ArticleScientific data2024
The Aphasia Recovery Cohort, an open-source chronic stroke repository.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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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.
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.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Topography and functional connectivity analysis of heart surgery-associated brain lesions: a literature review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- Accelerated brain aging and anterior white matter hyperintensity burden in chronic post-stroke aphasia: a lesion-aware MRI analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Cerebellar Tracts Microstructural Characteristics and Severity of Language Impairment in Post-stroke Patients with Aphasia: A DTI Study.Cerebellum (London, England) · 2026Article
- Acute-Phase Machine Learning Prediction of 12-Month Aphasia and Discourse Recovery.medRxiv : the preprint server for health sciences · 2026Article
- Diffusion Tensor Imaging and Advanced Diffusion Imaging in Post-Stroke Aphasia Recovery.Tomography (Ann Arbor, Mich.) · 2026Review
- Cortical hierarchy and aphasia severity: the sensorimotor-association gradient modulates lesion effects within language-specific networks.Communications biology · 2026Article
- Beyond the cerebral cortex: cerebellar language-related subregions contributions to fluency in post-stroke aphasia.NeuroImage. Clinical · 2026Article
- Uncovering hidden pathways: structural brain networks under connected speech in post-stroke aphasia.Brain communications · 2026Article
- A Structured Review and Quantitative Profiling of Public Brain MRI Datasets for Foundation Model Development.Journal of imaging · 2025Review
- Optimal stochastic tracking control for brain network dynamics.Communications biology · 2025Article
- Integrating direct electrical stimulation with brain connectivity predicts lesion-induced language impairment and recovery.Communications medicine · 2025Article
- Comparison of Large Language Model with Aphasia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- BrainScape: An open-source framework for integrating and preprocessing anatomical MRI datasets.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Stable multivariate lesion symptom mapping.Aperture neuro · 2024Article
- Distinct brain morphometry patterns revealed by deep learning improve prediction of aphasia severity.Research square · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Sharing neuroimaging datasets enables reproducibility, education, tool development, and new discoveries. Neuroimaging from many studies are publicly available, providing a glimpse into progressive disorders and human development. In contrast, few stroke studies are shared, and these datasets lack longitudinal sampling of functional imaging, diffusion imaging, as well as the behavioral and demographic data that encourage novel applications. This is surprising, as stroke is a leading cause of disability, and acquiring brain imaging is considered standard of care. The first release of the Aphasia Recovery Cohort includes imaging data, demographics and behavioral measures from 230 chronic stroke survivors who experienced aphasia. We also share scripts to illustrate how the imaging data can predict impairment. In conclusion, recent advances in machine learning thrive on large, diverse datasets. Clinical data sharing can contribute to improvements in automated detection of brain injury, identification of white matter hyperintensities, measures of brain health, and prognostic abilities to guide care.
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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.