[Epileptic seizures and epilepsy after a stroke : Incidence, prevention and treatment]. / Epileptische Anfälle und Epilepsie nach einem Schlaganfall : Inzidenz, Prävention und Behandlung.

Following stroke, 3-6% of patients develop acute symptomatic seizures within the first 7 days. The rate is higher after cerebral haemorrhage compared to ischaemia. In 10-12% of patients, after more than 7 days unprovoked seizures occur. Due to these low incidence rates, primary prophylaxis with antiepileptic drugs is generally not necessary. Following one acute symptomatic seizure, recurrence risk within the first 7 days post-stroke is 10-20%, generally arguing against secondary prophylaxis with an antiepileptic drug. In clinical practice however, antiepileptic drug treatment in this constellation is often initiated. If this is done, the antiepileptic drug should be withdrawn soon after the acute phase, as the long-term risk for manifestation of an unprovoked seizure is approximately 30%. Following one post-stroke unprovoked seizure, recurrence risk within the next 10 years is more than 70%, this defines epilepsy. In this case, antiepileptic drug treatment is regularly recommended.

Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers.

Current criteria identifying patients with ultra-high risk of psychosis (UHR) have low specificity, and less than one-third of UHR cases experience transition to psychosis within 3 years of initial assessment. We explored whether a Bayesian probabilistic multimodal model, combining baseline historical and clinical risk factors with biomarkers (oxidative stress, cell membrane fatty acids, resting quantitative electroencephalography (qEEG)), could improve this specificity. We analyzed data of a UHR cohort (n=40) with a 1-year transition rate of 28%. Positive and negative likelihood ratios were calculated for predictor variables with statistically significant receiver operating characteristic curves (ROCs), which excluded oxidative stress markers and qEEG parameters as significant predictors of transition. We clustered significant variables into historical (history of drug use), clinical (Positive and Negative Symptoms Scale positive, negative and general scores and Global Assessment of Function) and biomarker (total omega-3, nervonic acid) groups, and calculated the post-test probability of transition for each group and for group combinations using the odds ratio form of Bayes' rule. Combination of the three variable groups vastly improved the specificity of prediction (area under ROC=0.919, sensitivity=72.73%, specificity=96.43%). In this sample, our model identified over 70% of UHR patients who transitioned within 1 year, compared with 28% identified by standard UHR criteria. The model classified 77% of cases as very high or low risk (P>0.9, <0.1) based on history and clinical assessment, suggesting that a staged approach could be most efficient, reserving fatty-acid markers for 23% of cases remaining at intermediate probability following bedside interview.

EKG abnormalities in children and adolescents with symptomatic temporal lobe epilepsy.

BACKGROUND: Changes in cardiac rate and rhythm are often found in adult patients with temporal lobe epilepsy (TLE) and could be involved in the pathogenesis of sudden unexplained death (SUDEP). However, little is known about heart rate (HR) variability in pediatric patients with TLE. OBJECTIVES: To investigate ictal and peri-ictal HR abnormalities in children and adolescents with medically refractory symptomatic TLE and to determine the influence of focus localization and laterality. METHODS: Patients younger than 18 years, with drug-resistant unilateral symptomatic TLE and presenting with at least one habitual complex partial seizure (CPS) during presurgical noninvasive video-EEG monitoring, were enrolled. Synchronous single-channel EKG recordings were analyzed during the preictal, ictal, and postictal stages. RESULTS: Twenty patients fulfilled the inclusion criteria. Seventy-two temporal lobe seizures (TLSs) were analyzed. Ictal tachycardia was found in 71 TLSs (98%), whereas ictal bradycardia was not observed. During preictal stages, tachycardia occurred in 20 seizures and mild bradycardia in 3. In 44 seizures (62%), tachycardia was still present >60 seconds after EEG seizure termination. Cluster analysis revealed significant differences in HR evolution depending on location and side of seizure onset: Early and high HR increase was primarily associated with right mesial TLSs. CONCLUSIONS: Cardiovascular dysregulation is common during temporal lobe CPSs in children. These results confirm a right hemispheric lateralization of sympathetic cardiac control.

