Establishing and validating a new source analysis method using phase

Abstract

Electroencephalogram (EEG) measures the brain oscillatory activity non-invasively. The localization of deep brain generators of the electric fields is essential for understanding neuronal function in healthy humans and for damasking specific regions that cause abnormal activity in patients with neurological disorders. The aim of this study was to test whether the phase estimation from scalp data can be reliably used to identify the number of dipoles in source analyses. The steps performed included: i) modeling different phasic oscillatory signals using auto-regressive processes at a particular frequency, ii) simulation of two different noises, namely white and colored noise, having different signal-to-noise ratios, iii) simulation of dipoles at different areas in the brain and iv) estimation of the number of dipoles by calculating the phase differences of the simulated signals. Moreover we applied this method of source analysis on real data from temporal lobe epilepsy (TLE) patients. The analytical framework was successful in identifying the sources and their orientations in the simulated data and identified the epileptogenic area in the studied patients which was confirmed by pathological studies after TLE surgery.