Multiscale Community-Based Fingerprinting of Signed Functional Networks
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 detection framework that incorporates both correlated and anti-correlated brain activity to iden...
| Authors | Sema Athamnah, Selin Aviyente |
|---|---|
| Primary category | q-bio.NC |
| Published | 25 August 2026 |
| Last updated at source | 25 August 2026 |
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