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arXiv · 2602.05807

SpARCD: A Spectral Graph Framework for Revealing Differential Functional Connectivity in fMRI Data

Shira Yoffe·Ziv Ben-Zion·Guy Gurevitch·Talma Hendler·Malka Gorfine·Ariel Jaffe
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Abstract

Identifying brain regions that exhibit altered functional connectivity between cognitive or emotional states is a fundamental problem in neuroscience. We propose SpARCD (Spectral Analysis for Revealing Connectivity Differences), a statistical framework for detecting detecting condition-specific patterns of functional connectivity. SpARCD uses distance correlation, a dependence measure sensitive to both linear and nonlinear associations, to construct weighted region-wise connectivity graphs for each condition. A differential operator obtained through spectral filtering is then used to identify connectivity changes via its leading eigenvectors. To assess statistical significance, we develop a permutation-based testing procedure that yields interpretable region-level significance maps. We establish finite-sample validity of the permutation test and derive asymptotic guarantees for the stability of the resulting region rankings. Simulation studies demonstrate improved power relative to conventional edge-wise and univariate approaches, particularly in settings with nonlinear dependence structures. We applied SpARCD to fMRI data from 113 individuals with early-stage PTSD and 42 controls during emotional and neutral task conditions. The method identified distinct connectivity networks associated with visual processing in both PTSD and control participants. Resting-state comparisons between PTSD and control participants highlighted similar visual networks. SpARCD provides a statistically rigorous and computationally efficient framework for comparing high-dimensional connectivity patterns.

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Shira Yoffe, Ziv Ben-Zion, Guy Gurevitch, Talma Hendler, Malka Gorfine, Ariel Jaffe. 2026-02-05. SpARCD: A Spectral Graph Framework for Revealing Differential Functional Connectivity in fMRI Data. https://arxiv.org/abs/2602.05807

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