Lecture 10: Some experimental data on cognitive processes in the brain
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1 NN B 09 1 Lecture 10: Some experimental data on cognitive processes in the brain Wolfgang Maass Institut für Grundlagen der Informationsverarbeitung Technische Universität Graz, Austria Institute for Theoretical Computer Science
2 NN B 09 2 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
3 NN B 09 3
4 Overview of experimental methods for analyzing brain activity NN B 09 4 Fig. on p. 81 of Purves et al
5 NN B 09 5 fmri (functional magnetic resonance imaging): a non-invasive window into brain activity Show movie
6 NN B 09 6 Methodological problems of fmri analysis What exactly does the BOLD signal tell us about neural computation in a concrete brain area? How can one explain that some brain regions exhibit a reduced BOLD signal usual when a cognitive task is performed (or when some item is successfully stored in memory)?
7 NN B 09 7 Does the BOLD signal recorded by fmri indicate increased excitation of neuronal activity? It is currently still not known, whether the fmri could also indicate increased inhibition of local neuronal circuits Fig. 2 of N. Logothetis, What we can do and what we cannot do with fmri, Science 2008
8 NN B 09 8 Some brain regions exhibit a smaller BOLD signal (compared with average level) when a cognitive task is performed. (from Purves et al, p.375)
9 Some typical fmri results for higher level brain operations NN B 09 9
10 Deductive versus inductive reasoning NN B Fig. from p. 631 of Purves et al :
11 NN B Fig. from p. 639 of Purves et al fmri traces of insight
12 NN B Larger BOLD signal in frontopolar cortex when abtract operations are performed on internally generated information ( thinking ) Fig. A, B, C from p. 629 of Purves et al
13 NN B Some remarks on the prefrontal cortex (PFC) Purves et al, fig. on p 582
14 NN B Some areas in the PFC exhibit a larger BOLD signal when a routine response has to be inhibited Purves et al. P. 588, A, B, C
15 Patients with damages in specific parts (ventromedial) of PFC are trouble in inhibiting behaviours NN B Purves et al, figures on p. 592
16 NN B another example for that Purves et al, figures on p. 593
17 NN B Other typical deficits of patients with damages in certain parts of PFC Inferring and applying behavioural rules from sensory cues: Purves et al p 587 fig (Wisconsin card sorting test)
18 NN B Results on the organization of memory in the brain Apparently the brain uses several different memory systems: Purves et al. Fig from p. 341
19 NN B Creation of longterm memory goes through several stages of consolidation Baars et al fig on p. 273
20 NN B The medial temporal cortex: an important area for creating lasting declarative memory Purves et al. Panel A from p. 336
21 Some results on the neural code for memory traces during consolidation NN B 09 21
22 NN B 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 Jan;10(1):100-7
23 Experimental setup NN B 09 23
24 Results of simultaneous recording from hippocampus and visual cortex NN B 09 24
25 A memory trace in the visual cortex NN B 09 25
26 A memory trace in the hippocampus NN B 09 26
27 Interaction between both memory traces NN B 09 27
28 NN B Is thinking or dreaming faster than experiencing an event? Science Nov 16;318(5853): Fast-forward playback of recent memory sequences in prefrontal cortex during sleep. Euston DR, Tatsuno M, McNaughton BL Fig 1B, 2 B
29 Results on faster replay of memory traces NN B 09 29
30 Statistical analysis of the temporal compression factor NN B 09 30
31 A hypothesis for the role of REM sleep in memory consolidation NN B 09 31
32 NN B Reverberation, storage, and postsynaptic propagation of memories during sleep. Ribeiro S, Nicolelis MA. Learn Mem Nov-Dec;11(6):686-96
33 NN B 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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