Abstract
Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages. Patients’ cortical lesion distribution patterns could significantly predict the functional network topology and a set of regions with significant weights in the prediction models were identified as “lesion hubs”. Intriguingly, we found two different types of lesion hubs, whose lesions associated with changes of network topology towards relatively different directions, being either more integrated (global) or more segregated (local), and correspond to hubs identified in healthy functional network in complex manners. Our results pose further important questions about the potential dynamics of the functional brain network after brain damage.
Highlights
Various important topological properties of healthy brain connectome have recently been identified
We calculated these topological properties in a single threshold in the main analyses and validated the results by calculating the cumulative topological properties in the full range of network sparsity using the area under curve (AUC) method[26]
Using multivariate pattern regression analysis based on brain structural lesions and resting-state functional imaging in 96 patients with brain damage, we established that the lesion patterns of patients could robustly predict the whole-brain functional network topology
Summary
Various important topological properties of healthy brain connectome have recently been identified. In patients with brain lesions, Gratton et al.[11] found that the mean lesion severity (the nodal lesion percentages scaled by the region’s centrality measure in the healthy group) of regions with high PCs, not those with high within-module degree (WMD)[14], was significantly correlated with the modularity property of the patient’s functional network. Such results offer compelling evidence that regions with higher PCs are more indispensable in maintaining a functional network’s www.nature.com/scientificreports/. Given that simulation lesion studies[10,20,21] relies on specific assumptions about the mechanisms of attack, which does not necessarily reflect actual brain lesion patterns, studies based on real brain damage data that employ multi-variate approaches are needed to understand how lesion encompassing various brain regions affect functional network topology
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