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  Neur(on)al Coding in Prefrontal Cortex during Visual Memory

Munk, M. (2013). Neur(on)al Coding in Prefrontal Cortex during Visual Memory. Talk presented at Bernstein Center for Computational Neuroscience. Heidelberg, Germany.

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Munk, M1, 2, Author              
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1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: As natural environments constantly change, the storage of behaviorally relevant information in short-term memory requires dynamical neuronal representations. Although such representations need to be flexible, they also need to code reliably and specifically. This appears incompatible with the broad selectivity profiles of many cortical neurons suggesting that accurate representations are based on ensembles rather than single neurons. Ensembles of neurons need to organize in a way that they can effectively encode and maintain information. This requires that the activity of distributed populations of neurons is coordinated in a way that allows for receiving (sensitivity), maintaining (stability) and relaying information (emission of effective spike patterns) upon recall for readout and the generation of behavior. At the neuronal level, almost nothing is known how encoding works except that everybody tends to believe that the synaptic activation of certain pre-assigned units or circuits reflects how e.g. PFC encodes information that needs to be stored. But, what is the role of the activity that is already in place when new sensory information arrives? If populations are responsible for encoding and maintaining information, then mere changes in activity are unlikely to represent the relevant mechanism, because this would require a very intelligent switch in each individual cell to change from transient activation to sustained firing. Then one would be stuck to explain how this switch would be operated in all involved cells simultaneously. If however, as has been postulated for many decades, reverberating activity was responsible for (at least) stabilizing the trace and maybe also for further maintenance, then a more dynamic scheme would be feasible in which the selection of contributing neurons could depend on their ability to synchronize their firing with the respective reverberating activities. Whether reverberations are always or sometimes expressed as oscillations at a local scale is not clear, but we have evidence that oscillations at various frequencies accompany all phases of working memory being correlated, both, with behavioral performance and memory content. We also have evidence for ensembles of neurons, which are distributed over columns of PFC being several millimeters apart, to become coactivated in a stimulus-selective or even -specific way during encoding, stabilization and retrieval. This coactivation has been investigated on a time scale of hundreds of milliseconds, aiming at a measure based on firing rate, while temporally more precise patterns of spike firing have been shown to coexist in the same data sets.

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 Dates: 2013-01-18
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: Munk2013_4
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Title: Bernstein Center for Computational Neuroscience
Place of Event: Heidelberg, Germany
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Invited: Yes

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