Description:

Title: Statistics of connectivity optimizing information storage in neuronal
networks

Speaker: Nicolas Brunel, University of Chicago

Abstract: Brains have impressive abilities 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 optimize
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.

Host: David Schwab

Speaker Schedule

Keywords: Physics, Astronomy, colloquium