Evaluating phase synchronization methods in fMRI: a comparison study and new approaches

TL;DR

This study compares phase synchronization methods in fMRI, introduces a new approach called CRP, and demonstrates its advantages in accurately capturing dynamic brain connectivity patterns.

Contribution

The paper introduces CRP, a novel phase synchronization measure, and evaluates its performance against existing methods using simulations and real rs-fMRI data.

Findings

CRP outperforms other methods in simulations and real data.

CRP effectively detects transitions in brain connectivity.

CRP facilitates clustering of brain states by unfolding PS distribution.

Abstract

In recent years there has been growing interest in measuring time-varying functional connectivity between different brain regions using resting-state functional magnetic resonance imaging (rs-fMRI) data. One way to assess the relationship between signals from different brain regions is to measure their phase synchronization (PS) across time. There are several ways to perform such analyses, and here we compare methods that utilize a PS metric together with a sliding window, referred to here as windowed phase synchronization (WPS), with those that directly measure the instantaneous phase synchronization (IPS). In particular, IPS has recently gained popularity as it offers single time-point resolution of time-resolved fMRI connectivity. In this paper, we discuss the underlying assumptions required for performing PS analyses and emphasize the necessity of band-pass filtering the data to obtain valid results. We review various methods for evaluating PS and introduce a new approach within the IPS framework denoted the cosine of the relative phase (CRP). We contrast methods through a series of simulations and application to rs-fMRI data. Our results indicate that CRP outperforms other tested methods and overcomes issues related to undetected temporal transitions from positive to negative associations common in IPS analysis. Further, in contrast to phase coherence, CRP unfolds the distribution of PS measures, which benefits subsequent clustering of PS matrices into recurring brain states.