Title :
Mutual information for measuring independence of STLmax time series in the epileptic brain
Author :
Mammone, Nadia ; Foresta, Fabio La ; Morabito, Francesco C. ; Versaci, Mario ; Aguglia, Umberto
Author_Institution :
Dept. DIMET, Univ. of Reggio Calabria, Reggio Calabria
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 Renyipsilas 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.
Keywords :
Lyapunov methods; diseases; electroencephalography; medical signal processing; time series; Renyi mutual information; STLmax time series; electrodes; epileptic brain; epileptogenesis; intracranial EEG recording; scalp EEG recording; seizure development; short-term maximum Lyapunov exponent; temporal lobe epilepsy; Chaos; Convergence; Electrodes; Electroencephalography; Entropy; Epilepsy; Mutual information; Scalp; Temporal lobe; Time measurement;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4633914