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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\, Director\,  Institute of Neuroscience and Psychology\,  
 University of Glasgow
DTSTART:20161118T163000Z
DTEND:20161118T180000Z
UID:TALK67105@talks.cam.ac.uk
CONTACT:Louise White
DESCRIPTION:The ultimate goal of cognitive neuroscience is to understand t
 he brain as an organ of information processing.  This will remain difficul
 t unless we understand more directly what information the brain processes 
 when it categorizes the external world.  For example\, our brain can extra
 ct from a face--a powerful social communication tool--information to categ
 orize 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 know
 ledge.  The current state of cognitive neuroscience is similar – we aim 
 to understand the brain as an information processor\, but we do not know w
 hat stimulus information it processes.  Using face categorisations\, I wil
 l present a framework and recent examples that started to address this fun
 damental problem. We start by first isolating what specific information un
 derlies 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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