{"dataset":{"id":"31922","dataset_id":"on005752","name":"The NIMH Healthy Research Volunteer Dataset","description":"The NIMH Healthy Research Volunteer Dataset is a comprehensive neuroimaging and clinical characterization study of 1,859 healthy adults. The dataset includes structural and functional MRI, diffusion tensor imaging, magnetoencephalography, cognitive assessments, psychiatric evaluations, and biospecimens. This resource enables investigations into normal cognition, mood regulation, and brain function across a deeply phenotyped healthy population.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on005752","concept_doi":"10.82901/nemar.on005752","latest_version_doi":"10.82901/nemar.on005752.v1.0.0","created_at":"2026-06-14 07:03:11","updated_at":"2026-07-10 22:56:10","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"The NIMH Healthy Research Volunteer Dataset\",\n  \"description\": \"The NIMH Healthy Research Volunteer Dataset is a comprehensive neuroimaging and clinical characterization study of 1,859 healthy adults. The dataset includes structural and functional MRI, diffusion tensor imaging, magnetoencephalography, cognitive assessments, psychiatric evaluations, and biospecimens. This resource enables investigations into normal cognition, mood regulation, and brain function across a deeply phenotyped healthy population.\",\n  \"methods_description\": \"Data collection includes clinical interviews (SCID-5), cognitive testing (KBIT-2, NIH Toolbox), psychiatric assessments (DSM-5 measures, WHODAS 2.0), and neuroimaging. MRI protocol includes T1, T2, FLAIR, pCASL, DTI, and resting-state fMRI acquisitions. MEG battery comprises resting-state, task-based, and empty room recordings. Biological measures include blood pressure, laboratory panels, and banked blood samples for genetic analysis.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Allison C. Nugent\": {\n      \"orcid\": \"0000-0003-2569-2480\"\n    },\n    \"Adam G Thomas\": {\n      \"orcid\": \"0000-0002-2850-1419\"\n    },\n    \"Margaret Mahoney\": {},\n    \"Alison Gibbons\": {},\n    \"Jarrod Smith\": {},\n    \"Antoinette Charles\": {},\n    \"Jacob S Shaw\": {\n      \"orcid\": \"0000-0002-7906-9945\"\n    },\n    \"Jeffrey D Stout\": {},\n    \"Anna M Namyst\": {\n      \"orcid\": \"0000-0001-6273-2205\"\n    },\n    \"Arshitha Basavaraj\": {},\n    \"Eric Earl\": {\n      \"orcid\": \"0000-0001-5512-0083\"\n    },\n    \"Dustin Moraczewski\": {},\n    \"Emily Guinee\": {},\n    \"Michael Liu\": {},\n    \"Travis Riddle\": {},\n    \"Joseph Snow\": {},\n    \"Shruti Japee\": {},\n    \"Morgan Andrews\": {},\n    \"Adriana Pavletic\": {},\n    \"Stephen Sinclair\": {},\n    \"Vinai Roopchansingh\": {},\n    \"Peter A Bandettini\": {},\n    \"Joyce Chung\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"MEG\"\n    },\n    {\n      \"term\": \"MRI\"\n    },\n    {\n      \"term\": \"healthy volunteers\"\n    },\n    {\n      \"term\": \"neuroimaging\"\n    },\n    {\n      \"term\": \"cognitive assessment\"\n    },\n    {\n      \"term\": \"psychiatric evaluation\"\n    },\n    {\n      \"term\": \"diffusion tensor imaging\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on005752\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=on005752\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-022-01623-9\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1016/j.psychres.2020.112822\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsReferencedBy\"\n    },\n    {\n      \"identifier\": \"10.1371/journal.pone.0184661\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsReferencedBy\"\n    },\n    {\n      \"identifier\": \"10.1038/s41592-018-0235-4\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsReferencedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds005752.v2.1.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"NIH\",\n      \"award_number\": \"ZICMH002889\"\n    },\n    {\n      \"funder_name\": \"NIH\",\n      \"award_number\": \"ZICMH002960\"\n    },\n    {\n      \"funder_name\": \"NIH\",\n      \"award_number\": \"ZIAMH002783\"\n    },\n    {\n      \"funder_name\": \"NIH\",\n      \"award_number\": \"ZIDMH00291\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"Diffusion MRI Dataset\",\n  \"modalities\": [\n    \"dwi\",\n    \"anat\",\n    \"func\",\n    \"perf\",\n    \"fmap\",\n    \"meg\"\n  ],\n  \"sizes\": [\n    \"680.0 GB (11000 files)\"\n  ],\n  \"formats\": [\n    \".acq\",\n    \".bak\",\n    \".bval\",\n    \".bvec\",\n    \".cfg\",\n    \".cls\",\n    \".de\",\n    \".ds/BadChannels\",\n    \".ds/tmp1zoi67or\",\n    \".ds/tmpoqqn4ln5\",\n    \".dsc\",\n    \".gz\",\n    \".hc\",\n    \".hist\",\n    \".infods\",\n    \".json\",\n    \".md\",\n    \".meg4\",\n    \".mrk\",\n    \".newds\",\n    \".pdf\",\n    \".res4\",\n    \".tsv\",\n    \".txt\",\n    \".xml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"a07a76e3c6212e27b4703c74641527c885f21531b3d6bf97b38e98dc344107a2\"\n}","last_activity_at":"2026-06-14 07:03:11","source":"openneuro","source_id":"ds005752","subject_count":251,"modalities":"anat,dwi,fmap,func,meg,perf","age_min":18,"age_max":90,"file_size":680041230967,"total_files":11000,"tasks":"airpuff,airpuffAltVer,artifact,gonogo,haririhammer,movie,noise,oddball,rest,sternberg","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Allison C. Nugent, Adam G Thomas, Margaret Mahoney, Alison Gibbons, Jarrod Smith, Antoinette Charles, Jacob S Shaw, Jeffrey D Stout, Anna M Namyst, Arshitha Basavaraj, Eric Earl, Dustin Moraczewski, Emily Guinee, Michael Liu, Travis Riddle, Joseph Snow, Shruti Japee, Morgan Andrews, Adriana Pavletic, Stephen Sinclair, Vinai Roopchansingh, Peter A Bandettini, Joyce Chung","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005752-blue)](https://doi.org/10.82901/nemar.on005752)\n\n# The National Institute of Mental Health (NIMH) Research Volunteer (RV) Data Set\n\nA comprehensive dataset characterizing healthy research volunteers in terms of clinical assessments, mood-related psychometrics, cognitive function neuropsychological tests, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG).\n\nIn addition, blood samples are currently banked for future genetic analysis.  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.  This dataset is unprecedented in its depth of characterization of a healthy population and will allow a wide array of investigations into normal cognition and mood regulation.\n\nThis dataset is licensed under the [Creative Commons Zero (CC0) v1.0 License](https://creativecommons.org/publicdomain/zero/1.0/).\n\n## Release Notes\n\n### Release v2.0.0\n\nThis release includes data collected between 2020-06-03 (cut-off date for v1.0.0) and 2024-04-01. Notable changes in this release:\n\n  1. 769 new participants have been added along with re-evaluation data for 15 participants. Total unique participants count is now 1859.  \n  2. `visit` and `age_at_visit` columns added to phenotype files to distinguish between visits and intervals between them.\n  3. Follow-up online survey data included.\n  4. Replaced Beck Anxiety Inventory (BAI) and Beck Depression Inventory-II (BDI-II) with General Anxiety Disorder-7 (GAD7) and Patient Health Questionnaire 9 (PHQ9) surveys, respectively.\n  5. Discontinued the Perceived Health rating survey.\n  6. Added Brief Trauma Questionnaire (BTQ) and Big Five personality survey to online screening questionnaires.\n  7. MRI:\n    - Replaced ADNI-3 resting state sequence with a multi-echo sequence with higher spatial resolution.\n    - Replaced field map scans with a shorter reversed-blipped EPI scan.\n  8. MEG:\n    - Some participants have 6-minute empty room data instead of the shorter duration empty room acquisition.\n\nSee the [CHANGES](./CHANGES) file for complete version-wise changelog.\n\n\n## Participant Eligibility\n\nTo be eligible for the study, participants need to be medically healthy adults over 18 years of age with the ability to read, speak and understand English.  All participants provided electronic informed consent for online pre-screening, and written informed consent for all other procedures.  Participants with a history of mental illness or suicidal or self-injury thoughts or behavior are excluded.  Additional exclusion criteria include current illicit drug use, abnormal medical exam, and less than an 8th grade education or IQ below 70.  Current NIMH employees, or first degree relatives of NIMH employees are prohibited from participating.  Study participants are recruited through direct mailings, bulletin boards and listservs, outreach exhibits, print advertisements, and electronic media.\n\n## Clinical Measures\n\nAll potential volunteers visit [the study website](https://nimhresearchvolunteer.ctss.nih.gov), check a box indicating consent, and fill out preliminary screening questionnaires.  The questionnaires include basic demographics, the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), the DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure, the DSM-5 Level 2 Cross-Cutting Symptom Measure - Substance Use, the Alcohol Use Disorders Identification Test (AUDIT), the Edinburgh Handedness Inventory, and a brief clinical history checklist.  