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SUMMARY:LCN Seminar: Dynamics of structured random neural networks
DTSTART:20141118T103000
DTSTAMP:20261005T074128Z
UID:80664f52548e800b2aabf5f88147fd27abbfb7867ea1c8cb660d014a
CATEGORIES:Conferences - Seminars
DESCRIPTION:Yonatan ALJADEFF\; Computational Neurobiology Laboratory\, The
  Salk Institute\, California\nRecently we showed that neural networks with
  cell-type-specific connectivity statistics exhibit a phase transition bet
 ween silent and chaotic activity\; and that in the chaotic regime these ne
 tworks can sustain multiple global dynamic modes.\nI will present these re
 sults and discuss new directions:\n1. When the connectivity is defined to 
 obey Dale's law\, the dynamics depend explicitly on N. Requiring that noth
 ing dramatic happens as N grows gives a set of second order balance condit
 ions analogous to the balance of excitation and inhibition.\n2. The critic
 al point is derived for a generalized network with a synapse specific gain
  function g(i\,j). Giveng we predict the network's leading principal compo
 nents in the space of individual neurons' autocorrelation functions\, ther
 eby providing a direct link between the network's structure and some of it
 s functional characteristics.
LOCATION:SV1717a http://plan.epfl.ch/?room=SV1717a
STATUS:CONFIRMED
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