| Literature DB >> 30261308 |
Michael P Harms1, Leah H Somerville2, Beau M Ances3, Jesper Andersson4, Deanna M Barch5, Matteo Bastiani4, Susan Y Bookheimer6, Timothy B Brown7, Randy L Buckner8, Gregory C Burgess9, Timothy S Coalson10, Michael A Chappell11, Mirella Dapretto6, Gwenaëlle Douaud4, Bruce Fischl12, Matthew F Glasser13, Douglas N Greve14, Cynthia Hodge9, Keith W Jamison15, Saad Jbabdi4, Sridhar Kandala9, Xiufeng Li16, Ross W Mair17, Silvia Mangia16, Daniel Marcus7, Daniele Mascali18, Steen Moeller16, Thomas E Nichols19, Emma C Robinson20, David H Salat14, Stephen M Smith4, Stamatios N Sotiropoulos21, Melissa Terpstra16, Kathleen M Thomas22, M Dylan Tisdall23, Kamil Ugurbil16, Andre van der Kouwe24, Roger P Woods25, Lilla Zöllei14, David C Van Essen10, Essa Yacoub16.
Abstract
The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are two large-scale brain imaging studies that will extend the recently completed HCP Young-Adult (HCP-YA) project to nearly the full lifespan, collecting structural, resting-state fMRI, task-fMRI, diffusion, and perfusion MRI in participants from 5 to 100+ years of age. HCP-D is enrolling 1300+ healthy children, adolescents, and young adults (ages 5-21), and HCP-A is enrolling 1200+ healthy adults (ages 36-100+), with each study collecting longitudinal data in a subset of individuals at particular age ranges. The imaging protocols of the HCP-D and HCP-A studies are very similar, differing primarily in the selection of different task-fMRI paradigms. We strove to harmonize the imaging protocol to the greatest extent feasible with the completed HCP-YA (1200+ participants, aged 22-35), but some imaging-related changes were motivated or necessitated by hardware changes, the need to reduce the total amount of scanning per participant, and/or the additional challenges of working with young and elderly populations. Here, we provide an overview of the common HCP-D/A imaging protocol including data and rationales for protocol decisions and changes relative to HCP-YA. The result will be a large, rich, multi-modal, and freely available set of consistently acquired data for use by the scientific community to investigate and define normative developmental and aging related changes in the healthy human brain.Entities:
Keywords: Aging; Connectomics; Development; Diffusion; Functional connectivity; Lifespan; Perfusion; Resting-state; Task
Mesh:
Year: 2018 PMID: 30261308 PMCID: PMC6484842 DOI: 10.1016/j.neuroimage.2018.09.060
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556