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High-resolution multiple-unit EEG in cat auditory cortex reveals large spatio-temporal stochastic interactions

Lookup NU author(s): Dr Peter Andras


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It has been argued that information processing in the cortex is optimised with regard to certain information theoretic principles. We have, for instance, recently shown that spike-timing dependent plasticity can improve an information-theoretic measure called spatio-temporal stochastic interaction which captures how strongly a set of neurons cooperates in space and time. Systems with high stochastic interaction reveal Poisson spike trains but nonetheless occupy only a strongly reduced area in their global phase space, they reveal repetiting but complex global activation patterns, and they can be interpreted as computational systems operating on selected sets of collective patterns or "global states" in a rule-like manner. In the present work we investigate stochastic interaction in high-resolution EEG-data from cat auditory cortex. Using Kohonen maps to reduce the high-dimensional dynamics of the system, we are able to detect repetiting system states and estimate the stochastic interaction in the data, which turns out to be fairly high. This suggests an organised cooperation in the underlying neural networks which cause the data and may reflect generic intrinsic computational capabilities of the cortex. © 2006 Elsevier Ireland Ltd. All rights reserved.

Publication metadata

Author(s): Wennekers T, Ay N, Andras P

Publication type: Article

Publication status: Published

Journal: BioSystems

Year: 2007

Volume: 89

Issue: 1-3

Pages: 190-197

Print publication date: 01/05/2007

ISSN (print): 0303-2647

ISSN (electronic): 1872-8324

Publisher: Elsevier


DOI: 10.1016/j.biosystems.2006.04.017

PubMed id: 17188422


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