Quantifying antiepileptic drug effects using intrinsic excitability measures

Abstract

Pathologic increases in excitability levels of cortical tissue commonly underlie the initiation and spread of seizure activity in patients with epilepsy. By reducing the excitability levels in neural tissue, antiepileptic drug (AED) pharmacotherapy aims to reduce seizure severity and frequency. However, AEDs may also bring about adverse effects, which have been reported to increase with higher AED load. Measures that monitor the dose-dependent effects of AEDs on cortical tissue and quantify its excitability level are therefore of prime importance for efficient clinical care and treatment but have been difficult to identify. Here, we systematically analyze continuous multiday electrocorticography (ECoG) data from 10 patients under different levels of AED load and derive the recently proposed intrinsic excitability measures (IEMs) from different brain regions and across different frequency bands. We find that IEMs are significantly negatively correlated with AED load (prescribed daily dose/defined daily dose). Furthermore, we demonstrate that IEMs derived from different brain regions can robustly capture global changes in the degree of excitability. These results provide a step toward the ultimate goal of developing a reliable quantitative measure of central physiologic effects of AEDs in patients with epilepsy.

Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy

“…Many of the patients in our study underwent antiepileptic medication reduction as part of presurgical monitoring, making it difficult to disentangle the effects of changing drug levels from other potential slow-varying modulators of seizure pathways. Changes in antiepileptic medication can impact neural excitability (68)(69)(70), and medication tapering increases seizure likelihood in most patients (16,71); however, it is controversial whether it also affects seizure patterns (9,16,56,71). In some cases, it appears that medication tapering reveals latent seizure pathways that are suppressed by medication (9) or allows existing pathways to further progress (e.g., the secondary generalization of typically focal seizures) (16).…”

Maintained avalanche dynamics during task-induced changes of neuronal activity in nonhuman primates

“…Our demonstration of scale-invariant size distributions suggests avalanche dynamics are maintained throughout task performance, which should mirror a sustained average synchrony among cortical sites. Previous studies have shown overall phase-synchronization between sites sensitively captures fast dynamical changes in a network ( Kitzbichler et al, 2009 ; Yang et al, 2012 ), in particular at higher frequencies ( Meisel et al, 2016 ). In line with our results from adaptive binning and thresholding, levels of LFP synchrony R (see Materials and methods) were not different across epochs in monkey A (Left: 0.56 ± 0.015, 0.56 ± 0.01 and 0.56 ± 0.01; Right: 0.56 ± 0.01, 0.55 ± 0.01 and 0.56 ± 0.004; mean ± standard deviation for BASE, EARLY and LATE respectively; p>0.05; two-tailed paired student’s t-test) as well as in monkey B (BASE, 0.450 ± 0.003; mean ± standard deviation; vs. PRE, 0.452 ± 0.003; vs. POST, 0.455 ± 0.003; p>0.05).…”

Seizure pathways: A model-based investigation

“…Data driven modeling may provide the opportunity to identify which drug could be helpful for different classes of seizure, as different mechanisms of anti-epileptic drug action may preferentially effect the various connectivity parameters, though further validation of model predictions is needed to translate estimation results to clinical practice. Levels of AEDs have been related to features of the EEG signal [ 59 , 60 ]. Therefore, it may be possible to extend this relationship to predicting the mode of action of an AED from an individual’s EEG.…”