Evidence map›Paper›PMID 40654593›Full record

ArticleNeuroscience applied2025

Towards collaborative data science in mental health research: The ECNP neuroimaging network accessible data repository.

Adyasha Khuntia, Madalina-Octavia Buciuman, John Fanning, Aleks Stolicyn, Clara Vetter, Reetta-Liina Armio, Tiina From, Federica Goffi, Lisa Hahn, Tobias Kaufmann and 21 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuroscience applied, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

31 authors.

Adyasha KhuntiaDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Madalina-Octavia BuciumanDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
John FanningDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Aleks StolicynDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK.
Clara VetterDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Reetta-Liina ArmioDepartment of Psychiatry, University of Turku, Turku, Finland.
Tiina FromDepartment of Psychiatry, University of Turku, Turku, Finland.
Federica GoffiDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Lisa HahnDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Tobias KaufmannNORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
Heikki LaurikainenDepartment of Psychiatry, University of Turku, Turku, Finland.
Eleonora MaggioniDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Ignacio Martinez-ZalacainBellvitge Biomedical Research Institute-IDIBELL, Psychiatry Department, Bellvitge University Hospital, CIBERSAM and Department of Psychobiology and Methodology of Health Sciences, Universitat Autònoma de Barcelona, Spain.
Anne RuefDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Mark Sen DongDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Emanuel SchwarzHector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Letizia SquarcinaDepartment of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
Ole AndreassenNORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
Marcella BellaniSection of Psychiatry, Dept of Neurosciences, Biomedicine and Movement, University of Verona, Verona, Italy.
Paolo BrambillaDepartment of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
Neeltje van HarenDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, the Netherlands.
Jarmo HietalaDepartment of Psychiatry, University of Turku, Turku, Finland.
Stephen M LawrieDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK.
Carles Soriano-MasCIBERSAM, Carlos III Health Institute, Madrid, Spain.
Heather WhalleyDivision of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK.
Maxime TaquetDepartment of Psychiatry, University of Oxford, Oxford, UK.
Eva MeisenzahlDepartment of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
Peter FalkaiDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Ariane WiegandDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
Nikolaos KoutsoulerisDepartment of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian University, Munich, Germany.
ECNP Neuroimaging Network

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current biologically uninformed psychiatric taxonomy complicates optimal diagnosis and treatment. Neuroimaging-based machine learning methods hold promise for tackling these issues, but large-scale, representative cohorts are required for building robust and generalizable models. The European College of Neuropsychopharmacology Neuroimaging Network Accessible Data Repository (ECNP-NNADR) addresses this need by collating multi-site, multi-modal, multi-diagnosis datasets that enable collaborative research. The newly established ECNP-NNADR includes 4829 participants across 21 cohorts and 11 distinct psychiatric diagnoses, available via the Virtual Pooling and Analysis of Research data (ViPAR) software. The repository includes demographic and clinical information, including diagnosis and questionnaires evaluating psychiatric symptomatology, as well as multi-atlas grey matter volume regions of interest (ROI). To illustrate the opportunities offered by the repository, two proof-of-concept analyses were performed: (1) multivariate classification of 498 patients with schizophrenia (SZ) and 498 matched healthy control (HC) individuals, and (2) normative age prediction using 1170 HC individuals with subsequent application of this model to study abnormal brain maturational processes in patients with SZ. In the SZ classification task, we observed varying balanced accuracies, reaching a maximum of 71.13% across sites and atlases. The normative-age model demonstrated a mean absolute error (MAE) of 6.95 years [coefficient of determination (

Indexed as

Data repositoryMachine learningMulti-site dataNeuroimagingPsychiatryStructural MRITransdiagnostic

Identifiers

PMID40654593
PMCPMC12244052

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.