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Adv."],"published-print":{"date-parts":[[2026,8,7]]},"abstract":"<jats:p>\n                    Early detection and prevention of psychiatric disorders, particularly depression, remain as major global health challenges, yet reliable tools for identifying individuals before symptom onset are lacking. Here, we combine functional neuroimaging with computational modeling to identify a mechanistic biomarker of depression risk. In a population-based adolescent cohort (IMAGEN,\n                    <jats:italic toggle=\"yes\">N<\/jats:italic>\n                    \u00a0=\u00a01332), we found that weakened neural representations of emotional signals were linked to depressive symptoms. Perturbation experiments in a brain-aligned deep learning model showed that this deficit reflects overregularized emotion perception, producing a negative perceptual bias. A neurocomputational signature of this mechanism predicted depression symptom onset up to 4 years later at the IMAGEN follow-up (\n                    <jats:italic toggle=\"yes\">N<\/jats:italic>\n                    \u00a0=\u00a0725), was associated with both a genetic-risk variant and polygenic risk for depression, and improved depression classification in a patient cohort (STRATIFY,\n                    <jats:italic toggle=\"yes\">N<\/jats:italic>\n                    \u00a0=\u00a0411). These findings suggest a possible mechanism linking genetic vulnerability to altered emotion perception and future depression, and propose a predictive computational marker with potential for early detection and prevention.\n                  <\/jats:p>","DOI":"10.1126\/sciadv.aed0772","type":"journal-article","created":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:59:18Z","timestamp":1786125558000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":0,"title":["Deep learning reveals a neurocomputational mechanism predicting depression risk in adolescents"],"prefix":"10.1126","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3598-2437","authenticated-orcid":true,"given":"Han","family":"Lu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Shenzhen University, Shenzhen, 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of Psychiatry and Psychotherapy, University of T\u00fcbingen and German Center for Mental Health (DZPG), Site T\u00fcbingen, Germany."},{"name":"Department of Psychiatry and Psychotherapy, Technische Universit\u00e4t Dresden, Dresden, Germany."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7352-1745","authenticated-orcid":true,"given":"Barbara J.","family":"Sahakian","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK."},{"name":"Behavioural and Clinical Neuroscience Institute, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5061-2820","authenticated-orcid":true,"given":"Christelle","family":"Langley","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK."},{"name":"Behavioural and 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College London, London SE5 8AF, UK."},{"name":"School of Psychology, Institute for Mental Health, University of Birmingham, Birmingham, UK."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lauren","family":"Robinson","sequence":"additional","affiliation":[{"name":"Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King\u2019s College London, London SE5 8AF, UK."},{"name":"Oxford Institute of Clinical Psychology Training and Research, Oxford University, Oxford, UK."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4600-7158","authenticated-orcid":true,"given":"Nilakshi","family":"Vaidya","sequence":"additional","affiliation":[{"name":"Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charit\u00e9 Universit\u00e4tsmedizin Berlin, 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