The WU-Minn Human Connectome Project: an overview

Abstract

The Human Connectome Project consortium led by Washington University, University of Minnesota, and Oxford University is undertaking a systematic effort to map macroscopic human brain circuits and their relationship to behavior in a large population of healthy adults. This overview article focuses on progress made during the first half of the 5-year project in refining the methods for data acquisition and analysis. Preliminary analyses based on a finalized set of acquisition and preprocessing protocols demonstrate the exceptionally high quality of the data from each modality. The first quarterly release of imaging and behavioral data via the ConnectomeDB database demonstrates the commitment to making HCP datasets freely accessible. Altogether, the progress to date provides grounds for optimism that the HCP datasets and associated methods and software will become increasingly valuable resources for characterizing human brain connectivity and function, their relationship to behavior, and their heritability and genetic underpinnings.

Figure 1

A. Parasagittal slice through posterior cortex of T₁w image from subject A1 (study-specific code), with accurate pial and white surface contours, even where cortex is thin (arrows). The fidelity with which the FreeSurfer white and pial surfaces track the anatomical boundaries is much better than the initial surfaces generated by running FreeSurfer 5.1 on 1 mm isotopic T₁w data from the same subject (cf Figs. 11, 12 in Glasser et al., 2013b). B, C. Myelin maps on inflated left and right hemispheres of subject A1. Highlighted vertices centered on myelin hotspots in the left hemisphere (B, black) have geographically corresponding vertices located within myelin hotspots in the right hemisphere (C, blue). The myelin maps illustrated here are improved over those available in the HCP Q1 data release by virtue of a step that reduces residual low spatial frequency biases by subtracting a highly smoothed population-average myelin map (see Glasser et al., 2013a Fig. 22 and associated text for details).

Figure 2

Cortical shape features in identical twins. Highlighted vertices are locations on a gyral crown (white ridge) in twin A1 (yellow, blue arrows) or in twin A2 (red, green) but are deeper in a sulcus in the ‘geographically corresponding’ location in the other twin. Subjects are identified in a study-specific code (A1, A2, B1, B2) in conformance with the Restricted Access Data Use Terms (see below).

Figure 3

A. A map of functional connectivity (after regression of the mean gray timecourse) in the left and right hemispheres of an individual HCP subject associated with a seed location in right retrosplenial cortex (black arrow, black circle). B. A functional connectivity map for a nearby seed location (white arrow, black circle) in cingulate cortex (part of the default mode network).

Figure 4

A map of functional connectivity (full correlation converted to Z-statistics) in the left and right hemispheres associated with a seed location in left parietal cortex (part of the default mode network), from a group average functional connectivity analysis (20 subjects from the HCP Q1 data release, but not the same as the standard ‘20 unrelated’ subjects). Positive correlations are thresholded at Z>5 and negative correlations are thresholded at Z<−2.5 Adapted, with permission, from Smith et al. (2013)

Figure 5

A. Five example components from a 30-component ICA analysis (8 were discarded as being either artifact or being inconsistent across subjects) displayed on inflated cortical atlas surfaces. B. 22×22 correlation matrices (group-average parcellated connectomes) derived from the timeseries associated with the 22 group-ICA components. Full correlation is shown below the diagonal; partial correlation above the diagonal. Each row or column is the set of correlations (red, yellow) or anti-correlations (green, blue) between a single network matrix “node” and all other nodes; the nodes were reordered from the original ordering, according to a hierarchical clustering algorithm (depicted at the top). The network analysis and figure generation was carried out using the FSLNets package (fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLNets). Adapted from Smith et al. (2013).

Figure 6

shows representative fractional anisotropy and color-encoded principal diffusion direction images from the HCP dMRI data, compared with a more conventional 2mm data set (from a different subject). The improvement in anatomical detail is clearly discernible. For example, many white matter tracts appear thicker (less partial voluming). The imaging protocol for the conventional data was as follows: Siemens 3T Verio, 2mm isotropic voxels, 64 slices, 60 directions, 2 averages with reversed phase encoding polarity, b=1500s/mm^2, TE/TR=86/10000ms, GRAPPA=2, scan time=20min

Figure 7

Structural connectivity in an individual and in group averages and in comparison to functional connectivity. A. Connectivity trajectory visualization for a single HCP subject (100307). Probabilistic trajectories seeded from a single grayordinate in left frontal cortex and intersecting the white/gray matter boundary surface in at least one more location are shown on the left panel; the right hemisphere’s midthickness surface provides a spatial reference. The inset (right) displays a part of the trajectories for a single sagittal slice, overlayed on a T₁w image (white/gay matter boundary shown with the black solid line). B. Structural connectivity values in a group average (9 HCP subjects) for the same seed location (black dot), viewed on the inflated cortical surface. The values are displayed using a logarithmic scale. C. Functional connectivity values for the same seed location, displayed on the inflated surface. The values correspond to the average functional connectivity of a group of 20 HCP subjects.

Figure 8

Group-average task-fMRI from the working memory task. Adapted, with permission, from Barch et al., (2013)

Figure 9

Group-average task-fMRI from the language vs math task. Adapted, with permission, from Barch et al., (2013)

Figure 10

A. Task-fMRI activation from the right-hand movement task carried out on the Q1 unrelated 20 subjects, mapped onto the group-average cerebral surfaces (first two panels) and onto the inflated cerebellar atlas surface that has been mapped to the MNI atlas stereotaxic space (Van Essen, 2009). B. Resting-state fMRI component 13 from a 100-dimensional ICA decomposition (with 82 components judged to be signal), applied to the 66 subjects in the HCP Q1 data release having four rfMRI runs.