Schedule of Events | Search Abstracts | Invited Symposia | Symposia | Poster Sessions | Data Blitz

Individual Variability in Functional Connectivity Gradients: A Precision fMRI Investigation

Poster Session B - Sunday, March 8, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Andre Zamani¹ (), Shreya Kakachery¹, Kalina Christoff Hadjiilieva¹; ¹University of British Columbia

Functional connectivity gradients are continuous, low-dimensional representations that capture how brain regions differ in their patterns of whole-brain functional connectivity. In doing so, they reveal large-scale patterns of functional organization that are present in functional connectivity, such as the now widely recognized continuum between unimodal and transmodal systems. Despite their increasing use in neuroscientific research, however, functional gradients are largely investigated at the group level where data is averaged across multiple (or many) participants. Such averaging mixes signal from distinct yet spatially adjacent functional networks across individuals, and as such, limits the precision with which gradient scores can be computed for separate networks. Moreover, reliance on group-derived functional gradients obscures potential individual variability in the ordering of functional gradients (i.e., the amount of variance explained by one gradient over another). To address these limitations, we employed a precision fMRI approach, estimating both functional gradients and networks at the individual level using densely sampled participants from the open-access, ultra-high field 7T Natural Scenes Dataset. Functional gradients were computed using the BrainSpace toolbox, and individual-level functional networks were estimated using Multi Session Hierarchical Bayesian Modeling. Distributions of vertex-level gradient scores were then computed for each individually defined functional network and compared across participants. We also evaluated individual differences in the amount of variance explained by different functional gradients. These findings underscore the value of precision fMRI for advancing our understanding of functional gradients and their individual variability.

Topic Area: METHODS: Neuroimaging