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Conventional neuroimaging methods assume linearity and stationarity, failing to capture frequency-specific neural computations. We introduce Multi-Band Brain Net (MBBN), a transformer-based framework that models frequency-specific spatiotemporal brain dynamics from fMRI. MBBN integrates biologically grounded frequency decomposition with multi-band self-attention, enabling discovery of frequency-dependent network interactions. Trained on 49,673 individuals across three large-scale cohorts (UK Biobank, Adolescent Brain Cognitive Development Study (ABCD), Autism Brain Imaging Data Exchange (ABIDE)), MBBN achieves state-of-the-art performance in predicting psychiatric and cognitive outcomes\u2014including major depressive disorder (MDD), attention-deficit\/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD)\u2014with AUROC improvements of up to 41.36% alongside strong cognitive intelligence prediction. Frequency-resolved analyses reveal disorder-specific signatures: in ADHD, high-frequency fronto-sensorimotor connectivity is attenuated and opercular somatosensory\u00a0nodes emerge as dynamic hubs; in ASD, orbitofrontal-somatosensory circuits show focal high-frequency disruption alongside enhanced ultra-low-frequency coupling between the temporo-parietal junction and prefrontal cortex. By combining biologically\u00a0informed frequency decomposition with transformer architecture, MBBN delivers interpretable biomarkers and improved prediction of psychiatric and cognitive traits.<\/jats:p>","DOI":"10.1038\/s42003-026-10011-7","type":"journal-article","created":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T05:54:35Z","timestamp":1778219675000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Learning brain dynamics across distinct scaling regimes reveals psychiatric signatures"],"prefix":"10.1038","volume":"9","author":[{"given":"Sangyoon","family":"Bae","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junbeom","family":"Kwon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinjae","family":"Yoo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiook","family":"Cha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,8]]},"reference":[{"key":"10011_CR1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-04723-6","volume":"9","author":"J Taghia","year":"2018","unstructured":"Taghia, J. et al. 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