The Human Connectome Project will provide a treasure trove of information at an unprecedented level of detail. It is important that the interpretation of these connectivity data respects key organizational features of the human brain and the physical dimensions of its components.
The HCP will generate invaluable information about connectivity, function and parcellation of the cerebral cortex, cerebellum, thalamus, and basal ganglia. Relatively little is currently known about human brain connectivity, but studies of nonhuman primates indicate that each cortical area and each subcortical nucleus typically has reciprocal connections with dozens of other areas and nuclei. Moreover, connection strengths for any given structure range over many orders of magnitude.
The core objective of the HCP is to determine the connectomes for each individual subject studied. We consider a connectome to be a connectivity matrix that encodes objective measures of the anatomical or functional connections between each pair of identified brain locations. Diffusion imaging yields evidence regarding the likelihood that two regions are directly connected. Such measures are correlated with, but not proportional to, connection strength (the number of fibers in the pathway). Functional imaging (R-fMRI) yields evidence regarding the dynamic interactions between two regions, which tends to be high if the regions are directly connected but may also reflect a history of common activation.
We consider a "dense connectome" as a connectivity matrix between pairs of gray-matter voxels at the finest resolution available (e.g., voxel size of ~1 mm for 7T data and ~2 mm for 3T data). A "parcellated connectome" is a more compact representation of connections between identified brain subdivisions (parcels or nodes). Parcellated connectomes are expected to be the datasets most widely used by the scientific community.
Individual variability in connectomes may account for diversity in many aspects of normal cognition, perception, and motor skills. Several challenges will be addressed in order to chart connectivity and test for such correlations.
- H Johansen-Berg, M F S Rushworth. Using Diffusion Imaging to Study Human Connectional Anatomy. Annual Review of Neuroscience. 2009; 32:75-94.
- D Van Essen, D Dierker. Surface-Based and Probabilistic Atlases of Primate Cerebral Cortex. Neuron. 2007 Oct 25; 56(2):209-25.
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