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SUMMARY:Dynamics of cortical circuits lead to switching resting state func
 tional connectivity - Viktor Jirsa\, Institute for Systems Neuroscience\, 
 Marseille\, France
DTSTART:20140225T110000Z
DTEND:20140225T120000Z
UID:TALK50453@talks.cam.ac.uk
CONTACT:Mikail Rubinov
DESCRIPTION:Simulations of whole-brain mean-field computational models wit
 h a realistic connectivity dictated by tractography studies allow to repro
 duce with remarkable accuracy average functional interactions in the resti
 ng state\, showing their emergence from the interplay between anatomy\, in
 teraction delays and noise-driven local dynamics. However\, previous compu
 tational studies did not address experimentally observed occurrence of non
 -stationarity in resting state functional connectivity. In particular\, em
 pirical resting state functional connectivity manifests a rich temporal st
 ructure\, characterized by switching transitions between a few discrete fu
 nctional connectivity states. Here we discuss how state-of-the-art computa
 tional models fail dramatically in reproducing these spontaneous state tra
 nsitions\, despite their excellent fitting of the time-averaged functional
  connectivity. In this aspect\, they are thus not qualitatively superior t
 o extremely simplified linear stochastic models accounting uniquely for ef
 fects due to pure structure. We show then how non-linear dynamics can resc
 ue the situation. Considering a model with dynamic bistability at the leve
 l of each area\, we explore a novel subcritical dynamical regime which giv
 es rise to a large repertoire of possible dynamical behaviors. The resulti
 ng modes of fluctuations are strongly reminiscent of some of the most freq
 uently observed Resting State Networks. Thanks to the noise-driven explora
 tion of this dynamical (and functional) repertoire\, we are thus able to r
 eproduce in silico the switching non-stationarity of functional connectivi
 ty observed in empirical resting state recordings.\n
LOCATION:MRC CBU lecture theatre\, 15 Chaucer Road
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