Human Connectome Project

The Human Connectome Project (HCP) was a five-year project (later extended to 10 years) sponsored by sixteen components of the National Institutes of Health, split between two consortia of research institutions. The project was launched in July 2009 as the first of three Grand Challenges of the NIH's Blueprint for Neuroscience Research. On September 15, 2010, the NIH announced that it would award two grants: $30 million over five years to a consortium led by Washington University in St. Louis and the University of Minnesota, with strong contributions from University of Oxford (FMRIB) and $8.5 million over three years to a consortium led by Harvard University, Massachusetts General Hospital and the University of California Los Angeles.

The goal of the Human Connectome Project was to build a "network map" (connectome) that sheds light on the anatomical and functional connectivity within the healthy human brain, as well as to produce a body of data that will facilitate research into brain disorders such as dyslexia, autism, Alzheimer's disease, and schizophrenia.

A number of successor projects are currently in progress, based on the Human Connectome Project results.

The WU-Minn-Oxford consortium developed improved MRI instrumentation, image acquisition and image analysis methods for mapping the connectivity in the human brain at spatial resolutions significantly better than previously available; using these methods, WU-Minn-Oxford consortium collected a large amount of MRI and behavioral data on 1,200 healthy adults — twin pairs and their siblings from 300 families - using a special 3 Tesla MRI instrument. In addition, it scanned 184 subjects from this pool at 7 Tesla, with higher spatial resolution. The data were analyzed to show the anatomical and functional connections between parts of the brain for each individual, and were related to behavioral test data. Comparing the connectomes and genetic data of genetically identical twins with fraternal twins revealed the relative contributions of genes and environment in shaping brain circuitry and pinpointed relevant genetic variation. The maps also shed light on how brain networks are organized.

Using a combination of non-invasive imaging technologies, including resting-state fMRI and task-based functional MRI, MEG and EEG, and diffusion MRI, the WU-Minn mapped connectomes at the macro scale — mapping large brain systems that were divided into anatomically and functionally distinct areas, rather than mapping individual neurons.

Dozens of investigators and researchers from nine institutions contributed to this project. Research institutions include: Washington University in St. Louis, the Center for Magnetic Resonance Research at the University of Minnesota, University of Oxford, Saint Louis University, Indiana University, D'Annunzio University of Chieti–Pescara, Ernst Strungmann Institute, Warwick University, Advanced MRI Technologies, and the University of California at Berkeley.

The data that resulted from this research is publicly available in an open-source web-accessible neuroinformatics platform.

The MGH/Harvard-UCLA consortium focussed on optimizing MRI technology for imaging the brain's structural connections using diffusion MRI, with a goal of increasing spatial resolution, quality, and speed. Diffusion MRI, employed in both projects, maps the brain's fibrous long-distance connections by tracking the motion of water. Water diffusion patterns in different types of cells allow the detection of different types of tissues. Using this imaging method, the long extensions of neurons, called white matter, can be seen in sharp relief.