Information processing algorithms in the brain

Schyns, P.G. , Gosselin, F. and Smith, M. (2009) Information processing algorithms in the brain. Trends in Cognitive Sciences, 13(1), pp. 20-26. (doi: 10.1016/j.tics.2008.09.008) (PMID:19070533)

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If the brain is a machine that processes information, then its cognitive activity can be interpreted as a set of information processing states linking stimulus to response (i.e. as a mechanism or an algorithm). The cornerstone of this research agenda is the existence of a method to translate the measurable states of brain activity into the information processing states of a cognitive theory. Here, we contend that reverse correlation methods can provide this translation and we frame the transitions between information processing states in the context of automata theory. We illustrate, using examples from visual cognition, how this novel framework can be applied to understand the information processing algorithms of the brain in cognitive neuroscience.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Schyns, Professor Philippe
Authors: Schyns, P.G., Gosselin, F., and Smith, M.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
College of Science and Engineering > School of Psychology
Journal Name:Trends in Cognitive Sciences
Publisher:Elsevier Ltd.
ISSN (Online):1879-307X
Published Online:12 December 2008

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
415511Cortical networks for flexible categorisationsPhilippe SchynsBiotechnology and Biological Sciences Research Council (BBSRC)BB/D01400X/1INP - CENTRE FOR COGNITIVE NEUROIMAGING
449881Social interaction - a cognitive-neurosciences approachSimon GarrodEconomic & Social Research Council (ESRC)ES/E020933/1INP - CENTRE FOR COGNITIVE NEUROIMAGING