The NIMH intramural healthy volunteer dataset: A comprehensive MEG, MRI, and behavioral resource
Year: 2022
Type: data-paper
Study design: Observational Study
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.
Source: Scientific Data
Authors: Allison C. Nugent, Adam G. Thomas, Margaret Mahoney, Alison Gibbons, Jarrod T. Smith, Antoinette J. Charles, Jacob S. Shaw, Jeffrey D. Stout, Anna M. Namyst, Arshitha Basavaraj, Eric Earl, Travis Riddle, Joseph Snow, Shruti Japee, Adriana J. Pavletic, Stephen Sinclair, Vinai Roopchansingh, Peter A. Bandettini, Joyce Chung
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,090
OpenAlex ID: W4293089032