The WHODAS 2.0 is a 15 item questionnaire that assesses overall general health and disability, with 14 items distributed over 6 domains: cognition, mobility, self-care, “getting along”, life activities, and participation.  The DSM-5 Level 1 cross-cutting measure uses 23 items to assess symptoms across diagnoses, although an item regarding self-injurious behavior was removed from the online self-report version.  The DSM-5 Level 2 cross-cutting measure is adapted from the NIDA ASSIST measure, and contains 15 items to assess use of both illicit drugs and prescription drugs without a doctor’s prescription.  The AUDIT is a 10 item screening assessment used to detect harmful levels of alcohol consumption, and the Edinburgh Handedness Inventory is a systematic assessment of handedness.  These online results do not contain any personally identifiable information (PII).  At the conclusion of the questionnaires, participants are prompted to send an email to the study team. These results are reviewed by the study team, who determines if the participant is appropriate for an in-person interview.\n\nParticipants who meet all inclusion criteria are scheduled for an in-person screening visit to determine if there are any further exclusions to participation.  At this visit, participants receive a History and Physical exam, Structured Clinical Interview for DSM-5 Disorders (SCID-5), the Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI), and the Kaufman Brief Intelligence Test, Second Edition (KBIT-2).  The purpose of these cognitive and psychometric tests is two-fold.  First, these measures are designed to provide a sensitive test of psychopathology.  Second, they provide a comprehensive picture of cognitive functioning, including mood regulation.  The SCID-5 is a structured interview, administered by a clinician, that establishes the absence of any DSM-5 axis I disorder.  The KBIT-2 is a brief (20 minute) assessment of intellectual functioning administered by a trained examiner.  There are three subtests, including verbal knowledge, riddles, and matrices.  \n\n## Biological and physiological measures\n\nBiological and physiological measures are acquired, including blood pressure, pulse, weight, height, and BMI.  Blood and urine samples are taken and a complete blood count, acute care panel, hepatic panel, thyroid stimulating hormone, viral markers (HCV, HBV, HIV), c-reactive protein, creatine kinase, urine drug screen and urine pregnancy tests are performed.  In addition, three additional tubes of blood samples are collected and banked for future analysis, including genetic testing.\n\n## Imaging Studies\n\nParticipants were given the option to enroll in optional magnetic resonance imaging (MRI) and magnetoencephalography (MEG) studies.\n\n### MRI\n\nOn the same visit as the MRI scan, participants are administered a subset of tasks from the NIH Toolbox Cognition Battery. The four tasks asses attention and executive functioning (Flanker Inhibitory Control and Attention Task), executive functioning (Dimensional Change Card Sort Task), episodic memory (Picture Sequence Memory Task), and working memory (List Sorting Working Memory Task). The MRI protocol used was initially based on the ADNI-3 basic protocol, but was later modified to include portions of the ABCD protocol in the following manner:\n\n1. The T1 scan from ADNI3 was replaced by the T1 scan from the ABCD protocol.\n2. The Axial T2 2D FLAIR acquisition from ADNI2 was added, and fat saturation turned on.\n3. Fat saturation was turned on for the pCASL acquisition.\n4. The high-resolution in-plane hippocampal 2D T2 scan was removed, and replaced with the whole brain 3D T2 scan from the ABCD protocol (which is resolution and bandwidth matched to the T1 scan).\n5. The slice-select gradient reversal method was turned on for DTI acquisition, and reconstruction interpolation turned off.\n6. Scans for distortion correction were added (reversed-blip scans for DTI and resting state scans).\n7. The 3D FLAIR sequence was made optional, and replaced by one where the prescription and other acquisition parameters provide resolution and geometric correspondence between the T1 and T2 scans.\n\n### MEG\n\nThe optional MEG studies were added to the protocol approximately one year after the study was initiated, thus there are relatively fewer MEG recordings in comparison to the MRI dataset.  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