NeurIPS: Neuro-anatomical Inductive Priors for Sphere-based Brain Decoding

ArXi:2605.24993v1 Announce Type: new Current fMRI decoders face a performance-fidelity trade-off where efficient ID encoders outperform geometrically faithful surface-based models. We argue this is partly driven by inefficient surface tokenization and the failure to use anatomy as a predictive signal. We present NeurIPS, a framework that improves surface-based decoding by reframing anatomical variation from a nuisance to a powerful inductive prior.