HCP Aging


Citing HCP-Aging

To cite use of HCP-Aging data or methods in a publication, press release, or presentation please include in your Acknowledgements section:

“Research reported in this publication was supported by the National Institute On Aging of the National Institutes of Health under Award Number U01AG052564 and by funds provided by the McDonnell Center for Systems Neuroscience at Washington University in St. Louis. The HCP-Aging 2.0 Release data used in this report came from DOI: 10.15154/1520707.

Publications related to this study:

  • The Lifespan Human Connectome Project in Aging: An overview.

    Susan Y Bookheimer, David H Salat, Melissa Terpstra, Beau M Ances, Deanna M Barch, Randy L Buckner, Gregory C Burgess, Sandra W Curtiss, Mirella Diaz-Santos, Jennifer Stine Elam, Bruce Fischl, Douglas N Greve, Hannah A Hagy, Michael P Harms, Olivia M Hatch, Trey Hedden, Cynthia Hodge, Kevin C Japardi, Taylor P Kuhn, Timothy K Ly, Stephen M Smith, Leah H Somerville, Kâmil Uğurbil, Andre van der Kouwe, David Van Essen, Roger P Woods, Essa Yacoub
    NeuroImage, Oct 18, 2018 PMID: 30332613
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    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).

  • Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

    Michael P Harms, Leah H Somerville, Beau M Ances, Jesper Andersson, Deanna M Barch, Matteo Bastiani, Susan Y Bookheimer, Timothy B Brown, Randy L Buckner, Gregory C Burgess, Timothy S Coalson, Michael A Chappell, Mirella Dapretto, Gwenaëlle Douaud, Bruce Fischl, Matthew F Glasser, Douglas N Greve, Cynthia Hodge, Keith W Jamison, Saad Jbabdi, Sridhar Kandala, Xiufeng Li, Ross W Mair, Silvia Mangia, Daniel Marcus, Daniele Mascali, Steen Moeller, Thomas E Nichols, Emma C Robinson, David H Salat, Stephen M Smith, Stamatios N Sotiropoulos, Melissa Terpstra, Kathleen M Thomas, M Dylan Tisdall, Kamil Ugurbil, Andre van der Kouwe, Roger P Woods, Lilla Zöllei, David C Van Essen, Essa Yacoub
    NeuroImage, Sep 28, 2018 PMID: 30261308
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    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.