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

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 m...

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Detalles Bibliográficos
Autores principales: Hegde, Anant, Erdogmus, Deniz, Shiau, Deng S., Principe, Jose C., Sackellares, Chris J.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2248704/
https://www.ncbi.nlm.nih.gov/pubmed/18317515
http://dx.doi.org/10.1155/2007/83416
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author Hegde, Anant
Erdogmus, Deniz
Shiau, Deng S.
Principe, Jose C.
Sackellares, Chris J.
author_facet Hegde, Anant
Erdogmus, Deniz
Shiau, Deng S.
Principe, Jose C.
Sackellares, Chris J.
author_sort Hegde, Anant
collection PubMed
description 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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spelling pubmed-22487042008-03-03 Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography Hegde, Anant Erdogmus, Deniz Shiau, Deng S. Principe, Jose C. Sackellares, Chris J. Comput Intell Neurosci Research Article 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. Hindawi Publishing Corporation 2007 2007-11-13 /pmc/articles/PMC2248704/ /pubmed/18317515 http://dx.doi.org/10.1155/2007/83416 Text en Copyright © 2007 Anant Hegde et al. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Research Article
Hegde, Anant
Erdogmus, Deniz
Shiau, Deng S.
Principe, Jose C.
Sackellares, Chris J.
Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
title Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
title_full Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
title_fullStr Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
title_full_unstemmed Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
title_short Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
title_sort clustering approach to quantify long-term spatio-temporal interactions in epileptic intracranial electroencephalography
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2248704/
https://www.ncbi.nlm.nih.gov/pubmed/18317515
http://dx.doi.org/10.1155/2007/83416
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