Physics-based models of brain structure connectivity informed by diffusion weighted imaging
Abstract
Recent evidence indicates that neural adaptations related to changes in task performance occur in not only gray matter brain regions but also the white matter fiber tracts that connect the gray matter regions with one another. Here, we propose a framework for linking individual differences in global properties of the brain’s anatomical connectivity, or connectome, to individual differences in task performance. We argue that this analysis framework may be optimally used on groups of patients with particular cognitive impairments to increase the dynamic range of task performance and optimize our sensitivity to detect structure-function relationships. In particular, patients suffering from mild traumatic brain injury may be an ideal group based on evidence suggesting an underlying cause of diffuse axonal injury that is widespread throughout the brain yet not detectable on structural magnetic resonance imaging (MRI) or computer tomography (CT) brain scans. The data discussed here lays the foundation for research on individual differences in structure-function relationships by comparing two diffusion-weighted imaging techniques that can be used to examine white matter structure in vivo in order to determine if one technique provides more reliable estimates of structural variability between individuals. While both methods show reproducibility of a particular individual’s brain structure, Diffusion Tensor Imaging appears better able to reliably capture the variability between subjects. We conclude with a description of a physics-based modeling approach using diffusion-weighted imaging data that facilitates several avenues of Army-relevant research.
