The Human Connectome Project


Human Connectome

The NIH Human Connectome Project is an ambitious effort to map the neural pathways that underlie human brain function. The overarching purpose of the Project is to acquire and share data about the structural and functional connectivity of the human brain. It will greatly advance the capabilities for imaging and analyzing brain connections, resulting in improved sensitivity, resolution, and utility, thereby accelerating progress in the emerging field of human connectomics.

Altogether, the Human Connectome Project will lead to major advances in our understanding of what makes us uniquely human and will set the stage for future studies of abnormal brain circuits in many neurological and psychiatric disorders.

Consortia

The Blueprint has funded two major cooperative agreements that will take complementary approaches to deciphering the brain's complex wiring diagram. For more information see the NIH press release, "$40 million awarded to trace human brain's connections."

Use the box at the right to search the consortium sites or browse the sites directly using the links below.

Connectome News and Announcements

  • Detail from DSI scan shows fabric-like 3D grid structure of connections in monkey brain.
  • Axial brain slices with mapped networks in orange.
  • A slice of diffusion tensor ellipsoids plotted over the fractional anisotrophy image to illustrate the fiber orientation throughout the brain.
  • Matrix showing correlation denoted by color between brain seed regions.
  • Select white matter tracts that run through spherical Regions of Interest (ROIs), superimposed over a larger amount of tracts from the same data set.
  • Boundaries and centers mapped in color on an inflated atlas brain surface.
  • White matter fiber architecture of the brain. Measured by diffusion spectral imaging (DSI).
  • fMRI activations mapped in color on an inflated atlas brain surface.
  • Coronal, parasagittal, and axial brain slices showing diffusion tracts colored by direction
  • Coronal volume brain slice showing functional connectivity in color within subcortical voxels and as an anatomical brain surface outline of the cerebral cortex.
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Search the Human Connectome Project
Blueprint Harvard/MGH-UCLA WU-Minn

The Harvard/MGH-UCLA Project Homepage

Latest Updates

The Massachusetts General Hospital and the University of California at Los Angeles consortium has built a next-generation 3T magnetic resonance imaging (MRI) scanner that improves the quality and spatial resolution with which brain connectivity data can be acquired. The MGH/UCLA Consortium will scan participants at MGH, and both sites will use advanced software to translate the MRI data into connectomic maps detailing the fibrous connections in the brain. Goals of the project include:

  • Use of the most advanced 3T scanner currently available to explore finer resolution neural connectivity.
  • Design of more efficient data acquisition protocols and scanner pulse sequences.
  • Development of novel algorithms for detailed analysis of fiber structure and inter-regional connectedness.
  • Development of novel graphical means for interactively navigating brain connectivity.
The WU-Minn Project Homepage

Latest Updates

Washington University in St. Louis and the University of Minnesota lead a 10-institution consortium aiming to comprehensively map long-distance brain connections and their variability through cutting-edge neuroimaging of 1,200 healthy adults (twins and their non-twin siblings). Data will be acquired using multiple imaging modalities, including customized 3T and 7T magnetic resonance imaging plus magnetoencephalography. By pairing studies of structural and functional brain connectivity with extensive behavioral and heritability measures, the project will provide freely available data about brain connectivity, its relationship to behavior, and contributions of environmental and genetic factors to individual differences in brain circuitry.

  • Numerous advances in data acquisition and analysis methods have been achieved during Phase I (through summer 2012).
  • Phase II (2012-2015) will involve data acquisition from 400 subjects/year.
  • Data will be freely shared starting in the fall of 2012 via a user-friendly platform for data mining, analysis, and visualization.