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Lookup NU author(s): Dr Peter Andras
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Cortical dynamics can be recorded in various ways. Theoretical works suggest that analyzing the dynamics of recorded activities might reveal the workings of the underlying neural system. Here we describe the extraction of an activity pattern language that characterizes the dynamics of high-resolution EEG data recorded. We show that the language can be formulated in terms of probabilistic continuation rules which predict reasonably well the dynamics of activity patterns in the data.
Author(s): Andras P
Editor(s): Berthold, M.R., Glen, R., Fischer, I.
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Computational Life Sciences II: Second International Symposium
Year of Conference: 2006
Pages: 247-256
ISSN: 0302-9743 (Print) 1611-3349 (Online)
Publisher: Springer
URL: http://dx.doi.org/10.1007/11875741_24
DOI: 10.1007/11875741_24
Library holdings: Search Newcastle University Library for this item
Series Title: Lecture Notes in Computer Science
ISBN: 9783540457671
