The part and the whole: how single nodes contribute to large-scale phase-locking in functional EEG networks

Abstract

Objective: The application of signal analysis techniques to electroencephalographic (EEG) recordings from epilepsy patients shows that epilepsy involves not only altered neuronal synchronization but also the reorganization of functional EEG networks. This study aims to assess the large-scale phase-locking of such functional networks and how individual network nodes contribute to this collective dynamics. Methods: We analyze the EEG recorded before, during and after seizures from sixteen patients with pharmacoresistant focal-onset epilepsy. The data is filtered to low (4–30 Hz) and high (80–150 Hz) requencies. We define the multivariate phase-locking measure and the univariate phase-locking contribution measure. Surrogate signals are used to estimate baseline results expected under the null hypothesis that the EEG is a correlated linear stochastic process. Results: On average, nodes from inside and outside the seizure onset zone (SOZ) increase and decrease, respectively, the large-scale phase-locking. This difference becomes most evident in a joint analysis of low and high frequencies. Conclusions: Nodes inside and outside the SOZ play opposite roles for the large-scale phase-locking in functional EEG network in epilepsy patients. Significance: The application of the phase-locking contribution measure to EEG recordings from epilepsy patients can potentially help in localizing the SOZ.