CNCS Seminar
Tuesday, April 12, 2016, 3:00pm, 119 Physics
Nicolas Brunel (University of Chicago)
Statistics of connectivity in networks optimizing information storage
Abstract:- Brains have an impressive ability to store information about the
external world on time scales that range from seconds to years.
The rules of information storage in neuronal circuits are the
subject of ongoing debate. Two scenarios have been proposed by
theorists: In the first scenario, specific patterns of activity
representing external stimuli become fixed point attractors of the
dynamics of the network. In the second, the network stores
sequences of patterns of network activity so that when the first
pattern is presented the network retrieves the whole sequence. In
both scenarios, the correct dynamics are achieved thanks to
appropriate changes in network connectivity. I will describe how
methods from statistical physics can be used to investigate the
storage capacity of such networks, and the statistical properties
of network connectivity that optimizes information storage
(distribution of synaptic weights, probabilities of specific
network motifs, degree distributions, etc) in both scenarios.
Finally, I will compare the theoretical results with available data
on cortical connectivity. [video]
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