The NIMH intramural healthy volunteer dataset: A comprehensive MEG, MRI, and behavioral resource.
Allison C NugentAdam G ThomasMargaret MahoneyAlison GibbonsJarrod T SmithAntoinette J CharlesJacob S ShawJeffrey D StoutAnna M NamystArshitha BasavarajEric A EarlTravis RiddleJoseph SnowShruti JapeeAdriana J PavleticStephen SinclairVinai RoopchansinghPeter A BandettiniJoyce ChungPublished in: Scientific data (2022)
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.
Keyphrases
- mental health
- magnetic resonance imaging
- resting state
- electronic health record
- contrast enhanced
- white matter
- functional connectivity
- high resolution
- high throughput
- healthcare
- public health
- mental illness
- diffusion weighted imaging
- rna seq
- multiple sclerosis
- pain management
- magnetic resonance
- machine learning
- mild cognitive impairment
- brain injury
- current status
- data analysis
- cerebral ischemia
- climate change
- artificial intelligence
- health information
- high density