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Titolo:
Epileptic seizures are characterized by changing signal complexity
Autore:
Bergey, GK; Franaszczuk, PJ;
Indirizzi:
Johns Hopkins Univ, Sch Med, Johns Hopkins Epilepsy Ctr, Dept Neurol, Baltimore, MD 21287 USA Johns Hopkins Univ Baltimore MD USA 21287 Neurol, Baltimore, MD 21287 USA
Titolo Testata:
CLINICAL NEUROPHYSIOLOGY
fascicolo: 2, volume: 112, anno: 2001,
pagine: 241 - 249
SICI:
1388-2457(200102)112:2<241:ESACBC>2.0.ZU;2-P
Fonte:
ISI
Lingua:
ENG
Soggetto:
TEMPORAL-LOBE EPILEPSY; PRIMARY EPILEPTOGENIC AREA; BRAIN ELECTRICAL-ACTIVITY; TIME-SERIES ANALYSIS; EEG SIGNALS; DYNAMICS; CHAOS; RECORDINGS; NONLINEARITY; TRANSFORM;
Keywords:
seizures; epilepsy; termination; complexity; signal analysis; electroencephalography;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
27
Recensione:
Indirizzi per estratti:
Indirizzo: Bergey, GK Johns Hopkins Univ, Sch Med, Johns Hopkins Epilepsy Ctr, Dept Neurol, Meyer 2-147,600 N Wolfe St, Baltimore, MD 21287 USA Johns Hopkins Univ Meyer 2-147,600 N Wolfe St Baltimore MD USA 21287
Citazione:
G.K. Bergey e P.J. Franaszczuk, "Epileptic seizures are characterized by changing signal complexity", CLIN NEU, 112(2), 2001, pp. 241-249

Abstract

Objective: Epileptic seizures are brief episodic events resulting from abnormal synchronous discharges from cerebral neuronal networks. The traditional methods of signal analysis are limited by the rapidly changing nature ofthe EEG signal during a seizure. Time-frequency analyses, however, such asthose produced by the matching pursuit (MP) method can provide continuous decompositions of recorded seizure activity. These accurate decompositions can allow for more detailed analyses of the changes in complexity of the signal that may accompany seizure evolution. Methods: The MP algorithm was applied to provide time-frequency decompositions of entire seizures recorded from depth electrode contacts in patients with intractable complex partial seizures of mesial temporal onset. The results of these analyses were compared with signals generated from the Duffing equation that represented both limit cycle and chaotic behavior. Results: Seventeen seizures from 12 different patients were analyzed. These analyses reveal that early in the seizure, the most organized, rhythmic seizure activity is more complex than limit cycle behavior, and that signal complexity increases further later in the seizure. Conclusions: Increasing complexity routinely precedes seizure termination. This may reflect progressive desynchronization. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 26/01/20 alle ore 10:58:03