title: Cortical activity pattern computation.
abstract: Neural computations are modelled in various ways, but still there is no clear understanding of how the brain performs its computational tasks. This paper presents new results about analysis of neural processes in terms of activity pattern computations. It is shown that it is possible to extract from high-resolution EEG data a first order Markov approximation of a neural communication system employing pattern computations, which is significantly different from similar purely random systems. In our view this result shows that it is likely that neural activity patterns measurable at the macro-level by EEG are correlated with underlying neural computations.
authors.affiliation: School of Computing Science, University of Newcastle, Newcastle Upon Tyne NE1 7RU, UK. peter.andras@ncl.ac.uk
authors.forename: Peter
authors.initials: P
authors.lastname: Andras
authors.forename: Thomas
authors.initials: T
authors.lastname: Wennekers
mesh_terms: D000818:Animals; D002415:Cats; D002540:Cerebral Cortex / Q000502:physiology*; D019295:Computational Biology; D004569:Electroencephalography; D008959:Models, Neurological; D049490:Systems Biology