Neuroccino 15th Dec 2025 - new approach to fmri analysis

Connectome caricatures remove large-amplitude coactivation patterns in resting-state fMRI to emphasize individual differences

Abstract
High-amplitude coactivation patterns are sparsely present during resting-state functional magnetic resonance imaging (fMRI), yet they drive functional connectivity and resemble task activation patterns. However, little research has characterized the remaining majority of the resting-state signal. Here, we introduce caricaturing, a method for projecting resting-state data onto a subspace orthogonal to a manifold of coactivation patterns estimated from task fMRI data. This removes linear combinations of these coactivation patterns from resting-state data to create caricatured connectomes. We used task data from two large-scale neuroimaging datasets to construct a manifold of task coactivation patterns and created caricatured connectomes. These connectomes exhibit lower between-individual similarity and higher identifiability and could be used to predict phenotypic measures, representing individual differences in behavior, often to a greater degree than standard connectomes. Our results show that there is a useful signal beyond the dominant coactivations that drive resting-state functional connectivity, which may better characterize the brain’s intrinsic functional architecture.


Paper link: https://www.nature.com/articles/s4159...