Spontaneous brain activity is an important biomarker for various neurological and psychological conditions and can bemeasured using resting functional Magnetic Resonance Imaging (rfMRI). Since brain activity during rest is spontaneous,it is not possible to directly compare rfMRI time-courses across subjects. Moreover, the spatial configuration offunctionally specialized brain regions can vary across subjects throughout the cortex limiting our ability to make precisespatial comparisons. We describe a new approach to jointly align and synchronize fMRI data in space and time across agroup of subjects. We build on previously described methods for inter-subject spatial “Hyper-Alignment” and temporalsynchronization through the “BrainSync” transform. We first describe BrainSync Alignment (BSA), a group-basedextension of the pair-wise BrainSync transform, that jointly synchronizes resting or task fMRI data across time for multiplesubjects. We then explore the combination of BSA with Response Hyper-Alignment (RHA) and compare withConnectivity Hyper-Alignment (CHA), an alternative approach to spatial alignment based on resting fMRI. The result ofapplying RHA and BSA is both to produce improved functional spatial correspondence across a group of subjects, and toalign their time-series so that, even for spontaneous resting data, we see highly correlated temporal dynamics athomologous locations across the group. These spatiotemporally aligned data can then be used as an atlas in futureapplications. We explore the relative performance of BSA/RHA and CHA by computing spatial maps of inter-subjectcorrelation of spatially aligned and synchronized rfMRI data. We also perform a validation study by applying the spatialtransforms to z-score maps from an independent task fMRI dataset. Finally, we also explore application of these spatiotemporalalignment methods directly to task fMRI data.
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