Automatic detection of spike and wave discharges in the EEG of genetic absence epilepsy rats from Strasbourg.

Genetic absence epilepsy rats from Strasbourg are a strain of Wistar rats in which all animals exhibit spontaneous occurrences of spike and wave discharges (SWDs) in the EEG. In this paper, we propose a novel method for the detection of SWDs, based on the key observation that SWDs are quasi-periodic signals. The method consists of the following steps: 1) calculation of the spectrogram; 2) estimation of the background spectrum and detection of stimulation artifacts; 3) harmonic analysis with continuity analysis to estimate the fundamental frequency; and 4) classification based on the percentage of power in the harmonics to the total power of the spectrum. We evaluated the performance of the novel detection method and six SWD/seizure detection methods from literature on a large database of labeled EEG data consisting of two datasets running to a total duration of more than 26 days of recording. The method outperforms all tested SWD/seizure detection methods, showing a sensitivity and selectivity of 96% and 97%, respectively, on the first test set, and a sensitivity and selectivity of 94% and 92%, respectively, on the second test set. The detection performance is less satisfactory (as for all other methods) for EEG fragments showing more irregular and less periodic SWDs.

Detection of focal epileptiform events in the EEG by spatio-temporal dipole clustering.

OBJECTIVE: Methods for the detection of epileptiform events can be broadly divided into two main categories: temporal detection methods that exploit the EEG's temporal characteristics, and spatial detection methods that base detection on the results of an implicit or explicit source analysis. We describe how the framework of a spatial detection method was extended to improve its performance by including temporal information. This results in a method that provides (i) automated localization of an epileptogenic focus and (ii) detection of focal epileptiform events in an EEG recording. For the detection, only one threshold value needs to be set. METHODS: The method comprises five consecutive steps: (1) dipole source analysis in a moving window, (2) automatic selection of focal brain activity, (3) dipole clustering to arrive at the identification of the epileptiform cluster, (4) derivation of a spatio-temporal template of the epileptiform activity, and (5) template matching. Routine EEG recordings from eight paediatric patients with focal epilepsy were labelled independently by two experts. The method was evaluated in terms of (i) ability to identify the epileptic focus, (ii) validity of the derived template, and (iii) detection performance. The clustering performance was evaluated using a leave-one-out cross validation. Detection performance was evaluated using Precision-Recall curves and compared to the performance of two temporal (mimetic and wavelet based) and one spatial (dipole analysis based) detection methods. RESULTS: The method succeeded in identifying the epileptogenic focus in seven of the eight recordings. For these recordings, the mean distance between the epileptic focus estimated by the method and the region indicated by the labelling of the experts was 8mm. Except for two EEG recordings where the dipole clustering step failed, the derived template corresponded to the epileptiform activity marked by the experts. Over the eight EEGs, the method showed a mean sensitivity and selectivity of 92 and 77%, respectively. CONCLUSIONS: The method allows automated localization of the epileptogenic focus and shows good agreement with the region indicated by the labelling of the experts. If the dipole clustering step is successful, the method allows a detection of the focal epileptiform events, and gave a detection performance comparable or better to that of the other methods. SIGNIFICANCE: The identification and quantification of epileptiform events is of considerable importance in the diagnosis of epilepsy. Our method allows the automatic identification of the epileptic focus, which is of value in epilepsy surgery. The method can also be used as an offline exploration tool for focal EEG activity, displaying the dipole clusters and corresponding time series.

A hybrid algorithm for solving the EEG inverse problem from spatio-temporal EEG data.

Epilepsy is a neurological disorder caused by intense electrical activity in the brain. The electrical activity, which can be modelled through the superposition of several electrical dipoles, can be determined in a non-invasive way by analysing the electro-encephalogram. This source localization requires the solution of an inverse problem. Locally convergent optimization algorithms may be trapped in local solutions and when using global optimization techniques, the computational effort can become expensive. Fast recovery of the electrical sources becomes difficult that way. Therefore, there is a need to solve the inverse problem in an accurate and fast way. This paper performs the localization of multiple dipoles using a global-local hybrid algorithm. Global convergence is guaranteed by using space mapping techniques and independent component analysis in a computationally efficient way. The accuracy is locally obtained by using the Recursively Applied and Projected-MUltiple Signal Classification (RAP-MUSIC) algorithm. When using this hybrid algorithm, a four times faster solution is obtained.

