The NIMH intramural healthy volunteer dataset: A comprehensive MEG, MRI, and behavioral resource

Author
Allison Nugent
Adam Thomas
Margaret Mahoney
Alison Gibbons
Jarrod Smith
Antoinette Charles
Jacob Shaw
Jeffrey Stout
Anna Namyst
Arshitha Basavaraj
Eric Earl
Travis Riddle
Joseph Snow
Shruti Japee
Adriana Pavletic
Stephen Sinclair
Vinai Roopchansingh
Peter Bandettini
Joyce Chung
Keywords
Library and Information Sciences
Statistics, Probability and Uncertainty
Computer Science Applications
Education
Information Systems
Statistics and Probability
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.

Data

Year of Publication
2022
Journal
Scientific Data
Volume
9
Issue
1
ISSN Number
2052-4463
DOI
10.1038/s41597-022-01623-9