It's the Geometry, Not the Model: Effective Rank and Subspace Alignment in Functional Connectivity Classification

The study investigates how the geometry of resting‑state functional connectivity (FC) influences classification of brain phenotypes and cross‑site transfer, rather than focusing on model design. It finds that FC variation across subjects is concentrated in a small effective subspace, and that differences in subspace orientation across cohorts can limit transfer even when effective ranks are similar. By projecting onto leading components at the effective‑rank scale, most classification performance is retained, and the alignment of site‑specific subspaces predicts transfer performance. "whyItMatters":"The findings highlight that aligning effective subspaces across sites is crucial for improving generalization of FC‑based classifiers, offering a geometric diagnostic for cross‑site harmonization efforts."

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