ReviewThe Human Connectome Project: A data acquisition perspective
Introduction
Recent advances in neuroimaging, including many that are discussed in this special issue, have made it feasible to examine human brain connectivity systematically and across the whole brain in large numbers of individual subjects. Progress in the nascent field of connectomics led NIH in 2009 to announce a Request for Applications for the Human Connectome Project (HCP), with an overarching objective of studying human brain connectivity and its variability in healthy adults. In September, 2010, grants were awarded to two consortia(http://www.neuroscienceblueprint.nih.gov/connectome/). One is a 5-year grant to a consortium of ten institutions in the United States and Europe,led by Washington University and the University of Minnesota (the ‘WU-Minn HCP Consortium’). This consortium aims to study brain connectivity and function with a genetically-informative design in 1200 individuals using four MR-based modalities plus MEG and EEG. Behavioral and genetic data will also be acquired from these subjects. The second is a 3-year grant to a consortium led by Harvard/MGH and UCLA to develop an advanced MR scanner for diffusion imaging.
A deeper understanding of human brain connectivity and its variability will provide valuable insights into what makes us uniquely human and what accounts for the great diversity of behavioral capacities and repertoires in healthy adults. It will provide a critical baseline of knowledge for future studies of brain connectivity during development and aging and in myriad neurodevelopmental, neuropsychiatric and neurological disorders. Also, the data acquisition strategies and analysis methods developed under the auspices of the HCP will be freely shared and will benefit many other projects. Increasingboth the commonality and the sensitivity of methods used to characterize human brain connectivity across different studies will enhance our ability to detect subtle links between genetics, human brain connectivity patterns, and behavioral variation.
Despite their great promise, all of the modalities that can be appliedto in vivo human connectomics currently have serious limitations in their sensitivity, accuracy, and resolution (Van Essen and Ugurbil, 2012). Hence, during Phase I of the grant (until the summer of 2012) the WU-Minn HCPconsortium is making a major effort to improve the methods of data acquisition and analysis. This includes a new 3T MRI scanner designed to improve the quality and resolution of connectivity data,as well asanew 7T scanner, both of which will capitalize on major improvement in MR pulse sequences. This initial phase will be followed by a3-year period of data acquisition from the main cohort(Phase II). The combination of methods refinement followed by extensive data acquisition makes the HCP a unique enterprise compared to several other large-scale imaging efforts that are also underway (see Discussion).
This review focuses on the data acquisition aspects of the HCP, given their critical importance for the endeavor. After a brief overview of the HCP objectives, we describe the subject cohort and behavioral measures, followed by the hardware configuration and data acquisition strategies for each of the main imaging modalities. Alreadythere have been significant methodological advances that provide grounds for optimism about the data quality that will be attainable.Approaching near-optimal solutions will be very challenging given the large number of factors and parameters needing evaluation. We provide examples of our general approach to this problem.
Section snippets
Overview of the HCP
Fig. 1 provides a high-level view of our plans for data acquisition in Phase II of the project. Data will be acquired from 1200 subjects, comprising young adult sibships of average size 3–4, including twins and their non-twin siblings. Each subject will spend 2 days at WashU for behavioral assessment, blood draw for eventual genotyping, and multiple MR scanning sessions (4 sessions, with 3 lasting 1 h). The WashU scans will be carried out using a customized 3T ConnectomeScanner adapted from a
Discussion
Three issues touched upon above warrant brief discussion. These include issues of (i) limitations of in vivo imaging; (ii) advantages of twin–sibship families coupled with data sharing limitations; and (iii) the relationship of HCP to other large-scale neuroimaging projects.
Acknowledgments
We thank the entire WU-Minn HCP consortium team for their excellent efforts that have contributed directly or indirectly to the plans described in this manuscript. Funded in part by the Human Connectome Project (1U54MH091657) from the 16 NIH Institutes and Centers that Support the NIH Blueprint for Neuroscience Research, and by the McDonnell Center for Systems Neuroscience at Washington University. Members of the WU-Minn HCP Consortium are listed at //www.humanconnectome.org/about/hcp-investigators.html
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