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Biomedical Optics & Medical Imaging

Deciphering the human-brain connectome

The Human Connectome Project aims to reveal and understand the complex neural pathways supporting brain function.
7 December 2010, SPIE Newsroom. DOI: 10.1117/2.1201011.003395

Understanding the human brain remains one of the greatest scientific challenges of the 21st century. The Washington University/University of Minnesota consortium leads the Human Connectome Project (HCP), a five-year initiative funded by the National Institutes of Health Blueprint for Neuroscience Research, and was awarded $30 million in September 2010 to comprehensively map brain circuitry, which will yield information about brain connectivity and its relationship to genetic, environmental factors and behavior. It will pave the way for future studies on changes during development and aging, or in the context of neurological and psychiatric disorders. Nine participating research centers will use powerful neuroimaging and electrophysical recording techniques, such as magnetic-resonance imaging (MRI), magneto- and electro-encephalography (MEG, EEG), computational analysis, informatics, and visualization to study 1200 healthy adults, aimed at better understanding the intricate workings of the human brain.

To obtain high-quality maps of brain connectivity, the HCP will use cutting-edge MRI hardware and mathematical models. During the first two years, we will focus on optimizing a Siemens Skyra 3 Tesla (3T) system at the University of Minnesota's Center for Magnetic Resonance Research (CMRR), to achieve faster data acquisition and increased spatial resolution. The instrument will then be shipped to Washington University to scan the 1200 subjects (twin and nontwin siblings from 300 families). Additionally, CMRR scientists will use their extensive experience with ultrahigh-field imaging to exploit the numerous advantages of the 7T scanner, including higher signal-to-noise ratio, improved spatial accuracy and functional resolution, greater anatomical detail,1 and enhanced parallel-imaging capabilities.2 To better understand the 3T data, 200 subjects will also be scanned at 7T.

Two complementary imaging modalities will be used to resolve anatomical and functional connectivity. First, we will use diffusion imaging,3 or—more precisely—high-angular-resolution diffusion imaging (HARDI), to chart the fiber bundles of white matter throughout the gray-matter regions of the brain. Combined with advanced computational techniques4 and software (FSL: University of Oxford Centre for Functional MRI of the Brain Software Library, Caret), use of HARDI will allow reconstruction of fiber-bundle orientation at each volume element (voxel) with exquisite angular precision to generate probability maps of anatomical connectivity (see Figure 1, left). Second, resting-state functional MRI5 (fMRI) will provide comprehensive descriptions of the functional connectivity between different gray-matter regions, based on correlations in the fMRI blood-oxygen-level-dependent signal among functionally interacting brain regions.

We will obtain additional information about brain function using Task-fMRI, where subjects carry out behavioral tasks while in the scanner. MEG and EEG will provide this kind of information on millisecond timescales. Furthermore, extensive behavioral testing of each subject will enable comparisons between brain connectivity and behavioral phenotypes. Genome-wide association studies evaluating the influence of genetic factors on brain circuitry will be conducted through genotyping of all subjects.

We will use a variety of analytical and visualization tools to integrate the large amount of diverse experimental data generated by the HCP, providing the research community with unprecedented information on the interaction between anatomical and functional brain networks (see Figure 1). The nodes of these networks, called ‘brain parcels’ (because they correspond to distinct brain territories), are difficult to identify because of the sheer number of regions and pathways, high individual variability, and limits on the spatial resolution of the imaging methods. Therefore, brain parcellation will be achieved using clustering strategies and algorithms, and will be analyzed with tools from graph theory6 to uncover the brain's local and global organization. All this data, along with the tools developed to analyze it, will be made freely accessible through a robust informatics platform.

Figure 1.  Anatomical (left) and functional (right) connectivity of the area identified by the blue dot. (Source: M. Glasser, T. Laumann, D. Van Essen, Washington University in St. Louis.)

This enormous undertaking will provide a detailed baseline for the major anatomical and functional circuits of the normal human brain and enable future research to study connectivity abnormalities in disorders such as schizophrenia and autism. The HCP will be an enormously valuable endeavor, having a transformative impact on our understanding of the human brain.

This research is funded in part by the HCP (1U54MH091657-01) from the 16 National Institutes of Health (NIH) Institutes and Centers that support the NIH Blueprint for Neuroscience Research, and by grants P41-RR008079 and R01-MH60974.

Christophe Lenglet, Michael Garwood, Noam Harel, Essa Yacoub, Kamil Ugurbil
Center for Magnetic Resonance Research, University of Minnesota Medical School
Minneapolis, MN

Christophe Lenglet is an assistant professor of radiology and Institute for Translational Neuroscience Scholar. His research focuses on development of mathematical models and computational tools for processing, analysis, and visualization of neuroimaging data.

Guillermo Sapiro
Department of Electrical and Computer Engineering, University of Minnesota
Minneapolis, MN
David Van Essen
Department of Anatomy and Neurobiology, Washington University in St. Louis
Saint Louis, MO