Mutual Information for measuring independence of STLmax time series in the epileptic brain

Nadia Mammone, Fabio La Foresta, Francesco C. Morabito, Mario Versaci, Umberto Aguglia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Results in literature show that the convergence of the Short-Term Maximum Lyapunov Exponent (STLmax) time series, extracted from intracranial EEG recorded from patients affected by intractable temporal lobe epilepsy, is linked to the seizure onset. When the STLmax profiles of different electrode sites converge (high entrainment) a seizure is likely to occur. In this paper Renyi's Mutual information (MI) is introduced in order to investigate the independence between pairs of electrodes involved in the epileptogenesis. A scalp EEG recording and an intracranial EEG recording, including two seizures each, were analysed. STLmax was estimated for each critical electrode and then MI between couples of STLmax profiles was measured. MI showed sudden spikes that occurred 8 to 15 min before the seizure onset. Thus seizure onset appears related to a burst in MI: this suggests that seizure development might restore the independence between STLmax of critical electrode sites.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Pages955-960
Number of pages6
DOIs
Publication statusPublished - 2008
Event2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
Duration: Jun 1 2008Jun 8 2008

Other

Other2008 International Joint Conference on Neural Networks, IJCNN 2008
CountryChina
CityHong Kong
Period6/1/086/8/08

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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