TY - JOUR
T1 - Neighbourhood topology unveils pathological hubs in the brain networks of epilepsy-surgery patients
AU - Di Gaetano, Leonardo
AU - Santos, Fernando A.N.
AU - Battiston, Federico
AU - Bianconi, Ginestra
AU - Defenu, Nicolò
AU - Nissen, Ida A.
AU - Van Straaten, Elisabeth C.W.
AU - Hillebrand, Arjan
AU - Millán, Ana P.
N1 - Publisher Copyright:
© 2025 The Author(s). Published by Oxford University Press on behalf of the Guarantors of Brain.
PY - 2025/10/31
Y1 - 2025/10/31
N2 - 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 (RA): 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 RA, 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 pre-surgical magnetoencephalography-derived whole-brain networks from 91 epilepsy-surgery patients. Our neighbourhood focus is 2-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 neighbourhood of each node, providing a regional measure of hubness. Our analyses reveal that both the RA and its neighbourhood present large hub status, but with significant variability across patients. For some, hubs appear in the RA; for others, in its neighbourhood. Moreover, this variability does not correlate with surgical outcome. These results highlight the potential of neighbourhood-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.
AB - 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 (RA): 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 RA, 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 pre-surgical magnetoencephalography-derived whole-brain networks from 91 epilepsy-surgery patients. Our neighbourhood focus is 2-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 neighbourhood of each node, providing a regional measure of hubness. Our analyses reveal that both the RA and its neighbourhood present large hub status, but with significant variability across patients. For some, hubs appear in the RA; for others, in its neighbourhood. Moreover, this variability does not correlate with surgical outcome. These results highlight the potential of neighbourhood-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.
KW - brain hubs
KW - brain networks
KW - epilepsy
KW - magnetoencephalography
KW - topological data analysis
UR - https://www.scopus.com/pages/publications/105022900439
U2 - 10.1093/braincomms/fcaf431
DO - 10.1093/braincomms/fcaf431
M3 - Article
AN - SCOPUS:105022900439
SN - 2632-1297
VL - 7
JO - Brain Communications
JF - Brain Communications
IS - 6
M1 - fcaf431
ER -