| Literature DB >> 28757305 |
Evan M Gordon1, Timothy O Laumann2, Adrian W Gilmore3, Dillan J Newbold4, Deanna J Greene5, Jeffrey J Berg6, Mario Ortega4, Catherine Hoyt-Drazen7, Caterina Gratton4, Haoxin Sun8, Jacqueline M Hampton4, Rebecca S Coalson9, Annie L Nguyen4, Kathleen B McDermott10, Joshua S Shimony11, Abraham Z Snyder9, Bradley L Schlaggar12, Steven E Petersen13, Steven M Nelson14, Nico U F Dosenbach15.
Abstract
Human functional MRI (fMRI) research primarily focuses on analyzing data averaged across groups, which limits the detail, specificity, and clinical utility of fMRI resting-state functional connectivity (RSFC) and task-activation maps. To push our understanding of functional brain organization to the level of individual humans, we assembled a novel MRI dataset containing 5 hr of RSFC data, 6 hr of task fMRI, multiple structural MRIs, and neuropsychological tests from each of ten adults. Using these data, we generated ten high-fidelity, individual-specific functional connectomes. This individual-connectome approach revealed several new types of spatial and organizational variability in brain networks, including unique network features and topologies that corresponded with structural and task-derived brain features. We are releasing this highly sampled, individual-focused dataset as a resource for neuroscientists, and we propose precision individual connectomics as a model for future work examining the organization of healthy and diseased individual human brains.Entities:
Keywords: brain networks; fMRI; functional connectivity; individual variability; myelin mapping
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Year: 2017 PMID: 28757305 PMCID: PMC5576360 DOI: 10.1016/j.neuron.2017.07.011
Source DB: PubMed Journal: Neuron ISSN: 0896-6273 Impact factor: 17.173