Brain texture alterations predict subtle visual perceptual dysfunctions in recent onset psychosis and clinical high-risk state

Journal article

Deeper understanding of Subtle Visual Dysfunctions (VisDys) in the early stage of mental illness and their neurobiological underpinnings, as reflected by microstructural brain texture features, could advance our understanding of the underlying disease perceptual mechanisms that mediate susceptibility to psychosis. In this study, we aim a) to investigate the utility of brain texture features for the prediction of VisDys in recent onset psychosis (ROP) and clinical high-risk syndromes for psychosis (CHR-P), respectively, b) to test prediction models established in ROP and CHR-P in an independent validation sample with recent onset depression (ROD) diagnoses and c) to test for symptom expression related brain features associated with VisDys. sMRI were acquired in a training sample including 128 ROP (67 patients with VisDys), 134 CHR-P (71 patients with VisDys). Independent validation sets included 46 ROP (19 with VisDys), 124 CHR-P (68 patients with VisDys) and a sample of 256 ROD (50 patients with VisDys). Both classification schemas in ROP and CHR-P presented balanced accuracy >77% and >64% in the independent validation samples of ROP, CHR-P, and ROD, respectively. Statistically significant associations were identified with scores from the Positive and Negative Symptom Scale, psychosocial functioning, and the Scale of Negative Symptoms.

Authors: Lencer, R; Sprenger, A; Meyhöfer, I; Dannlowski, U; Romer, G

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer Nature [academic journals on nature.com]
• Journal: Translational Psychiatry
• Volume: 16
• Issue: 1
• Article number: 113
• Publication date: 2026-02-12
• Acceptance date: 2026-01-20
• DOI: 10.1038/s41398-026-03840-x
• EISSN: 2158-3188
• ISSN: 2158-3188
• Language: English
• Keywords: Psychosis; Psychosocial; Schizophrenia (object-oriented programming); Perception; Disease; Medical diagnosis; Neuroimaging; Cognition