http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.00051/abstract
Andrei Irimia and John D. Van Horn*
Department of Neurology, Keck School of Medicine, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA
Brain connectivity loss due to traumatic brain injury, stroke or multiple sclerosis can have serious consequences on life quality and a measurable impact upon neural and cognitive function. Though brain network properties are known to be affected disproportionately by injuries to certain gray matter regions, the manner in which white matter (WM) insults affect such properties remains poorly understood. Here, network-theoretic analysis allows us to identify the existence of a macroscopic neural connectivity core in the adult human brain which is particularly sensitive to network lesioning. The systematic lesion analysis of brain connectivity matrices from diffusion neuroimaging over a large sample (N = 110) reveals that the global vulnerability of brain networks can be predicated upon the extent to which injuries disrupt this connectivity core, which is found to be quite distinct from the set of connections between rich club nodes in the brain. Thus, in addition to connectivity within the rich club, the brain as a network also contains a distinct core scaffold of network edges consisting of WM connections whose damage dramatically lowers the integrative properties of brain networks. This pattern of core WM fasciculi whose injury results in major alterations to overall network integrity presents new avenues for clinical outcome prediction following brain injury by relating lesion locations to connectivity core disruption and implications for recovery. The findings of this study contribute substantially to current understanding of the human WM connectome, its sensitivity to injury, and clarify a long-standing debate regarding the relative prominence of gray vs. WM regions in the context of brain structure and connectomic architecture.
- Department of Neurology, Keck School of Medicine, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA
- See more at: http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.00051/abstract#sthash.tWZJPVnQ.dpuf
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