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Structural and functional multi-platform MRI series of a single human volunteer over more than fifteen years
- Source :
- Scientific Data, Vol 6, Iss 1, Pp 1-9 (2019), Scientific Data
- Publication Year :
- 2019
- Publisher :
- Nature Publishing Group, 2019.
-
Abstract
- We present MRI data from a single human volunteer consisting in over 599 multi-contrast MR images (T1-weighted, T2-weighted, proton density, fluid-attenuated inversion recovery, T2* gradient-echo, diffusion, susceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) acquired in over 73 sessions on 36 different scanners (13 models, three manufacturers) over the course of 15+ years (cf. Data records). Data included planned data collection acquired within the Consortium pour l’identification précoce de la maladie Alzheimer - Québec (CIMA-Q) and Canadian Consortium on Neurodegeneration in Aging (CCNA) studies, as well as opportunistic data collection from various protocols. These multiple within- and between-centre scans over a substantial time course of a single, cognitively healthy volunteer can be useful to answer a number of methodological questions of interest to the community.<br />Measurement(s)brainTechnology Type(s)magnetic resonance imagingSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9925037
- Subjects :
- Statistics and Probability
Data records
Adult
medicine.medical_specialty
Aging
Data Descriptor
Time Factors
Computer science
Brain imaging
Library and Information Sciences
030218 nuclear medicine & medical imaging
Education
03 medical and health sciences
0302 clinical medicine
Magnetic resonance imaging
Neuroimaging
medicine
Humans
Medical physics
lcsh:Science
Multi platform
Volunteer
Data collection
Resting state fMRI
Middle Aged
Healthy Volunteers
3. Good health
Computer Science Applications
Metadata
Time course
lcsh:Q
Statistics, Probability and Uncertainty
030217 neurology & neurosurgery
Information Systems
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 6
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Scientific Data
- Accession number :
- edsair.doi.dedup.....7b34d31066967679a7f72553c9de2b53