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SUMMARY:Contextual modulation of gamma rhythms in inhibition stabilized co
 rtical networks - Yashar Ahmadian\, Columbia University
DTSTART:20150708T150000Z
DTEND:20150708T160000Z
UID:TALK60098@talks.cam.ac.uk
CONTACT:Guillaume Hennequin
DESCRIPTION:Cortical networks feature strong recurrent excitation\, posing
  them near\npotential instability. By and large\, models of cortical dynam
 ics have relied on single neuronal saturation to overcome such instability
 . However\, throughout the cortical dynamic range\, neurons' activity tend
 s to remain well below their saturation levels\, and correspondingly their
  empirically measured input-output functions remain convex and supralinear
 . Such expansive nonlinearities at first appear to aggravate the problem o
 f stability.  Nevertheless we have recently shown that strong recurrent in
 hibition is sufficient to stabilize cortical networks against runaway exci
 tation\, without relying on single neuronal saturation (Ahmadian et al. 20
 13\, Rubin et al. 2015). Moreover\, as a consequence\, such Stabilized Sup
 ralinear Networks (SSN) provide a robust and parsimonious mechanistic expl
 anation for a plethora of contextual modulation phenomena observed across 
 sensory cortical areas.  These include surround suppression and divisive n
 ormalization\, recently dubbed a canonical brain computation (Carandini & 
 Heeger\, 2011).\n\nIn this talk I will first review these published result
 s. In the second half\, I will focus on ongoing work using the SSN to mode
 l aspects of time-dependent cortical dynamics. Gamma rhythms are a robust 
 feature of cortical dynamics\, and have been hypothesized to play a centra
 l role in various cognitive tasks. Gamma rhythm characteristics such as th
 eir power and peak frequency\, however\, exhibit strong dependencies on st
 imulus and contextual parameters (it has in turn been argued that such dep
 endencies may invalidate some hypothesized computational functions for gam
 ma). I will describe how SSN is able to robustly account for such modulati
 ons in gamma characteristics. In particular\, I will show how the model ex
 plains the particular dependence of gamma peak frequency on local stimulus
  contrast and stimulus size observed in the visual cortex. Time allowing\,
  I will also elaborate on two possible mechanisms for attentional modulati
 on of rates in SSN\, which lead to opposite effects on gamma power\, as ob
 served\, respectively\, in V1 vs. higher visual cortical areas.\n\n
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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