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SUMMARY:Computational Neuroscience Journal Club - Philip Sterne (Universit
 y of Cambridge)
DTSTART:20091103T160000Z
DTEND:20091103T170000Z
UID:TALK20384@talks.cam.ac.uk
CONTACT:Dr Jean-Pascal Pfister
DESCRIPTION:Philip Sterne will present\n\n"Recognizing Sequences of Sequen
 ces":http://www.ploscompbiol.org/article/info:doi%2F10.1371%2Fjournal.pcbi
 .1000464\n\nStefan J. Kiebel\, Katharina von Kriegstein\, Jean Daunizeau\,
  Karl J. Friston. (2009). Plos Comp. Biol. 5(8)\n\nThe brain's decoding of
  fast sensory streams is currently impossible to emulate\, even approximat
 ely\, with artificial agents. For example\, robust speech recognition is r
 elatively easy for humans but exceptionally difficult for artificial speec
 h recognition systems. In this paper\, we propose that recognition can be 
 simplified with an internal model of how sensory input is generated\, when
  formulated in a Bayesian framework. We show that a plausible candidate fo
 r an internal or generative model is a hierarchy of ‘stable heteroclinic
  channels’. This model describes continuous dynamics in the environment 
 as a hierarchy of sequences\, where slower sequences cause faster sequence
 s. Under this model\, online recognition corresponds to the dynamic decodi
 ng of causal sequences\, giving a representation of the environment with p
 redictive power on several timescales. We illustrate the ensuing decoding 
 or recognition scheme using synthetic sequences of syllables\, where sylla
 bles are sequences of phonemes and phonemes are sequences of sound-wave mo
 dulations. By presenting anomalous stimuli\, we find that the resulting re
 cognition dynamics disclose inference at multiple time scales and are remi
 niscent of neuronal dynamics seen in the real brain.\n\n
LOCATION:Cambridge University Engineering Department\, CBL Rm #438 (http:/
 /learning.eng.cam.ac.uk/Public/Directions)
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