Dipole estimation errors due to differences in modeling anisotropic conductivities in realistic head models for EEG source analysis.

To improve the EEG source localization in the brain, the conductivities used in the head model play a very important role. In this study, we focus on the modeling of the anisotropic conductivity of the white matter. The anisotropic conductivity profile can be derived from diffusion weighted magnetic resonance images (DW-MRI). However, deriving these anisotropic conductivities from diffusion weighted MR images of the white matter is not straightforward. In the literature, two methods can be found for calculating the conductivity from the diffusion weighted images. One method uses a fixed value for the ratio of the conductivity in different directions, while the other method uses a conductivity profile obtained from a linear scaling of the diffusion ellipsoid. We propose a model which can be used to derive the conductivity profile from the diffusion tensor images. This model is based on the variable anisotropic ratio throughout the white matter and is a combination of the linear relationship as stated in the literature, with a constraint on the magnitude of the conductivity tensor (also known as the volume constraint). This approach is stated in the paper as approach A. In our study we want to investigate dipole estimation differences due to using a more simplified model for white matter anisotropy (approach B), while the electrode potentials are derived using a head model with a more realistic approach for the white matter anisotropy (approach A). We used a realistic head model, in which the forward problem was solved using a finite difference method that can incorporate anisotropic conductivities. As error measures we considered the dipole location error and the dipole orientation error. The results show that the dipole location errors are all below 10 mm and have an average of 4 mm in gray matter regions. The dipole orientation errors ranged up to 66.4 degrees, and had a mean of, on average, 11.6 degrees in gray matter regions. In a qualitative manner, the results show that the orientation and location error is dependent on the orientation of the test dipole. The location error is larger when the orientation of the test dipole is similar to the orientation of the anisotropy, while the orientation error is larger when the orientation of the test dipole deviates from the orientation of the anisotropy. From these results, we can conclude that the modeling of white matter anisotropy plays an important role in EEG source localization. More specifically, accurate source localization will require an accurate modeling of the white matter conductivity profile in each voxel.

Neuromodulation with levetiracetam and vagus nerve stimulation in experimental animal models of epilepsy.

Epilepsy is a neurological disorder consisting of recurrent seizures, resulting from excessive, uncontrolled electrical activity in the brain. Epilepsy treatment is successful in the majority of the cases; however; still one third of the epilepsy patients are refractory to treatment. Besides the ongoing research on the efficacy of antiepileptic treatments in suppressing seizures (anti-seizure effect), we want to seek for therapies that can lead to plastic, neuromodulatory changes in the epileptic network. Neuropharmacological therapy with levetiracetam (LEV) and vagus nerve stimulation (VNS) are two novel treatments for refractory epilepsy. LEV acts rapidly on seizures in both animal models and humans. In addition, preclinical studies suggest that LEV may have antiepileptogenic and neuroprotective effects, with the potential to slow or arrest disease progression. VNS as well can have an immediate effect on seizures in epilepsy models and patients with, in addition, a cumulative effect after prolonged treatment. Studies in man are hampered by the heterogeneity of patient populations and the difficulty to study therapy-related effects in a systematic way. Therefore, investigation was performed utilizing two rodent models mimicking epilepsy in humans. Genetic absence epilepsy rats from Strasbourg (GAERS) have inborn absence epilepsy and Fast rats have a genetically determined sensitivity for electrical amygdala kindling, which is an excellent model of temporal lobe epilepsy. Our findings support the hypothesis that treatment with LEV and VNS can be considered as neuromodulatory: changes are induced in central nervous system function or organization as a result of influencing and initiating neurophysiological signals.

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.

Muscle and eye movement artifact removal prior to EEG source localization.

Muscle and eye movement artifacts are very prominent in the ictal EEG of patients suffering from epilepsy, thus making the dipole localization of ictal activity very unreliable. Recently, two techniques (BSS-CCA and pSVD) were developed to remove those artifacts. The purpose of this study is to assess whether the removal of muscle and eye movement artifacts improves the EEG dipole source localization. We used a total of 8 EEG fragments, each from another patient, first unfiltered, then filtered by the BSS-CCA and pSVD. In both the filtered and unfiltered EEG fragments we estimated multiple dipoles using RAP-MUSIC. The resulting dipoles were subjected to a K-means clustering algorithm, to extract the most prominent cluster. We found that the removal of muscle and eye artifact results to tighter and more clear dipole clusters. Furthermore, we found that localization of the filtered EEG corresponded with the localization derived from the ictal SPECT in 7 of the 8 patients. Therefore, we can conclude that the BSS-CCA and pSVD improve localization of ictal activity, thus making the localization more reliable for the presurgical evaluation of the patient.

