Date: Sep 15, 2010 Source: (
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The National Institutes of Health today awarded grants totaling $40 million to map the human brain's connections in high resolution. Better understanding of such connectivity promises improved diagnosis and treatment of brain disorders.
The grants are the first awarded under the Human Connectome Project (http://www.nih.gov/news/health/jul2009/ninds-15.htm). They will support two collaborating research consortia. The first will be led by researchers at Washington University, St. Louis, and the University of Minnesota, Twin Cities. The other will be led by investigators at Massachusetts General Hospital (MGH)/Harvard University, Boston, and the University of California Los Angeles (UCLA).
"We're planning a concerted attack on one of the great scientific challenges of the 21st. Century," explained Washington University's Dr. David Van Essen, Ph.D., who co-leads one of the groups with Minnesota's Kamil Ugurbil, Ph.D. "The Human Connectome Project (http://www.humanconnectome.org/consortia/) will have transformative impact, paving the way toward a detailed understanding of how our brain circuitry changes as we age and how it differs in psychiatric and neurologic illness."
The Connectome projects are being funded by 16 components (http://grants.nih.gov/grants/guide/rfa-files/RFA-MH-10-020.html) of NIH under its Blueprint for Neuroscience Research(http://www.neuroscienceblueprint.nih.gov/).
"On a scale never before attempted, this highly coordinated effort will use state-of-the-art imaging instruments, analysis tools and informatics technologies — and all of the resulting data will be freely shared with the research community," said Michael Huerta, Ph.D., of the National Institute of Mental Health, who directs the NIH Connectome initiative. "Individual variability in brain connections underlies the diversity of our thinking, perception and motor skills, so understanding these networks promises advances in brain health."
The Washington U./Minnesota team will map the connectomes in each of 1,200 healthy adults — twin pairs and their siblings from 300 families. The maps will show the anatomical and functional connections between parts of the brain for each individual, and will be related to behavioral test data. Comparing the connectomes and genetic data of genetically identical twins with fraternal twins will reveal the relative contributions of genes and environment in shaping brain circuitry and pinpoint relevant genetic variation. The maps will also shed light on how brain networks are organized.
The Washington U. / U. Minnesota Connectome project will map the brain connections in each of 1200 participants. In the left image, yellow and red show a map of ‘structural connectivity' in human cerebral cortex (regions that are connected to the blue spot as revealed by diffusion MRI). In the right image, yellow and red show a map of ‘functional connectivity' (regions associated with the blue spot as revealed by functional MRI). Source: David Van Essen, Ph.D., Washington University.
In tooling up for the screening, the researchers will optimize magnetic resonance imaging (MRI) scanners to capture the brain's anatomical wiring — and its activity, both when participants are at rest and when challenged by tasks. All participants will undergo such structural and functional scans at Washington University. For these, researchers will use a customized MRI scanner with a magnetic field of 3 Tesla. This Connectome Scanner will incorporate new imaging approaches developed by consortium scientists at Minnesota and Advanced MRI Technologies and will provide ten-fold faster imaging times and better spatial resolution.
Additionally, a subset of twin pairs will also be scanned using more powerful 7 and 10.5 Tesla MRI units at the University of Minnesota, which has pioneered the use of such advanced, ultra high magnetic field imaging. For another subset of twins, the scans will be complemented by movies of millisecond brain electrical activity obtained at St. Louis University, using magnetoencephalography (MEG)(http://kurage.nimh.nih.gov/meglab/Main/MegOverview) and electroencephalography (EEG) (http://www.nlm.nih.gov/medlineplus/ency/article/003931.htm).
