lecture 10: some experimental data on cognitive processes ... · purves et al p 587 fig. 23.5....

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Lecture 10:Some experimental data on

cognitive processes in the brain

Wolfgang Maass

Institut für Grundlagen der InformationsverarbeitungTechnische Universität Graz, Austria

Institute for Theoretical Computer Science http://www.igi.tugraz.at/maass/

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Open Problems

• Models for „thinking“ in networks of neurons.

• Models for the implementation of processing rules in neural circuits (and for the application of such rules to external or internal information)

• Models for the encoding of internal information(memory) in neural circuits

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Overview of experimental methods foranalyzing brain activity

Fig. on p. 81 of Purves et al

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fMRI (functional magnetic resonance imaging): a non-invasive window into brain activity

• Show movie

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Methodological problems of fMRI analysis

What exactly does the BOLD signal tell us about neuralcomputation in a concrete brain area ?

How can one explain that some brain regions exhibit areduced BOLD signal usual when a cognitive task isperformed (or when some item is successfully storedin memory) ?

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Does the BOLD signal recorded by fMRI indicateincreased excitation of neuronal activity ?

It is currently still not known, whether the fMRI could also indicateincreased inhibition of local neuronal circuits

Fig. 2 of N. Logothetis, What we can do and what we cannot do with fMRI, Science 2008

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Some brain regions exhibit a smaller BOLD signal(compared with average level) when a cognitive taskis performed.

(from Purves et al, p.375)

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Some typical fMRI results for higher levelbrain operations

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Deductive versus inductive reasoningFig. from p. 631 of Purves et al :

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fMRI traces of „insight“

Fig. from p. 639 of Purves et al

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Larger BOLD signal in frontopolar cortexwhen abtract operations are performed on internally

generated information („thinking“)

Fig. A, B, C from p. 629 of Purves et al

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Some remarks on the prefrontal cortex (PFC)Purves et al, fig. on p 582

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Some areas in the PFC exhibit a larger BOLD signalwhen a routine response has to be inhibited

• Purves et al. P. 588, A, B, C

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Patients with damages in specific parts (ventro-medial) of PFC are trouble in inhibiting behaviours

Purves et al, figures on p. 592

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…another example for that

• Purves et al, figures on p. 593

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Other typical deficits of patients withdamages in certain parts of PFC

Inferring and applying behavioural rules from sensorycues:

Purves et al p 587 fig. 23.5.(Wisconsin card sorting test)

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Results on the organization of memory in the brain

Apparently the brain uses several different memory systems:Purves et al. Fig. 13.10 from p. 341

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Creation of longterm memory goes throughseveral stages of consolidation

Baars et al fig. 19.17 on p. 273

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The medial temporal cortex: an importantarea for creating lasting declarative memory

Purves et al. Panel A from p. 336

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Some results on theneural code for memory traces during consolidation

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An example for the interaction of hippocampus with primary visual cortex in memory formation

Coordinated memory replay in the visual cortex and hippocampus during sleep.Ji D, Wilson MA. Nat Neurosci. 2007 Jan;10(1):100-7

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Experimental setup

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Results of simultaneous recording fromhippocampus and visual cortex

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A „memory trace“ in the visual cortex

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A „memory trace“ in the hippocampus

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Interaction between both „memory traces“

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Is „thinking“ or „dreaming“ faster thanexperiencing an event ?

Science. 2007 Nov 16;318(5853):1147-50. Fast-forward playback of recent memory sequences in prefrontal cortex during sleep. Euston DR, Tatsuno M, McNaughton BL – Fig 1B, 2 B

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Results on faster replay of „memory traces“

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Statistical analysis of the temporal compression factor

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A hypothesis for the role of REM sleep in memory consolidation

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Reverberation, storage, and postsynaptic propagation of memories during sleep. Ribeiro S, Nicolelis MA.

Learn Mem. 2004 Nov-Dec;11(6):686-96

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Open Problems

• Models for „thinking“ in networks of neurons.

• Models for the implementation of processing rules in neural circuits (and for the application of such rules to external or internal information)

• Models for the encoding of internal information(memory) in neural circuits