4.7 Article

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

期刊

NEUROIMAGE
卷 183, 期 -, 页码 972-984

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2018.09.060

关键词

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

资金

  1. 14 NIH Institutes and Centers
  2. McDonnell Center for Systems Neuroscience at Washington University
  3. Office of the Provost at Washington University
  4. University of Minnesota Medical School
  5. [U01MH109589]
  6. [U01MH109589-S1]
  7. [U01AG052564]
  8. [U01AG052564-S1]
  9. EPSRC [EP/P012361/1, EP/L023067/1] Funding Source: UKRI
  10. MRC [MR/K006673/1, MR/L009013/1] Funding Source: UKRI

向作者/读者索取更多资源

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.

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