AUTHOR=Alaçam Deniz , Miller Robyn , Agcaoglu Oktay , Preda Adrian , Ford Judith , Calhoun Vince 

TITLE=A method for capturing dynamic spectral coupling in resting fMRI reveals domain-specific patterns in schizophrenia

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 17 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1078995

DOI=10.3389/fnins.2023.1078995

ISSN=1662-453X

ABSTRACT=Resting-state functional magnetic resonance imaging(rs-fMRI) is a powerful tool for assessing functional brain connectivity. Recent studies have focused on shorter-term connectivity and dynamics in the resting state. However, most of the prior work evaluates changes in time-series correlations. In this study, we focus on time-resolved spectral coupling(assessed via the correlation between power spectra of the windowed time courses) among different brain circuits determined via independent component analysis(ICA). 

Motivated by earlier work suggesting significant spectral differences in people with schizophrenia, we developed an approach to evaluate time-resolved spectral coupling (trSC). Our method is based on the correlation between power spectra of windowed time-courses for pairs of brain components and global quartile values. The number of cells in each quartile were calculated and represented via binary matrices. Also,  we calculated the average cluster size within various subgroups of interest via binary matrices. Lastly, we examined group differences by computing two-sample t-test maps for each averaged count and average cluster size matrices. We evaluated the method by applying it to resting-state data collected from 314 subjects and estimated the spectral coupling using an ICA analysis separating the brain into 47 components and evaluated differences in these measures in people with schizophrenia(SZ) versus healthy controls(HC) and also between males and females.

This approach enables us to observe the change of connectivity strength within each quartile for different subgroups.Both cell count and average cluster size analysis for subgroups indicate a higher connectivity rate in the fourth quartile for the visual network in HC.This indicates increased trSC in visual networks in HC. In other words, this shows that the visual networks in SZ have less mutually consistent spectra. It is also the case that the visual networks are less spectrally correlated on short timescales with networks of all other functional domains.

The results of this study reveal significant differences in the degree to which spectral power profiles are coupled over time. Importantly, there are significant but distinct differences both between males and females and between SZ and HC.Fluctuations over time are complex, and focusing on only time-resolved coupling among time-courses is likely to miss important information.