| Home > Publications database > Delineating white matter phenotypes of sensori-/psychomotor functioning in large-scale cohorts of healthy individuals and patients with mental disorders across the lifespan (whiteSPAN): rationale and methods of an interdisciplinary bicentric project. |
| Journal Article | DKFZ-2025-02625 |
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2025
Steinkopff
Darmstadt
Abstract: Aberrant sensori-/psychomotor functioning-including muscular hand weakness, sedentary behavior, psychomotor agitation, slowing, agitation, apathy, and anxiety-is increasingly recognized as a transdiagnostic feature across mental and neurodegenerative disorders. Objectively measured sensori-/psychomotor abnormalities serve as rapid, noninvasive indicators of cognitive and affective dysfunction, yet large-scale neuroimaging studies examining their white matter (WM) correlates remain limited. This bi-centric research project aims to investigate associations between sensori-/psychomotor functioning and WM microstructure across anxiety disorders (AD), major depressive disorder (MDD), schizophrenia spectrum disorders (SSD), mild cognitive impairment (MCI), and Alzheimer's disease (AD). We will analyze diffusion MRI data from over 2,400 healthy individuals and 1,600 patients, combining publicly available datasets (e.g., Human Connectome Project, Alzheimer's Disease Neuroimaging Initiative) with in-house cohorts comprising >400 deeply-phenotyped SSD and MDD patients. A major strength of the project lies in the harmonization of psychopathological rating scales and sensori-/psychomotor assessments across these populations. Using advanced computational tools-including tractometry, tractomics, normative modeling, and deep learning-we aim to map a WM phenotype of sensori-/psychomotor dysfunction across the lifespan. Multivariate taxometric approaches will help identify biologically informed sensori-/psychomotor biotypes that cut across traditional diagnostic boundaries. By distinguishing disorder-specific WM changes from normative developmental and aging processes, this project seeks to inform precision medicine approaches and guide biomarker-driven interventions for mental and neurodegenerative disorders.
Keyword(s): Deep learning ; Diffusion MRI ; Large-scale data ; Machine learning ; Neuroimaging ; Psychomotor
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