Functional connectivity gradients depend on cortical sampling position and brain state

Authors

Li, M., Ding, Z., Gore, J. C.

Abstract

Functional-connectivity analyses often treat signals sampled from nearby cortical positions as interchangeable, despite anatomical and hemodynamic transitions at the gray-white boundary. We tested whether sampling position constitutes a state-sensitive dimension of macroscale functional organization. In 176 Human Connectome Project young adults with four 7 T resting-state and four movie-watching runs, BOLD time series were sampled from subject-specific midthickness and gray-white-boundary surfaces, summarized across 400 cortical parcels, and embedded in a common functional-gradient space. Movie viewing reduced principal-gradient separation between surfaces, but this effect was spatially heterogeneous: Visual, Limbic and Default networks converged, whereas Salience/ventral-attention cortex differentiated. Shapley decomposition and counterfactual analyses showed that the state change reflected coordinated reconfiguration of both surface representations rather than one surface approaching the other. Changes in the original connectivity profiles tracked gradient changes, indicating that the result was not solely introduced by embedding. Both surfaces also exhibited stimulus-locked intersubject functional connectivity during movies. However, stimulus-shared separation captured only part of movie-state organization and did not explain the movie-minus-rest change. Finally, in 172 matched participants, resting-state separation maps generalized from 7 T to 3 T, whereas absolute magnitude and cross-field individual ranking were less stable. These findings establish cortical sampling position as an interpretable measurement dimension of functional-connectivity geometry. Its spatial organization is reproducible across acquisitions, but its magnitude and state dependence vary, emphasizing that where BOLD signals are sampled relative to the cortical boundary can shape conclusions about macroscale brain organization.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 20 Jul 2026.

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