DocumentCode :
140475
Title :
Gamma (30–80Hz) bicoherence distinguishes seizures in the human epileptic brain
Author :
Cotic, Marija ; Chinvarun, Yotin ; Guirgis, Mirna ; Carlen, Peter L. ; Bardakjian, Berj L.
Author_Institution :
Inst. of Biomater. & Biomed. Eng., Univ. of Toronto, Toronto, ON, Canada
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
4455
Lastpage :
4458
Abstract :
We have applied wavelet bicoherence (BIC) analysis to human iEEG data to characterize non-linear frequency interactions in the human epileptic brain. Bicoherence changes were most prominent in the gamma (30-80 Hz) frequency band, and allowed for the differentiation between seizure and non-seizure states in all patients studied (n=3). While gamma band BIC values increased during seizure activity, this trend was only observed in a select number of electrode(s) located on the implanted patient subdural grids. Several studies have suggested that fast frequencies may play a role in the process of seizure genesis. While the small patient numbers limit the significance of our study, our results highlight the bicoherence of the gamma frequency band (30-80 Hz) as an ictal identifier, and suggest an active role of this fast frequency during seizures.
Keywords :
diseases; electroencephalography; medical signal processing; signal classification; applied wavelet bicoherence analysis; frequency 30 Hz to 80 Hz; gamma bicoherence; gamma frequency band; human epileptic brain; human iEEG data; ictal identifier; nonlinear frequency interactions; nonseizure state; seizure activity; seizures; Couplings; Eigenvalues and eigenfunctions; Electrodes; Epilepsy; Oscillators; Wavelet analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6944613
Filename :
6944613
Link To Document :
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