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SUMMARY:The statistical structure of noise in large neural populations - N
 eil Rabinowitz
DTSTART:20150624T100000Z
DTEND:20150624T103000Z
UID:TALK59973@talks.cam.ac.uk
CONTACT:Guillaume Hennequin
DESCRIPTION:Sensory neurons represent stimulus information\, but their res
 ponses can vary considerably across repeated stimulus presentations. This 
 "response noise" has long figured in our models of computation in the brai
 n\, but we know little about how it is structured across large populations
 \, or how it changes depending on which computations are being performed. 
 I will present some recent work with structured latent variable models tha
 t attempts to advance on these questions. In particular\, I will focus on 
 data from large populations of macaque V4 neurons during a perceptual task
 \, whose joint activity reveals the action of latent modulatory sources. T
 he uncovered signals have pronounced anatomical and functional structure\,
  their statistics depend on attentional state\, and their values relate to
  past and future behaviour.
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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