Article
Deep learning reveals a neurocomputational mechanism predicting depression risk in adolescents.
Science advances - 7 Aug 2026
Lu Han, Yan Xiaoqian, Becker Benjamin, Heinz Andreas, Sahakian Barbara J, Langley Christelle, Zuo Zhaoyu, Cao Luolong, Zhang Zuo, Robinson Lauren, Vaidya Nilakshi, Winterer Jeanne, King Sinead, Walton Charlotte, Banaschewski Tobias, Barker Gareth J, Bokde Arun L W, Brühl Rüdiger, Flor Herta, Garavan Hugh, Gowland Penny, Grigis Antoine, Lemaitre Herve, Martinot Jean-Luc, Martinot Marie-Laure Paillère, Artiges Eric, Nees Frauke, Orfanos Dimitri Papadopoulos, Poustka Luise, Kebir Hedi, Schmidt Ulrike, Sinclair Julia, Smolka Michael N, Hohmann Sarah, Holz Nathalie, Walter Henrik, Whelan Robert, Desrivières Sylvane, Schumann Gunter, Luo Qiang
Abstract excerpt
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 = 1332), we found that weakened...
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