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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...
EEG functional connectivity maps, showing the interactions between brain areas in context to the placement of electrodes, were used for the investigation and comparison of three different types of epileptiform activity defined as single spike, spike followed by slow wave and repetitive spike. A nonlinear data-driven method was used to extract connectivity matrices that helped to identify network synchronization...
This study proposes a nonlinear data-driven method to delineate Electroencephalogram (EEG) recordings as either coming from controls or patients with epilepsy. This method uses the probability of recurrence and the correlation between electrodes to extract the phase synchronization and the functional connectivity maps of the brain from interictal EEG data recordings. This newly proposed algorithm...
Background The lives of half a million children in the United States are severely affected due to the alterations in their functional and mental abilities which epilepsy causes. This study aims to introduce a novel decision support system for the diagnosis of pediatric epilepsy based on scalp EEG data in a clinical environment. Methods A new time varying approach for constructing functional connectivity...
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