SOURCE-LINKED INTELLIGENCE

Multiscale Community-Based Fingerprinting of Signed Functional Networks

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Objective: Recent studies demonstrate that functional connectomes contain subject-specific signatures, or \textit{fingerprints}, that can identify individuals across repeated sessions and tasks. Existing methods mostly rely on edge-level features that are sensitive to noise, difficult to interpret, and limited in their ability to generalize across tasks and datasets. Methods: We propose a multiscale community-based functional connectome fingerprinting framework that characterizes each individual by the mesoscale structure of their functional networks. We introduce a signed multilayer community

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