% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Hirjak:306584,
author = {D. Hirjak and S. Volkmer and R. Peretzke$^*$ and A.
Meyer-Lindenberg and K. H. Maier-Hein$^*$ and P. Neher$^*$},
title = {{D}elineating white matter phenotypes of
sensori-/psychomotor functioning in large-scale cohorts of
healthy individuals and patients with mental disorders
across the lifespan (white{SPAN}): rationale and methods of
an interdisciplinary bicentric project.},
journal = {European archives of psychiatry and clinical neuroscience},
volume = {nn},
issn = {0003-9373},
address = {Darmstadt},
publisher = {Steinkopff},
reportid = {DKFZ-2025-02625},
pages = {nn},
year = {2025},
note = {ISSN 1433-8491 / #LA:E230# / epub},
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.},
keywords = {Deep learning (Other) / Diffusion MRI (Other) / Large-scale
data (Other) / Machine learning (Other) / Neuroimaging
(Other) / Psychomotor (Other)},
cin = {E230 / HD01},
ddc = {610},
cid = {I:(DE-He78)E230-20160331 / I:(DE-He78)HD01-20160331},
pnm = {315 - Bildgebung und Radioonkologie (POF4-315)},
pid = {G:(DE-HGF)POF4-315},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:41288695},
doi = {10.1007/s00406-025-02138-1},
url = {https://inrepo02.dkfz.de/record/306584},
}