ArticleScientific data2022
The NIMH intramural healthy volunteer dataset: A comprehensive MEG, MRI, and behavioral resource.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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.
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.
Who cites it
28 citing papers in PubMed.
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- Similarities and differences in the late-onset GM2 gangliosidoses: Tay-Sachs and Sandhoff diseases.Journal of neurology · 2026Article
- Disrupted dynamics of transient brain states in patients with brain tumors: a co-activation pattern analysis of resting-state fMRI.La Radiologia medica · 2026Article
- Magnetoencephalography in human neuroscience research: planning, piloting, implementation and quality assurance.Nature protocols · 2026Review
- The ENIGMA MEG Pipeline: Automated cortically localized spectral analysis of multi-site resting state MEG datasets.bioRxiv : the preprint server for biology · 2026Article
- Brain Health in Former Professional Motorsport Drivers: Case Series in a Population Exposed to Sport-Related Concussions and Repetitive Head Impacts.Sports medicine - open · 2026Article
- Deep Computational Anatomy via Latent-Aligned Multiview Normalizing Flows.bioRxiv : the preprint server for biology · 2026Article
- Normative modeling of MEG brain oscillations across the human lifespan.Communications biology · 2026Article
- Frontier and hot topics in Magnetoencephalography(MEG) in neurological diseases.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Identifying impulsivity and substance use measures in neuroimaging datasets: A scoping review and searchable dataset repository for researchers.Current addiction reports · 2026Article
- A Structured Review and Quantitative Profiling of Public Brain MRI Datasets for Foundation Model Development.Journal of imaging · 2025Review
- Intrinsic Neural Timescales Relate to Event-Related Activity-Key Role for Intracolumnar Connections.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Unraveling Microstructural and Macrostructural Brain Age Dynamics in Multiple Sclerosis.Neurology(R) neuroimmunology & neuroinflammation · 2025Article
- Similarities and Differences in the Late-Onset GM2 Gangliosidoses: Tay-Sachs and Sandhoff Diseases.medRxiv : the preprint server for health sciences · 2025Article
- Cognitive Control Network and Language Reorganization in Patients with Brain Tumors.AJNR. American journal of neuroradiology · 2025Article
- Deep Learning Cerebellar Magnetic Resonance Imaging Segmentation in Late-Onset GM2 Gangliosidosis: Implications for Phenotype.medRxiv : the preprint server for health sciences · 2025Article
- Concurrent functional-structural reorganization in brain networks of AVM patients: a functional and structural study.Frontiers in neurology · 2025Article
- BrainAgeNeXt: Advancing brain age modeling for individuals with multiple sclerosis.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Brain morphology normative modelling platform for abnormality and centile estimation: Brain MoNoCle.Imaging neuroscience (Cambridge, Mass.) · 2025Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
The NIMH Healthy Research Volunteer Dataset is a collection of phenotypic data characterizing healthy research volunteers using clinical assessments such as assays of blood and urine, mental health assessments, diagnostic and dimensional measures of mental health, cognitive and neuropsychological functioning, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG). In addition, blood samples of healthy volunteers are banked for future analyses. All data collected in this protocol are broadly shared in the OpenNeuro repository, in the Brain Imaging Data Structure (BIDS) format. In addition, task paradigms and basic pre-processing scripts are shared on GitHub. There are currently few open access MEG datasets, and multimodal neuroimaging datasets are even more rare. Due to its depth of characterization of a healthy population in terms of brain health, this dataset may contribute to a wide array of secondary investigations of non-clinical and clinical research questions.
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What OpenQuestion holds
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.