
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Compensation: Attention Increased frontal activation in elderly adults under divided attention
Madden et al., 1997
Divided minus Central
Younger Adults Older Adults
F S W
H M D
B T G
N Z L
T R J
Q T Y
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Compensation: Executive Control Elderly adults recruit additional, non-prefrontal regions
Madden et al., 2004
Posano et al., 2005
Younger adults: Prefrontal Cortex
Elderly adults: Thalamus/BG
Elderly adults: Parietal Cortex
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Compensation: Methodological Caveats fMRI provides information about what’s active, not what’s not active
Cabeza, 2002
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Selective Deficits, Compensation: Reward systems?
Almost nothing known… hence, this meeting.
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NIA Neuroeconomics Workshop Scott Huettel, Duke University
Acknowledgments
Faculty collaborators, discussed projects• David Madden • Roberto Cabeza• Len White• Gregory McCarthy
External support• NIMH (Huettel)• NINDS (McCarthy)• NIA (Madden, Cabeza)
neuroeconomics.duke.edu
Current Laboratory Members• Alexandru Avram • J. Neil Bearden• Jacqui Detwiler • Erin Douglas• Wilko Schultz-Mahlendorf• Mark Sutherland• Dharol Tankersley• Bethany Weber
Recommended Readings:• Cabeza, Nyberg, & Park (2005). Cognitive Neuroscience of Aging. Oxford Univ. Press• Hedden & Gabrieli (2004). Nature Reviews Neuroscience• D’Esposito, Deouell, & Gazzaley (2003). Nature Reviews Neuroscience
All uncredited figures from:• Huettel, Song, & McCarthy (2004). Functional Magnetic Resonance Imaging