Are you thinking what I'm thinking? Synchronization of resting fMRI time-series across subjects - Joshi, Anand A.; Chong, Minqi; Li, Jian; Choi, Soyoung; Leahy, Richard M. (NeuroImage (Orlando, Fla.), 2018)
We describe BrainSync, an orthogonal transform that allows direct comparison of resting fMRI (rfMRI) time-series across subjects. For this purpose, we exploit the geometry of the rfMRI signal space to propose a novel orthogonal transformation that synchronizes rfMRI time-series across sessions and subjects. When synchronized, rfMRI signals become approximately equal at homologous locations across subjects. The method is based on the observation that rfMRI data exhibit similar connectivity patterns across subjects, as reflected in the pairwise correlations between different brain regions. We show that if the data for two subjects have similar correlation patterns then their time courses can be approximately synchronized by an orthogonal transformation. This transform is unique, invertible, efficient to compute, and preserves the connectivity structure of the original data for all subjects. Analogously to image registration, where we spatially align structural brain images, this temporal synchronization of brain signals across a population, or within-subject across sessions, facilitates cross-sectional and longitudinal studies of rfMRI data. The utility of the BrainSync transform is illustrated through demonstrative simulations and applications including quantification of rfMRI variability across subjects and sessions, cortical functional parcellation across a population, timing recovery in task fMRI data, comparison of task and resting state data, and an application to complex naturalistic stimuli for annotation prediction. [Display omitted] •.BrainSync is an orthogonal transform that allows direct comparison of fMRI signals across subjects and scans.•The BrainSync transform is lossless and preserves correlation structures.•The transform is efficient to compute, based on simple intuitive assumptions, parameter free, and data driven.•Utility illustrated through joint cortical parcellation of a population, timing recovery in task fMRI, and annotation prediction for complex naturalistic stimuli.