Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

ABSTRACT:

Objective

To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patterns estimated during EEG periods without visible pathological activity.

Methods

Resting-state high-density EEG recording data from 20 left TLE patients, 20 right TLE patients and 35 healthy controls was used. Epochs without interictal spikes were selected. The cortical source activity was obtained for 82 regions of interest and whole-brain directed functional connectivity was estimated in the theta, alpha and beta frequency bands. These connectivity values were then used to build a classification system based on two two-class Random Forests classifiers: TLE vs healthy controls and left vs right TLE. Feature selection and classi

SUBMITTER: Verhoeven T 

PROVIDER: S-EPMC5842753 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature