P. Boon

Dynamics of epileptic phenomena determined from statistics of ictal transitions

In this paper, we investigate the dynamical scenarios of transitions between normal and paroxysmal state in epilepsy. We assume that some epileptic neural network are bistable i.e., they feature two operational states, ictal and interictal that co-exist. The transitions between these two states may occur according to a Poisson process, a random walk process or as a result of deterministic time-dependent mechanisms. We analyze data from animal models of absence epilepsy, human epilepsies and in vitro models. The distributions of durations of ictal and interictal epochs are fitted with a gamma distribution. On the basis of qualitative features of the fits, we identify the dynamical processes that may have generated the underlying data. The analysis showed that the following hold. 1) The dynamics of ictal epochs differ from those of interictal states. 2) Seizure initiation can be accounted for by a random walk process while seizure termination is often mediated by deterministic mechanisms. 3) In certain cases, the transitions between ictal and interictal states can be modeled by a Poisson process operating in a bistable network. These results imply that exact prediction of seizure occurrence is not possible but termination of an ictal state by appropriate counter stimulation might be feasible.

Long-term results of vagus nerve stimulation in refractory epilepsy

Vagus nerve stimulation (VNS) is an adjunctive antiepileptic treatment for patients with refractory epilepsy. Limited information on long-term treatment with VNS is available. The purpose of this paper is to present our experience with VNS with a follow-up of up to 4 years. Twenty-five patients (13 females and 12 males) with refractory partial epilepsy were treated with VNS. The first 15 patients with a mean age of 30 years and a mean duration of epilepsy of 17.5 years have sufficient follow-up for analysis. Mean post-implantation follow-up was 29 months and mean stimulation output 2.25 mA. There was a mean seizure frequency reduction from 14 complex partial seizures (CPS) per month before implantation to 8 CPS per month after implantation (P = 0.0016; Wilcoxon signed-rank rest (WSRT)). The mean maximum CPS-free interval changed from 9 to 312 days (P = 0.0007; WSRT). Six patients were free of CPS for at least one year. In one patient, one antiepileptic drug (AED) was tapered; in 10 patients, AEDs remained unchanged; in four, one adjunctive AED was administered. Side effects occurred in six patients, three of whom required a temporary reduction of output current. Nine patients reported no side effects at all. Treatment with VNS remains effective in the long-term. In this series 4 / 15 (27%) patients with highly refractory epilepsy experienced entirely seizure-free intervals of 12 months or more.

An investigation of the phase locking index for measuring of interdependency of cortical source signals recorded in the EEG

The phase locking index (PLI) was introduced to quantify in a statistical sense the phase synchronization of two signals. It has been commonly used to process biosignals. In this article, we investigate the PLI for measuring the interdependency of cortical source signals (CSSs) recorded in the Electroencephalogram (EEG). To this end, we consider simple analytical models for the mapping of simulated CSSs into the EEG. For these models, the PLI is investigated analytically and through numerical simulations. An evaluation is made of the sensitivity of the PLI to the amount of crosstalk between the sources through biological tissues of the head. It is found that the PLI is a useful interdependency measure for CSSs, especially when the amount of crosstalk is small. Another common interdependency measure is the coherence. A direct comparison of both measures has not been made in the literature so far. We assess the performance of the PLI and coherence for estimation and detection purposes based on, respectively, a normalized variance and a novel statistical measure termed contrast. Based on these performance measures, it is found that the PLI is similar or better than the CM in most cases. This result is also confirmed through analysis of EEGs recorded from epileptic patients.

Combined detection and source analysis of epileptic EEG spikes

We present a method for the detection of focal epileptic spikes in the EEG (electroencephalogram). The method is based on the dipole source localisation technique and provides a source location estimate for each detected spike. In the first section of the paper, a theoretical introduction is given about dipole source localisation, followed by a description of the modifications that were made to it for a more efficient calculation. An additional decision variable is introduced to exploit the high amplitude of the spikes that are searched for, without however imposing constraints on the precise shape of the waveforms. In the next section the efficiency of the method is discussed on the basis of an experiment with an EEG measurement from an epilepsy patient. It is shown that the method is capable of detecting and localising most of the epileptic spikes present in the EEG, while producing only few false-positive detections.

Long-term evaluation of synchronization between scalp EEG signals in partial epilepsy

For the anticipation of epileptic seizures synchronization between signals from intracranial recorded EEG has been studied. Here, we present our first findings for scalp EEG. For 3 epilepsy patients 85 hours of scalp EEG were analyzed. After determining the instantaneous phase with the Hilbert transform, the level of synchrony was calculated for all possible electrode pairs within 4 defined groups. This was done for 14 frequency bands of 2Hz between 1 and 50Hz. As well during sleep as in the awake state we found a particular behavior of the synchrony levels in the pathological hemisphere. Furthermore, we found a similar sleep-wake cycle for the two temporal lobe epilepsy patients, not seen in the case of the patient with extra temporal lobe epilepsy. These results show an altered brain dynamics for epilepsy patients, which can give information on the localization of the epilepsy.

A new method for detection and source analysis of EEG spikes

In the past our research group has developed a method for the detection of focal epileptic EEG (electroencephalogram) spikes that is based on the dipole source localization technique and provides a source localization for each detected spike. In this paper we revisit this method and propose a more accurate explanation of its behavior. Based on this we (i) propose a new method for the detection of epileptic EEG spikes in which the eccentricity of the fitted dipole serves as a new decision variable (ii) conclude that for EEG spike detection one has to make a distinction between EEGs acquired during sleep and during wake.

The pharmacokinetics of [11C]methoxy-norchloroprogabidic acid, a potential PET tracer for GABA receptors in the brain

Abstract We have described the kinetic properties of [ 11 C]methoxy-norchloroprogabidic acid, a potential radioligand for the gamma-aminobutyric acid (GABA) receptor. Early metabolism in mice was negligible. Protein binding in human plasma was 89 ± 7%. Distribution volumes were 89.6 ± 29.4 l whereas the elimination half-life was 41.6 ± 14.3 min. Animal and human positron emission tomography (PET) data demonstrate limited uptake of the activity in brain tissue. Displacement studies in mice suggest a nonsignificant fraction of specific receptor binding. [ 11 C] Methoxy-norchloroprogabidic acid is therefore unsuitable for brain PET.

Analysis of the Phase Locking Index for Measuring of Interdependency of Cortical Signals Recorded in the EEG

The phase locking index (PLI) was introduced to quantify in a statistical sense the phase synchronization of two signals. It has been commonly used to process biosignals. In this paper, we analyze the PLI for measuring the interdependency of cortical source signals (CSSs) recorded in the Electroencephalogram (EEG). The main focus of the analysis is the probability density function, which describes the sensitivity of the PLI to the joint noise ensemble in the CSSs. Since this function is mathematically intractable, we derive approximations and analyze them for a simple analytical model of the CSS mixture in the EEG. The accuracies of the approximate probability density functions (APDFs) are evaluated using simulations for the model. The APDFs are found sufficiently accurate and thus are applicable for practical intents and purposes. They can hence be used to determine the confidence intervals and significance levels for detection methods for interdependencies, e.g., between cortical signals recorded in the EEG.