Dynamics of cortical stability and seizure resilience in vivo
BORIS DOI
Abstract
The sudden emergence of dangerous seizures is the defining feature of epilepsy, but how and when the brain changes dynamics remain enigmatic. In the formalism of dynamical systems theory, seizure onset can be described as a critical transition between two alternative states: interictal and ictal. My PhD research aims at studying these transitions, specifically by examining the concept of resilience, which, in the present context, refers to a system’s ability to withstand perturbations without changing its state. It has been proposed that both the development of epilepsy and the emergence of seizures are a result of respectively a chronic and then transitory loss of resilience. Importantly, until the point of failure, changes in the system’s resilience will have minimal impact on its observable state. By monitoring a system’s reaction to minor perturbations, it has been theorized that changes in resilience could nevertheless be detected. In this study, we combined theoretical, experimental and clinical approaches to test this hypothesis, and to develop methodologies to delineate the landscape of physiological and pathological cortical excitability, including quantifications of seizure thresholds.
By using a mathematical model of seizures, and optogenetics stimulations in mice and intracranial electrical stimulations in patients with epilepsy, we were able to demonstrate how small perturbations can be used to gauge cortical stability and how larger perturbations can overcome cortical resilience in a measurable way, resulting in self-sustained seizures. Both phenomena were closely correlated and influenced by the underlying level of cortical excitability, which was tightly modulated in vivo through pharmacological intervention on the GABA-A receptor. Additionally, using a machine-learning approach on EEG snapshots, we confirmed that active and passive markers can be used to decode momentary states of cortical excitability and therefore the latent seizure resilience. Ultimately, this research helps to improve our understanding of the underlying mechanisms of seizure onsets and to develop new methods for predicting and preventing seizures.
By using a mathematical model of seizures, and optogenetics stimulations in mice and intracranial electrical stimulations in patients with epilepsy, we were able to demonstrate how small perturbations can be used to gauge cortical stability and how larger perturbations can overcome cortical resilience in a measurable way, resulting in self-sustained seizures. Both phenomena were closely correlated and influenced by the underlying level of cortical excitability, which was tightly modulated in vivo through pharmacological intervention on the GABA-A receptor. Additionally, using a machine-learning approach on EEG snapshots, we confirmed that active and passive markers can be used to decode momentary states of cortical excitability and therefore the latent seizure resilience. Ultimately, this research helps to improve our understanding of the underlying mechanisms of seizure onsets and to develop new methods for predicting and preventing seizures.
Date of Publication
2024
Year of graduation
2023
Theses Type
dissertation
Subject(s)
Language(s)
en
Author(s)
Lepeu, Gregory |
Faculty/Graduate School
Institute
Access(Rights)
open.access
Primary OA Publication
true