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Computational Intelligence and Neuroscience
Volume 2007 (2007), Article ID 83416, 18 pages
http://dx.doi.org/10.1155/2007/83416
Research Article

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

1Computational NeuroEngineering Laboratory, Department of Electrical & Computer Engineering, University of Florida, Gainesville 32611, FL, USA
2Department of Computer Science and Electrical Engineering CSEE, OGI School of Science & Engineering, Oregon Health & Science University, Portland, Beaverton 97006, OR, USA
3Optima Neuroscience, Inc., Gainesville 32601, FL, USA
4Malcolm Randal VA Medical Center, Gainesville, FLa 32608, FL, USA

Received 18 February 2007; Accepted 19 August 2007

Academic Editor: Saied Sanei

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.

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.