Details

Autor(en) / Beteiligte

• Bookheimer, Susan Y.
• Salat, David H.
• Terpstra, Melissa
• Ances, Beau M.
• Barch, Deanna M.
• Buckner, Randy L.
• Burgess, Gregory C.
• Curtiss, Sandra W.
• Diaz-Santos, Mirella
• Elam, Jennifer Stine
• Fischl, Bruce
• Greve, Douglas N.
• Hagy, Hannah A.
• Harms, Michael P.
• Hatch, Olivia M.
• Hedden, Trey
• Hodge, Cynthia
• Japardi, Kevin C.
• Kuhn, Taylor P.
• Ly, Timothy K.
• Smith, Stephen M.
• Somerville, Leah H.
• Uğurbil, Kâmil
• van der Kouwe, Andre
• Van Essen, David
• Woods, Roger P.
• Yacoub, Essa

Titel

The Lifespan Human Connectome Project in Aging: An overview

Ist Teil von

• NeuroImage (Orlando, Fla.), 2019-01, Vol.185, p.335-348

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2019

Quelle

MEDLINE

Beschreibungen/Notizen

• The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018). •The Lifespan Human Connectome Project-Aging (HCP-A) project is collecting multimodal MRI and behavioral data from 1200 + participants aged 36–100+.•MRI includes structural, resting state fMRI, task fMRI, diffusion, and arterial spin labeled imaging.•Bio-behavioral assessments include cognitive, psychiatric, metabolic, socioeconomic, and systemic health characterization.•600 + participants will receive a longitudinal follow-up at 20–24 months.•These data will become a public resource to enable in-depth studies of typical brain aging.