Neighbourhood topology unveils pathological hubs in the brain networks of epilepsy-surgery patients

Pathological hubs in the brain networks of epilepsy patients are hypothesized to drive seizure generation and propagation. In epilepsy-surgery patients, these hubs have traditionally been associated with the resection area: the region removed during the surgery with the goal of stopping the seizures, and which is typically used as a proxy for the epileptogenic zone. However, recent studies hypothesize that pathological hubs may extend to the vicinity of the resection area, potentially complicating post-surgical seizure control. Here we propose a neighbourhood-based analysis of brain organization to investigate this hypothesis. We exploit a large dataset of presurgical MEG (magnetoencephalography)-derived whole-brain networks from 91 epilepsy-surgery patients. Our neighbourhood-focus is two-fold. Firstly, we propose a partition of the brain regions into three sets, namely resected nodes, their neighbours, and the remaining network nodes. Secondly, we introduce generalized centrality metrics that describe the neighrbourhood of each node, providing a regional measure of hubness. Our analyses reveal that both the resection area and its neighborhood present large hub-status, but with significant variability across patients. For some, hubs appear in the resection area; for others, in its neighborhood. Moreover, this variability does not correlate with surgical outcome. These results highlight the potential of neighborhood-based analyses to uncover novel insights into brain connectivity in brain pathologies, and the need for individualized studies, with large-enough cohorts, that account for patient-specific variability.