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SUMMARY:A canonical brain computation: from mechanism to purpose - Dr. Yas
 har Ahmadian\, University of Cambridge
DTSTART:20201126T140000Z
DTEND:20201126T150000Z
UID:TALK154174@talks.cam.ac.uk
CONTACT:Thiago Burghi
DESCRIPTION:To support global perception\, neural networks in the cerebral
  cortex have to integrate information across local stimulus features. Such
  integration manifests\, for example\, in “normalization”: the subline
 ar summation of responses to combinations of local features. Normalization
  is performed across cortical areas and is considered a canonical brain co
 mputation. While normalization is typically sub-additive and suppressive\,
  its sublinearity weakens with diminishing stimulus strength. I will start
  by reviewing a parsimonious model of cortical circuitry which mechanistic
 ally explains this weakening\, and moreover predicts a transition to facil
 itative and super-additive multi-feature integration for weak stimuli. I w
 ill then present a normative theory of this transition in the case of the 
 primary visual cortex. I will show how the notion of optimal coding of nat
 ural scenes\, in the presence of biological noise\, robustly predicts the 
 same transition from sub- to super-additive multi-input integration. \n\nZ
 oom link: https://zoom.us/j/99373703786
LOCATION:Online (Zoom)
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