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SUMMARY:Brain algorithmics: reverse engineering dynamic information proces
 sing in brain networks from EEG/MEG time series  - Prof. Philippe G. Schyn
 s\, FRSE\, FRSA Institute of Neuroscience and Psychology\, Director Univer
 sity of Glasgow
DTSTART:20160311T163000Z
DTEND:20160311T180000Z
UID:TALK63251@talks.cam.ac.uk
CONTACT:Louise White
DESCRIPTION:he ultimate goal of cognitive neuroscience is to understand th
 e brain as an organ of information processing.  This will remain difficult
  unless we understand more directly what information the brain processes w
 hen it categorizes the external world.  For example\, our brain can extrac
 t from a face--a powerful social communication tool--information to catego
 rize identity\, age\, gender\, ethnicity\, emotion\, personality and even 
 health. Though our brain knows what information to use for each task\, as 
 information receivers we typically do not have direct access to this knowl
 edge.  The current state of cognitive neuroscience is similar – we aim t
 o understand the brain as an information processor\, but we do not know wh
 at stimulus information it processes.  Using face categorisations\, I will
  present a framework and recent examples that started to address this fund
 amental problem. We start by first isolating what specific information und
 erlies a given face categorization\, and then we examine where\, when and 
 how the brain networks process this information.
LOCATION:Ground Floor Lecture Theatre\, Department of Psychology
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