Comparison of Phase Synchronization Measures for Identifying Stimulus-Induced Functional Connectivity in Human Magnetoencephalographic and Simulated Data

Abstract

Phase synchronization measures are widely used for investigating interregional functional connectivity (FC) of brain oscillations, but which phase synchronization measure should be chosen for a given experiment remains unclear. Using neuromagnetic brain signals recorded from healthy participants during somatosensory stimuli, we compared the performance of four phase synchronization measures, imaginary part of phase-locking value, imaginary part of coherency (ImCoh), phase lag index and weighted phase lag index (wPLI), for detecting stimulus-induced FCs between the contralateral primary and ipsilateral secondary somatosensory cortices. The analyses revealed that ImCoh exhibited the best performance for detecting stimulus-induced FCs, followed by the wPLI. We found that amplitude weighting, which is related to computing both ImCoh and wPLI, effectively attenuated the influence of noise contamination. A simulation study modeling noise-contaminated periodograms replicated these findings. The present results suggest that the amplitudedependent measures, ImCoh followed by wPLI, may have the advantage in detecting stimulus-induced FCs.

How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls

“…For example Wang with co-workers [30] indicated that there is about 42 methods, while Bakhshayesh et al [31] showed that 26 types of FC-algorithms might be applied to analyze synchronizations between non-stationary, non-linear signal, such as this coming from EEG recordings. Unfortunately, only recently have research and computational begun to evaluate which of these methods give rise to relatively repetitive, closely related to phenotypic characteristics connection patterns that show significant inter-individual and modest intra-individual variance [29,32,33]. Despite some advances in assessing FC measures in terms of their validity and reproducibility, according to our knowledge, the recognition of how different FC-indexes may affect the scope and direction of differences schizophrenia patients and healthy controls regarding the parameters of the global neural networks configuration described in the language of the graph theory has not yet been carried out.…”

Multiscale Temporal Self-Attention and Dynamical Graph Convolution Hybrid Network for EEG-Based Stereogram Recognition

“…First, Phase Locking Value is applied to depict the functional connectivity for constructing the matrix in the dynamic graph convolution module. However, studies [58], [59] have shown that the Phase Locking Value exists some problems, such as active reference electrodes and volume conduction when measuring functional connectivity. Therefore, in our future work, we will research for the optimal metrics to assess functional connectivity for stereogram recognition task.…”

Learning Spatiotemporal Graph Representations for Visual Perception Using EEG Signals

“…Unlike other studies, we combine local and distant connections of the brain by constructing the adjacency matrix using electrode distance and functional connectivity. There are multiple ways to estimate functional connectivity, a recent study proves that weighted phase lag index (wPLI) attenuated the influence of noise contamination [24] and volume conduction [25], therefore, we decided to use wPLI for estimating the connectivity between a pair electrodes. The CNN extracts channel-wise features, specifically timedomain features that could be ignored by the GCNN since it gives more importance to the spatial relation between electrodes.…”