Neuronal synchrony and critical bistability: Mechanistic biomarkers for localizing the epileptogenic network

Sheng H Wang; Gabriele Arnulfo; Lino Nobili; Vladislav Myrov; Paul Ferrari; Philippe Ciuciu; Satu Palva; J Matias Palva

doi:10.1111/epi.17996

Neuronal synchrony and critical bistability: Mechanistic biomarkers for localizing the epileptogenic network

Epilepsia. 2024 Apr 30. doi: 10.1111/epi.17996. Online ahead of print.

Authors

Sheng H Wang^{1

2

3

4}, Gabriele Arnulfo⁵, Lino Nobili^{6

7}, Vladislav Myrov², Paul Ferrari^{8

9}, Philippe Ciuciu^{3

4}, Satu Palva^{1

10

11}, J Matias Palva^{1

2

10}

Affiliations

¹ Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland.
² Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.
³ Le Commissariat à l'énergie atomique et aux énergies alternatives, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France.
⁴ Models and Inference for Neuroimaging Data, Inria, Palaiseau, France.
⁵ Department of Informatics, Bioengineering, Robotics, and System Engineering, University of Genoa, Genoa, Italy.
⁶ Child Neuropsychiatry Unit, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Giannina Gaslini, Member of the European Reference Network EpiCARE, Genoa, Italy.
⁷ Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, and Maternal and Children's Sciences, University of Genoa, Genoa, Italy.
⁸ Jack H. Miller Magnetoencephalography Center, Helen DeVos Childrens Hospital, Grand Rapids, Michigan, USA.
⁹ Department of Pediatrics and Human Development, Michigan State University, East Lansing, Michigan, USA.
¹⁰ Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK.
¹¹ Division of Psychology, Values, Ideologies and Social Contexts of Education, Faculty of Education and Psychology, University of Oulu, Oulu, Finland.

PMID: 38687176
DOI: 10.1111/epi.17996

Abstract

Objective: Postsurgical seizure freedom in drug-resistant epilepsy (DRE) patients varies from 30% to 80%, implying that in many cases the current approaches fail to fully map the epileptogenic zone (EZ). We aimed to advance a novel approach to better characterize epileptogenicity and investigate whether the EZ encompasses a broader epileptogenic network (EpiNet) beyond the seizure zone (SZ) that exhibits seizure activity.

Methods: We first used computational modeling to test putative complex systems-driven and systems neuroscience-driven mechanistic biomarkers for epileptogenicity. We then used these biomarkers to extract features from resting-state stereoelectroencephalograms recorded from DRE patients and trained supervised classifiers to localize the SZ against gold standard clinical localization. To further explore the prevalence of pathological features in an extended brain network outside of the clinically identified SZ, we also used unsupervised classification.

Results: Supervised SZ classification trained on individual features achieved accuracies of .6-.7 area under the receiver operating characteristic curve (AUC). Combining all criticality and synchrony features further improved the AUC to .85. Unsupervised classification discovered an EpiNet-like cluster of brain regions, in which 51% of brain regions were outside of the SZ. Brain regions in the EpiNet-like cluster engaged in interareal hypersynchrony and locally exhibited high-amplitude bistability and excessive inhibition, which was strikingly similar to the high seizure risk regime revealed by our computational modeling.

Significance: The finding that combining biomarkers improves SZ localization accuracy indicates that the novel mechanistic biomarkers for epileptogenicity employed here yield synergistic information. On the other hand, the discovery of SZ-like brain dynamics outside of the clinically defined SZ provides empirical evidence of an extended pathophysiological EpiNet.

Keywords: bistability; classification; criticality; epileptogenic zone; synchrony.

Abstract

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