Abstract
At least one-third of all people with epilepsy have seizures that remain poorly controlled despite an increasing number of available anti-epileptic drugs (AEDs). Often, there is an initial good response to a newly introduced AED, which may last up to months, eventually followed by the return of seizures thought to be due to the development of tolerance. We introduce a framework within which the interplay between AED response and brain networks can be explored to understand the development of tolerance. We use a computer model for seizure generation in the context of dynamic networks, which allows us to generate an ‘in silico’ electroencephalogram (EEG). This allows us to study the effect of changes in excitability network structure and intrinsic model properties on the overall seizure likelihood. Within this framework, tolerance to AEDs – return of seizure-like activity – may occur in 3 different scenarios: 1) the efficacy of the drug diminishes while the brain network remains relatively constant; 2) the efficacy of the drug remains constant, but connections between brain regions change; 3) the efficacy of the drug remains constant, but the intrinsic excitability within brain regions varies dynamically. We argue that these latter scenarios may contribute to a deeper understanding of how drug resistance to AEDs may occur.
Highlights
Epilepsy is a serious brain disorder with a lifetime incidence of around 1%
One of the many challenges for neurologists treating epilepsy is that at least one-third of all patients have seizures that remain poorly controlled despite the increasing number of anti-epileptic drugs (AEDs) available, so-called drug-resistant epilepsy (DRE)
Our starting point is an equation previously introduced in the context of epilepsy [9]: z0 1⁄4 f ðzÞ þ αdw 0 1⁄4 ðλ−1 þ iωÞz þ 2zz2−zz4 þ αdw0. This is a stochastic differential equation and is used to describe the dynamics within a single brain region. Such an equation describes the evolution over time of a variable z, whose output may be thought of as a proxy for the electrographic activity recorded within a single channel of EEG overlying that brain region
Summary
Epilepsy is a serious brain disorder with a lifetime incidence of around 1%. One of the many challenges for neurologists treating epilepsy is that at least one-third of all patients have seizures that remain poorly controlled despite the increasing number of anti-epileptic drugs (AEDs) available, so-called drug-resistant epilepsy (DRE). Several mechanisms have been proposed to explain this phenomenon, including metabolic (pharmacokinetic) tolerance, due to induction of AED-metabolizing enzymes or blood–brain-barrier multidrug transporter proteins, and functional (pharmacodynamic) tolerance, related to alteration of AED targets
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