Fig. 1: Study overview.

a Estimating temporal variability of structure-function coupling (SFC). Step 1: Estimation of edge time series with the dimensionality of 308 × 308 × time via computing the element-wise product of pairwise Z-scored fMRI signals. Step 2: Estimation of morphometric similarity connectivity with the dimensionality of 308 × 308 based on nine sMRI and dMRI features. Step 3: The regional time-resolved SFC series, with the dimensionality of 308 × time, is computed by correlating a region’s morphometric similarity and functional co-fluctuation profile at each time point; subsequently, the temporal variability of dynamic SFC is quantified by fuzzy entropy. b Behavioral partial least squares (PLS) analysis. PLS is adopted to delineate multivariate relationships between SFC variability and 59 behavioral measures spanning multiple domains of cognition, emotion, motor, sensory, alertness, and personality. c Transcriptional decoding of SFC temporal variability. Imaging-transcriptomic associations are revealed by PLS, and enrichment analyses are conducted using PLS1 genes. d Neurotransmitter analysis of SFC temporal variability. Spatial correlations between SFC variability and neurotransmitter densities are examined, and a multiple linear regression model is fitted to predict SFC variability from receptor distributions.