GATSBY COMPUTATIONAL NEUROSCIENCE UNIT
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John Hertz

Nordita, Sweden

Wednesday 8 October 2008

 

16.00

Seminar Room B10 (Basement)

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

Inferring Spike Pattern Distributions from Data

 

We can learn something about how large neuronal networks function from models of the spike pattern distributions constructed from data. In this work (with Joanna Tyrcha, Stockholm Univ), we do this for data generated from both experiments and simulated models of local cortical networks, modeling this distribution by an Ising model. To estimate its parameters J ij and h i we use a technique based on inversion of the TAP mean-field equations for spin glasses. The distribution we find can be described in a good approximation as a Sherrington-Kirkpatrick spin glass in its normal phase.