Extracting the spike process from the EEG by spatially constrained ICA.

Epileptic patients often show interictal epileptic discharges (IED's) in the electroencephalogram (EEG) recorded between seizures. This epileptiform activity is in many cases related to the location of the seizure onset, and is believed to reflect the frequency of the seizures. We present a fully automated technique that is able to extract the IED's from the EEG, despite the obscuring artifacts. The presented technique is based on a multi-objective optimization by maximizing the signal's kurtosis and minimizing its distance to a defined template. Preliminary results show that this technique automatically extracts a source on which spike detection techniques should perform better than on the regular channel selection procedure.

Chronic levetiracetam treatment early in life decreases epileptiform events in young GAERS, but does not prevent the expression of spike and wave discharges during adulthood.

PURPOSE: In Genetic Absence Epilepsy Rats from Strasbourg (GAERS), age-related absence seizures start to appear from postnatal day (PN) 30 concomitant with 'spike and wave discharges' (SWDs) appearing on cortical EEG recordings. The aim of this study was to investigate the effect of early chronic levetiracetam (LEV) treatment on the development of SWDs in young and adult GAERS. METHODS: From PN 23 until PN 60, LEV (54 mg/kg, i.p.) was administered once daily to GAERS (n=8), while control GAERS (n=7) received saline (0.9% NaCl, i.p.). All animals were implanted with four epidural EEG electrodes at PN 51. EEG was recorded for 3h daily, during the last 4 days of the treatment (PN 57-PN 60) and during 4 additional days after treatment had been terminated (PN 61-PN 64). The animals were monitored again at the age of 4 months (PN 120-PN 124), about 2 months after the last administration of LEV. RESULTS: During treatment, epileptiform events in the LEV group were significantly reduced (62%, P<0.05) in comparison with the control group. During the following 4 days, epileptiform events were reduced in the LEV group, with an average difference of 53% (P=0.064). Once the animals had reached adult age, there was no difference in epileptiform events between the LEV group and controls. CONCLUSION: In this study, chronic LEV administration induced a reduction in epileptiform events in young GAERS. This effect persisted to some extent after treatment cessation (PN 61-PN 64), which might indicate a slowing down of epileptogenic processes. However, at the age of 4 months all animals revealed a similar expression of epileptiform discharges.

A finite difference method with reciprocity used to incorporate anisotropy in electroencephalogram dipole source localization.

Many implementations of electroencephalogram (EEG) dipole source localization neglect the anisotropical conductivities inherent to brain tissues, such as the skull and white matter anisotropy. An examination of dipole localization errors is made in EEG source analysis, due to not incorporating the anisotropic properties of the conductivity of the skull and white matter. First, simulations were performed in a 5 shell spherical head model using the analytical formula. Test dipoles were placed in three orthogonal planes in the spherical head model. Neglecting the skull anisotropy results in a dipole localization error of, on average, 13.73 mm with a maximum of 24.51 mm. For white matter anisotropy these values are 11.21 mm and 26.3 mm, respectively. Next, a finite difference method (FDM), presented by Saleheen and Kwong (1997 IEEE Trans. Biomed. Eng. 44 800-9), is used to incorporate the anisotropy of the skull and white matter. The FDM method has been validated for EEG dipole source localization in head models with all compartments isotropic as well as in a head model with white matter anisotropy. In a head model with skull anisotropy the numerical method could only be validated if the 3D lattice was chosen very fine (grid size < or = 2 mm).

The acute and chronic effect of vagus nerve stimulation in genetic absence epilepsy rats from Strasbourg (GAERS).

