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

Kenji Yoshinaga,Masao Matsuhashi,Ryosuke Takahashi,Tatsuya Mima,Akio Ikeda,Hidenao Fukuyama,Takashi Hanakawa

doi:10.3389/fnins.2020.00648

Abstract

Phase synchronization measures are widely used for investigating inter-regional 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 amplitude-dependent measures, ImCoh followed by wPLI, may have the advantage in detecting stimulus-induced FCs.

Highlights

Functional integration of multiple regions in the central nervous system is an important concept for understanding normal brain function (Ramnani et al, 2004; Stevens, 2009) and the pathophysiology of neuropsychiatric disorders (Stam, 2010; Pettersson-Yeo et al, 2011)
In all 63 datasets, somatosensory-evoked fields (SEFs) were visually identified in the channels over the contralateral SI to the stimulus (c-SI) and ipsilateral to the stimulus (i-SII)
Conspicuous stimulus-induced functional connectivity (FC) were found during a period of 50–250 ms after the stimulus and in the frequencies ranging from 3 Hz to 12 Hz in all FC measures (Figure 3)

Summary

Introduction

Functional integration of multiple regions in the central nervous system is an important concept for understanding normal brain function (Ramnani et al, 2004; Stevens, 2009) and the pathophysiology of neuropsychiatric disorders (Stam, 2010; Pettersson-Yeo et al, 2011). Functional integration has been extensively investigated using measures of brain connectivity, Comparison of Phase Synchronization Methods and the development of methods for quantifying brain connectivity is a growing field in human neuroscience (Sporns, 2011; Stam and van Straaten, 2012). Dynamics of brain connectivity are investigated using either functional connectivity (FC), effective connectivity, or both (van Diessen et al, 2015). FC is defined as the statistical dependence of neural signals across spatially remote brain regions (Sporns et al, 2004; Fingelkurts et al, 2005), which can provide prerequisite knowledge for effective connectivity analysis. Because of the simplicity in computing (Bullmore and Sporns, 2009; Bruña et al, 2018), FC analysis is commonly applied to the exploration and exploitation of neuroimaging and electrophysiological data

Objectives

Methods

Results

Discussion

Conclusion