Fast Whole-Brain, Geometry-Aware Functional Alignment for Cross-Subject Decoding

• URL: http://arxiv.org/abs/2607.10931v1
• Date: Sun, 12 Jul 2026 21:37:33 GMT
• Title: Fast Whole-Brain, Geometry-Aware Functional Alignment for Cross-Subject Decoding
• Abstract summary: Inter-individual variability in brain response patterns limits the development of decoders that generalize across individuals.<n>We introduce a new functional alignment method for fMRI, SpectralOT, that embeds cortical geometry into Laplace-Beltrami eigenmodes along functional data.
• Score: 29.425034490742945
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Decoding brain activity is useful for characterizing brain processes and understanding the functional architecture underlying cognition. However, the inter-individual variability in brain response patterns limits the development of decoders that generalize across individuals. A solution to this challenge is functional alignment: aligning functional data across individuals before training population-level decoders. The core issue is to strike the balance between aligning functional features and preserving the anatomical structure, while maintaining computational efficiency. We introduce a new functional alignment method for fMRI, SpectralOT, that embeds cortical geometry into Laplace-Beltrami eigenmodes along functional data to regularize the alignment.

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