PURPOSE: The aim of this study was to evaluate the efficacy of acute and chronic vagus nerve stimulation (VNS) in genetic absence epilepsy rats from Strasbourg (GAERS). This is a validated model for absence epilepsy, characterized by frequent spontaneous absences concomitant with spike and wave discharges (SWD) on the EEG. Although absences are a benign form of seizures, it is conceptually important to investigate the efficacy of VNS in a controlled study by using this chronic epilepsy model. METHODS: Both control and stimulated GAERS were implanted with five epidural EEG electrodes and a stimulation electrode around the left vagus nerve. In the first experiment, VNS was given when SWD occurred in the EEG; this was repeated the next day. A randomized crossover design (n = 8) was used. In the chronic experiment, GAERS underwent EEG monitoring during a first baseline week. During the second week, the treated group (n = 18) received VNS; controls (n = 13), on the other hand, only underwent EEG recordings. RESULTS: On day 1 of the acute VNS experiment, the mean duration of the SWD when VNS was applied was higher than in baseline conditions (p < 0.05). However, on day 2, there was no difference in mean duration of the SWD. In the chronic VNS experiment, no statistically significant differences were found between control and stimulated GAERS. CONCLUSIONS: Acute VNS applied shortly after the onset of SWD prolonged the mean duration of SWD in GAERS at least during the first day of VNS. Chronic stimulation hardly affected SWD in GAERS.

Acute vagus nerve stimulation does not suppress spike and wave discharges in genetic absence epilepsy rats from Strasbourg.

We evaluated the efficacy of vagus nerve stimulation (VNS) in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a validated model for absence epilepsy. In the first experiment, we investigated whether VNS applied at seizure onset can interrupt spike and wave discharges (SWD). In the second experiment, we investigated whether SWD are suppressed or shortened in duration when VNS is applied several hours per day. Both control and VNS groups underwent EEG and VNS electrode implantation. For the first experiment, a randomized crossover design was used. Stimuli (amplitude: 3 V; frequency: 30 Hz; pulse duration: 500 micros) were given when an SWD occurred on the EEG. The experiment was repeated the next day. In the second experiment, treated animals were stimulated (amplitude: 1.5 mA; frequency: 30 Hz; pulse duration: 500 micros; on/off time cycle: 30 s / 5 min) for 3h per day, during five consecutive days. In the first experiment, the duration of the SWD was increased on day 1, (P < 0.05). There was no difference in SWD duration on Day 2. In the second experiment, no significant differences could be found in number, duration and EEG frequency of SWD. VNS applied at the onset of an SWD can prolong the duration of SWD in GAERS. As a 5-day stimulation protocol had no effect, long-term VNS might be necessary to affect SWD.

Neurostimulation for refractory epilepsy.

Neurostimulation is an emerging treatment for refractory epilepsy. To date the precise mechanism of action remains to be elucidated. Better insight in the mechanism of action may identify seizure types or syndromes that respond to such a treatment and may guide the search for optimal stimulation parameters and finally improve clinical efficacy. In the past ten years some progress has been made through neurophysiological, neuroanatomical, neurochemical and cerebral blood flow studies in patients and animals undergoing vagus nerve stimulation (VNS). Interesting results have been found in VNS-treated patients that underwent evoked potential measurements, cerebrospinal fluid investigation, neuropsychological testing and PET, SPECT and fMRI testing. Desynchronisation of abnormal synchronous epileptic activity is one of the hypotheses on the mode of action that might primarily be responsible for an anti-seizure effect. There is however increasing evidence from research and clinical observation that VNS might establish a true and long-term anti-epileptic effect. It has been shown that VNS influences neurotransmission in the brain and provokes long-term changes in cerebral blood flow in areas crucial for epileptogenesis such as the thalamus and medial temporal lobe structures. Deep brain stimulation (DBS) for epilepsy has regained interest. Central nervous system structures known to play a key role in the epileptogenic network such as the thalamus and subthalamic nucleus have been targeted. Another approach is to target the ictal onset zone such as the medial temporal lobe. At Ghent University Hospital 10 patients have been treated with long-term amygdalohippocampal DBS. Several hypotheses have been raised for the mechanism of action of DBS for refractory seizures. Seizure reduction may be due to a microlesion caused by electrode insertion or by provoking a reversible functional lesion due to the effect of electrical current on hyperexcitable tissue. Neurophysiological techniques such as evoked potentials monitoring and intraoperative single unit potential recordings may guide correct electrode placement, individual DBS titration and elucidation of the mechanims of action of DBS for epilepsy.