A new measure of phase synchronization for a pair of time series and seizure focus localization

TL;DR

This paper introduces a new Fourier-based measure of phase synchronization called syn function, enabling more accurate seizure focus localization from EEG data without needing head conductivity information.

Contribution

It proposes a deterministic Fourier transform-based method for phase synchronization measurement, improving seizure localization accuracy over traditional statistical approaches.

Findings

The syn function effectively quantifies neural phase synchronization and asynchronization.

The method improves seizure focus localization accuracy from scalp EEG data.

It does not require knowledge of head electrical conductivity.

Abstract

Defining and measuring phase synchronization in a pair of nonlinear time series are highly nontrivial. This can be done with the help of Fourier transform, when it exists, for a pair of stored (hence stationary) signals. In a time series instantaneous phase is often defined with the help of Hilbert transform. In this paper phase of a time series has been defined with the help of Fourier transform. This gives rise to a deterministic method to detect phase synchronization in its most general form between a pair of time series. Since this is a stricter method than the statistical methods based on instantaneous phase, this can be used for lateralization and source localization of epileptic seizures with greater accuracy. Based on this method a novel measure of phase synchronization, called syn function, has been defined, which is capable of quantifying neural phase synchronization and asynchronization as important parameters of epileptic seizure dynamics. It has been shown that such a strict measure of phase synchronization has potential application in seizure focus localization from scalp electroencephalogram (EEG) data, without any knowledge of electrical conductivity of the head.