ArticleScience advances2024
Generalizable and replicable brain-based predictions of cognitive functioning across common psychiatric illness.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Exploring the link between body physiology and cognition: the role of the brain and aging.npj aging · 2026Article
- Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease.Nature communications · 2026Article
- Widespread synaptic density loss in schizophrenia follows molecular and network architecture.Molecular psychiatry · 2026Article
- External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging.Nature methods · 2026Review
- Widespread use of invalid statistical tests in biomedical machine learning.bioRxiv : the preprint server for biology · 2026Article
- A Framework for Advancing Mechanistic Neurobehavioral Biomarkers in Psychiatry.Biological psychiatry · 2026Review
- Common and distinct neurofunctional signatures of dynamic naturalistic emotion regulation strategies.Nature communications · 2026Article
- Optimizing functional connectivity scanning conditions for predicting autistic traits.medRxiv : the preprint server for health sciences · 2026Article
- Is the whole more than the sum of its parts? Considering global and local features of the connectome improves prediction of individuals and phenotypes.bioRxiv : the preprint server for biology · 2026Article
- Optimizing functional connectivity scanning conditions for predicting autistic traits.Nature. Mental health · 2026Article
- Temporal dynamic of cognitive decline in type 2 diabetes mellitus patients: a multimodal biomarker analysis using event-based modal and principal component analysis.Diabetology & metabolic syndrome · 2025Article
- Functional Coupling and Longitudinal Outcome Prediction in First-Episode Psychosis.Biological psychiatry global open science · 2025Article
- Reproducible Effects of Sex and Acquisition Order on Multiple Global Signal Metrics: Implications for Functional Connectivity Studies of Phenotypic Individual Differences Using fMRI.Brain and behavior · 2025Article
- Group-specific discriminant analysis enhances detection of sex differences in brain functional network lateralization.GigaScience · 2025Article
- Quality over quantity: powering neuroimaging samples in psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Article
- Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities.NeuroImage · 2024Article
- Multilayer meta-matching: Translating phenotypic prediction models from multiple datasets to small data.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Multilayer meta-matching: translating phenotypic prediction models from multiple datasets to small data.bioRxiv : the preprint server for biology · 2023Article
- Is the whole more than the sum of its parts? Considering global and local features of the connectome improves prediction of individuals and phenotypes.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
A primary aim of computational psychiatry is to establish predictive models linking individual differences in brain functioning with symptoms. In particular, cognitive impairments are transdiagnostic, treatment resistant, and associated with poor outcomes. Recent work suggests that thousands of participants may be necessary for the accurate and reliable prediction of cognition, questioning the utility of most patient collection efforts. Here, using a transfer learning framework, we train a model on functional neuroimaging data from the UK Biobank to predict cognitive functioning in three transdiagnostic samples (ns = 101 to 224). We demonstrate prediction performance in all three samples comparable to that reported in larger prediction studies and a boost of up to 116% relative to classical models trained directly in the smaller samples. Critically, the model generalizes across datasets, maintaining performance when trained and tested across independent samples. This work establishes that predictive models derived in large population-level datasets can boost the prediction of cognition across clinical studies.
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Registered trials
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 OpenQuestion graph.