Higher-order interdependencies of the epileptogenic network in presurgical resting-state fMRI
- 1Aix-Marseille Université, CRMBM, CNRS UMR 7339, Marseille, France
Abstract
Drug-resistant focal epilepsy (DRFE) is understood as a complex brain network disorder. As a result, conventional pair-wise functional connectivity may fail to capture the higher-order interactions between groups of epileptogenic regions. We applied multivariate information theory to stereotactic electroencephalography-defined networks in retrospective resting-state fMRI analysis to determine whether the overall strength and dominant type of interdependencies between three or more regions, represented by the S-information and O-information respectively, could offer clinically relevant insights prior to surgical intervention in DRFE. We found networks involving the epileptogenic zone to be mostly dominated by re-dundant information-sharing, which was predicted by stronger structural and functional connections between regions. Non-temporal lobe epilepsy patients demonstrated greater redundancy and stronger comparative interdependencies than temporal lobe epilepsy patients, in line with a more complex network architecture. Among non-temporal lobe cases with postoperative follow-up, not seizure-free patients displayed more positive O-information deviation scores than seizure-free patients, suggesting elevated redundancy in networks associated with poorer surgical outcomes. Our findings potentiate the S-information and O-information as complementary higher-order descriptors of the epileptogenic network within personalised presurgical assessments.
Related
- Regional and network-level resting state functional connectivity markers of pharmacological treatment resistance in obsessive-compulsive disorder
- Ageing reshapes the resting-state network landscape of the human brain
- Resting-State Functional Connectivity in Antipsychotic-Naïve First-Episode Psychosis: A Systematic Review of Network Alterations and Preprocessing Heterogeneity
- Explainable Deep Learning of Resting-State Functional Connectomes Reveals Network Biomarkers of Adolescent Intelligence
- Altered attention network dynamics in resting-state fMRI of individuals with high smartphone addiction scores
BibTeX
@misc{knight2026higherorder,
title = {{Higher-order interdependencies of the epileptogenic network in presurgical resting-state fMRI}},
author = {J. Knight and M. Neri and J. Makhalova and H. Dary and S. Medina-Villalon and J.-P. Ranjeva and A. Brovelli and F. Bartolomei and M. Guye and R. A. Haast},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.24.753209},
url = {https://www.biorxiv.org/content/10.64898/2026.09.24.753209v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Higher-order interdependencies of the epileptogenic network in presurgical resting-state fMRI
AU - J. Knight
AU - M. Neri
AU - J. Makhalova
AU - H. Dary
AU - S. Medina-Villalon
AU - J.-P. Ranjeva
AU - A. Brovelli
AU - F. Bartolomei
AU - M. Guye
AU - R. A. Haast
PY - 2026
DA - 2026/09/24
PB - bioRxiv
DO - 10.64898/2026.09.24.753209
UR - https://www.biorxiv.org/content/10.64898/2026.09.24.753209v1
AB - Drug-resistant focal epilepsy (DRFE) is understood as a complex brain network disorder. As a result, conventional pair-wise functional connectivity may fail to capture the higher-order interactions between groups of epileptogenic regions. We applied multivariate information theory to stereotactic electroencephalography-defined networks in retrospective resting-state fMRI analysis to determine whether the overall strength and dominant type of interdependencies between three or more regions, represented by the S-information and O-information respectively, could offer clinically relevant insights prior to surgical intervention in DRFE. We found networks involving the epileptogenic zone to be mostly dominated by re-dundant information-sharing, which was predicted by stronger structural and functional connections between regions. Non-temporal lobe epilepsy patients demonstrated greater redundancy and stronger comparative interdependencies than temporal lobe epilepsy patients, in line with a more complex network architecture. Among non-temporal lobe cases with postoperative follow-up, not seizure-free patients displayed more positive O-information deviation scores than seizure-free patients, suggesting elevated redundancy in networks associated with poorer surgical outcomes. Our findings potentiate the S-information and O-information as complementary higher-order descriptors of the epileptogenic network within personalised presurgical assessments.
ER -