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SUMMARY:<b>Relational Architectures</b>
DTSTART:20091030T070000
DTSTAMP:20260407T183701Z
UID:d391bffb45d43741c16fb1d29ca68cd9b710c6af729cfee64906454b
CATEGORIES:Conferences - Seminars
DESCRIPTION:Matthew Cook\nDespite many decades of intensive research\, the
  basic principles of cortical computation remain a mystery. Even the forma
 t of the data continues to be debated (e.g. average population activity vs
 . spike timing). Visual areas are the most studied and best understood in 
 the cortex\, but even in V1 we do not understand the operation of the cort
 ical circuitry. \n\nHowever\, we do know a lot about the types of response
 s that are seen in individual neurons. I will propose that the types of re
 sponses we see correspond closely to signals in relational computation\, a
  style of computation that allows inferences to flow in any direction thro
 ugh a network. (Belief propagation in factor graphs is an example of this 
 style of computation.) I will argue that relational computation is a much 
 more reasonable starting point for understanding cortical computation than
  the standard computer-inspired cpu/memory analogy. \n\nWe will consider h
 ow this point of view can inform us on such diverse topics as population c
 ode structure\, signal restoration\, or the location of information in the
  cortex.
LOCATION:BC 01 https://plan.epfl.ch/?room==BC%2001
STATUS:CONFIRMED
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