State-transition dynamics of resting-state functional magnetic resonance imaging data: Model comparison and test-to-retest analysis

TL;DR

This study extends EEG microstate analysis techniques to resting-state fMRI data, demonstrating comparable clustering quality and high test-retest reliability, indicating potential for individual fingerprinting.

Contribution

The paper introduces a method for analyzing state-transition dynamics in fMRI data, showing its reliability and potential for individual identification, which was less explored before.

Findings

Clustering quality in fMRI is comparable to EEG microstate analysis.

Test-retest reliability is higher within individuals than between individuals.

State-transition dynamics can discriminate individuals in fMRI data.

Abstract

Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating properties of the estimated state-transition dynamics to observables such as cognition and behavior. While microstate analysis has been widely employed to analyze EEG data, its use remains less prevalent in functional magnetic resonance imaging (fMRI) data, largely due to the slower timescale of such data. In the present study, we extend various data clustering methods used in EEG microstate analysis to resting-state fMRI data from healthy humans to extract their state-transition dynamics. We show that the quality of clustering is on par with that for various microstate analyses of EEG data. We then develop a method for examining test-retest reliability of the discrete-state transition dynamics between fMRI sessions and show that the within-participant test-retest reliability is higher than between-participant test-retest reliability for different indices of state-transition dynamics, different networks, and different data sets. This result suggests that state-transition dynamics analysis of fMRI data could discriminate between different individuals and is a promising tool for performing fingerprinting analysis of individuals.