Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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BCCN AG-Seminar

Tuesday, 05.05.2009 17 c.t.

Encoding and consolidating: Dynamics of hippocampal/prefrontal cortex interactions during sleep and active behavior

by Prof. Dr. Francesco P. Battaglia
from SILS Center for Neuroscience, Universiteit van Amsterdam, The Netherlands

Contact person: Theo Geisel


Seminarraum Haus 2, 4. Stock (Bunsenstr.)


Slow-wave sleep (SWS) is important for memory consolidation. During sleep, neural patterns reflecting previously acquired information are replayed. One possibility is that such replay exchanges information between hippocampus and neocortex, supporting consolidation. We recorded neuron ensembles in the rat medial prefrontal cortex (mPFC) to study memory trace reactivation during SWS following learning and execution of cross-modal strategy shifts. In general, reactivation of learning-related patterns occurred in distinct, highly synchronized transient bouts, mostly simultaneous with hippocampal sharp wave/ripple complexes (SPWRs), when hippocampal ensemble reactivation and cortico-hippocampal interaction is enhanced. Thus, replay seemed to be organized in avalanche-like events, with a power-law distribution of amplitudes. mPFC neural patterns appearing during response selection replayed prominently coincident with hippocampal SPWRs taking place in sleep, following learning of a new rule. This was learning-dependent, because it was not observed before rule acquisition. Thus, learning, or the resulting stable reward, influenced which patterns were most strongly encoded, and successively reactivated, in the hippocampal/prefrontal network. Theta phase coherence between hippocampus and mPFC is a possible mechanism for this pattern selection: such coherence is indeed more elevated at the choice point and after rule learning, indicating that hippocampal theta may have an effect in organizing mPFC activity in a way that favors plasticity and memory storage. I will also describe some simple mathematical methods, derived from random matrix theory, that can be used to assess the statistical significance of replay.

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