Resting-state fMRI in the Human Connectome Project
| Autor: | Jonathan D. Power, Kamil Ugurbil, David A. Feinberg, Timothy O. Laumann, Janine D. Bijsterbosch, Abraham Z. Snyder, Jesper L. R. Andersson, Junqian Xu, Mark W. Woolrich, Christian F. Beckmann, Steven E. Petersen, Gwenaëlle Douaud, Gholamreza Salimi-Khorshidi, Stephen M. Smith, Essa Yacoub, Matthew F. Glasser, D. C. Van Essen, Michael E. Kelly, Michael P. Harms, Edward J. Auerbach, Eugene P. Duff, An T. Vu, Karla L. Miller, Steen Moeller, Ludovica Griffanti |
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| Přispěvatelé: | Magnetic Detection and Imaging, Faculty of Science and Technology |
| Rok vydání: | 2013 |
| Předmět: |
Models
Anatomic Cognitive Neuroscience Rest Models Neurological 050105 experimental psychology Article 03 medical and health sciences 0302 clinical medicine Neuroimaging Models medicine Connectome Humans 0501 psychology and cognitive sciences Human Connectome Project medicine.diagnostic_test Resting state fMRI business.industry Anatomic Molecular Materials 05 social sciences 220 Statistical Imaging Neuroscience Brain Magnetic resonance imaging Pattern recognition Magnetic Resonance Imaging Nerve Net Neurology Data quality Neurological Artificial intelligence Functional magnetic resonance imaging Psychology business Neuroscience 030217 neurology & neurosurgery Diffusion MRI |
| Zdroj: | NeuroImage, 80, 144-168. Academic Press NeuroImage, 80, 144-168 NeuroImage, 80, pp. 144-168 |
| ISSN: | 1095-9572 1053-8119 |
| Popis: | Resting-state functional magnetic resonance imaging (rfMRI) allows one to study functional connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI scanner, and taking advantage of the fact that functionally related brain regions spontaneously co-activate. rfMRI is one of the two primary data modalities being acquired for the Human Connectome Project (the other being diffusion MRI). A key objective is to generate a detailed in vivo mapping of functional connectivity in a large cohort of healthy adults (over 1000 subjects), and to make these datasets freely available for use by the neuroimaging community. In each subject we acquire a total of 1. h of whole-brain rfMRI data at 3. T, with a spatial resolution of 2. ×. 2. ×. 2. mm and a temporal resolution of 0.7. s, capitalizing on recent developments in slice-accelerated echo-planar imaging. We will also scan a subset of the cohort at higher field strength and resolution. In this paper we outline the work behind, and rationale for, decisions taken regarding the rfMRI data acquisition protocol and pre-processing pipelines, and present some initial results showing data quality and example functional connectivity analyses. © 2013 Elsevier Inc. |
| Databáze: | OpenAIRE |
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