Computational Intelligence and Neuroscience

Computational Intelligence and Neuroscience / 2007 / Article
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EEG/MEG Signal Processing

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Research Article | Open Access

Volume 2007 |Article ID 083416 | https://doi.org/10.1155/2007/83416

Anant Hegde, Deniz Erdogmus, Deng S. Shiau, Jose C. Principe, Chris J. Sackellares, "Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography", Computational Intelligence and Neuroscience, vol. 2007, Article ID 083416, 18 pages, 2007. https://doi.org/10.1155/2007/83416

Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography

Academic Editor: Saied Sanei
Received18 Feb 2007
Accepted19 Aug 2007
Published12 Nov 2007

Abstract

Abnormal dynamical coupling between brain structures is believed to be primarily responsible for the generation of epileptic seizures and their propagation. In this study, we attempt to identify the spatio-temporal interactions of an epileptic brain using a previously proposed nonlinear dependency measure. Using a clustering model, we determine the average spatial mappings in an epileptic brain at different stages of a complex partial seizure. Results involving 8 seizures from 2 epileptic patients suggest that there may be a fixed pattern associated with regional spatio-temporal dynamics during the interictal to pre-post-ictal transition.

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Copyright © 2007 Anant Hegde et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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