Estimating the functional interactions between brain regions and mapping those connections to corresponding inter-individual differences in cognitive, behavioral and psychiatric domains are central pursuits for understanding the human connectome. The number and complexity of functional interactions within the connectome and the large amounts of data required to study them position functional connectivity research as a “big data” problem. Maximizing the degree to which knowledge about human brain function can be extracted from the connectome will require developing a new generation of neuroimaging analysis algorithms and tools. This review describes several outstanding problems in brain functional connectomics with the goal of engaging researchers from a broad spectrum of data sciences to help solve these problems. Additionally it provides information about open science resources consisting of raw and preprocessed data to help interested researchers get started.
Using probabilistic diffusion tractography, we examined the retinotopic organization of splenial callosal connections within early blind, anophthalmic, and control subjects. Early blind subjects experienced prenatal retinal “waves” of spontaneous activity similar to those of sighted subjects, and only lack postnatal visual experience. In anophthalmia, the eye is either absent or arrested at an early prenatal stage, depriving these subjects of both pre- and postnatal visual input. Therefore, comparing these two groups provides a way of separating the influence of pre- and postnatal retinal input on the organization of visual connections across hemispheres. We found that retinotopic mapping within the splenium was not measurably disrupted in early blind or anophthalmic subjects compared to visually normal controls. No significant differences in splenial volume were observed across groups. No significant differences in diffusivity were found between early blind subjects and sighted controls, through some differences in diffusivity were noted between anophthalmic subjects and controls. These results suggest that neither prenatal retinal activity nor postnatal visual experience play a role in the large-scale topographic organization of visual callosal connections within the splenium.
Connectivity information derived from diffusion MRI can be used to parcellate the cerebral cortex into anatomically and functionally meaningful subdivisions. Acquisition and processing parameters can significantly affect parcellation results, and there is no consensus on best practice protocols. We propose a novel approach for evaluating parcellation based on measuring the degree to which parcellation conforms to known principles of brain organization, specifically cortical field homogeneity and inter-hemispheric homology. The proposed metrics are well behaved on morphologically-generated whole-brain parcels, where they correctly identify contralateral homologies, and give higher scores to anatomically versus arbitrarily generated parcellations. The measures show that individual cortical fields have characteristic connectivity profiles that are compact and separable, and that the topological arrangement of such fields is strongly conserved between hemispheres and individuals. The proposed metrics can be used to evaluate the quality of parcellations at the subject and group levels, and to improve acquisition and data processing for connectivity-based cortical parcellation.
The function of a brain region can be constrained by its anatomical connections. The Inferior Parietal Lobule (IPL) is a cortical region with marked functional heterogeneity, involved in visuospatial attention, memory, language and mathematical cognition. In this work three different variants of the normalized graph-cut clustering algorithm were applied to obtain a parcellation of the IPL of living subjects into component regions based on the estimate of anatomical connectivity obtained from diffusion tensor tractography. Results over the three different algorithms were compared and a new metric proposed to measure the quality of individual parcellations by comparing to standard atlas regions. In this study of 19 subjects, an average of 64% overlap with the Juelich brain atlas was observed.
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