Abstract

This paper introduces a new method for the quantification and analysis of functional connectivity from electroencephalogram (EEG) by implementing cross-correlation method. The recorded clinical EEG signals are segmented and categorized into three types of epileptiform discharges (ED), interictal spike, spike and slow wave complex, and repetitive spike and slow wave complexes. The extracted EEG functional connectivity in different frequency bands were quantified and analyzed to identify characterizing patterns between each type of ED. Results revealed that the number of connections from different epileptogenic biomarkers and calculated for each frequency band were statistically different. Such functional connectivity maps reveal distinctive patterns that can be used to classify these types of ED.

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