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 JbabdiSridhar 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

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)972-984
Number of pages13
JournalNeuroImage
Volume183
DOIs
StatePublished - Dec 2018

Bibliographical note

Funding Information:
Research reported in this publication was supported by grants U01MH109589 , U01MH109589-S1 , U01AG052564 , and U01AG052564-S1 and by the 14 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research , by the McDonnell Center for Systems Neuroscience at Washington University , by the Office of the Provost at Washington University , and by the University of Minnesota Medical School . We thank the HCP-D/A Project Coordinator, Sandra Curtiss, and the staff at each site for all their effort to launch the projects and keep them running smoothly on a daily basis. Complete lists of study staff are available as supplemental tables in Bookheimer et al. (under review) and Somerville et al. (2018) . The UK Biobank measures of diffusion CNR were estimated using data from the UK Biobank via data access Application Number 8107. We also thank Prantik Kundu for discussions and assistance involving multi-echo denoising.

Funding Information:
Research reported in this publication was supported by grants U01MH109589, U01MH109589-S1, U01AG052564, and U01AG052564-S1 and by the 14 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research, by the McDonnell Center for Systems Neuroscience at Washington University, by the Office of the Provost at Washington University, and by the University of Minnesota Medical School. We thank the HCP-D/A Project Coordinator, Sandra Curtiss, and the staff at each site for all their effort to launch the projects and keep them running smoothly on a daily basis. Complete lists of study staff are available as supplemental tables in Bookheimer et al. (under review) and Somerville et al. (2018). The UK Biobank measures of diffusion CNR were estimated using data from the UK Biobank via data access Application Number 8107. We also thank Prantik Kundu for discussions and assistance involving multi-echo denoising.

Publisher Copyright:
© 2018 Elsevier Inc.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

Keywords

  • Aging
  • Connectomics
  • Development
  • Diffusion
  • Functional connectivity
  • Lifespan
  • Perfusion
  • Resting-state
  • Task

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