Identification of the stimulated hemiretina in primary school children and adults based on left and right hemifield pattern reversal visual evoked potentials--a comparative study.

OBJECTIVES: The analysis of left and right hemifield pattern-reversal visual evoked potentials (PVEPs) in children and the identification of the stimulated hemiretina testing different identification procedures previously applied to adults. METHODS: Lateral hemifield PVEPs were recorded in 40 children (6-11 years) and 27 adults (25-40 years) from, at least, 19 standard electrodes. Two procedures were tested for the determination of the stimulated hemifield: firstly, the evaluation of the values of instantaneous frequency at the occipital electrodes at P100 latency (determined by the global field power), and secondly, the application of a generalised dynamic neural network (GDNN) using the PVEP time course at selected electrode positions as the external input. RESULTS: P100 latency as well as P100 amplitude over the contralateral occiput in children were significantly greater than in adults. Contrary to the behaviour in adults, instantaneous frequency is not a robust identifier of left and right hemiretina stimulation in children. The best identification performances were achieved when using group trained GDNNs with the bipolar difference signals of electrodes P3/P4 or T5/T6 as the external input. CONCLUSIONS: The PVEPs at electrodes P3/P4 and T5/T6 contain essential information for the determination of the stimulated hemifield. This should be further considered during the development of on-line procedures for automatic PVEP detection in future studies.

Localizing value of epileptic visual auras.

It is difficult to differentiate between seizures of occipital or temporal lobe origin in patients with focal epileptic seizures associated with visual aura. These are often suspected to originate from the visual cortex, which causes reluctance to propose resection as treatment for the affected patient. To determine the value of localizing different types of visual auras, we report on 20 patients experiencing visual aura from a series of 878 surgically treated patients suffering from intractable focal seizures. In all of these patients, a morphological abnormality was identified on MRI (n = 18) or cranial CT (n = 2). These abnormalities were shown to represent the morphological correlate of the epileptogenic zone in each case, as demonstrated by intracranial ictal EEG recordings and/or seizure freedom after focal resective surgery. Elementary hallucinations, illusions and visual loss were reported not only by all patients with occipital lobe epilepsy, but also by patients with occipitotemporal and anteromedial temporal seizure onset. Complex hallucinations never occurred in occipital lobe seizures but were present in the two other groups. The same correlation was found for concentric changes of visual field (tunnel vision), a newly described ictal phenomenon. We conclude that elementary hallucinations, illusions and visual loss, although typical for occipital lobe epilepsy, can also occur in anteromedial temporal or occipitotemporal seizures and are therefore not a discordant feature in presurgical evaluation of patients with suspected temporal lobe epilepsy. Complex hallucinations and tunnel vision, however, should be considered concordant only with the assumption of an anteromedial temporal or occipitotemporal seizure onset.

Application of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures.

For many patients who are candidates for epilepsy surgery, non-invasive evaluation fails to provide sufficient information to permit surgical treatment. Since there are also definite risks and considerable costs associated with invasive procedures, new (non-invasive) techniques are required. This study provides empirical evidence that a non-linear approach applied to ictal surface electroencephalograms (EEGs) can help to delineate the area of seizure onset and may prove useful in complementing visual analysis of the EEG. Multichannel EEGs, recorded from eight patients with different drug-resistant localisation-related epilepsies, were analysed using the concept of correlation dimension and two extensions based on the pointwise dimension. The latter also provided results in cases where assessment of the correlation dimension was not feasible. Comparative values between 2 and 6 were accepted as the result of the algorithms, mostly 3-4 for the EEG channels strongly reflecting epileptic activity, and 4-6 for the other signals. The proportion of accepted pointwise values was usually 200-800% for strong epileptic EEG activity compared to the other data. The approach permitted the characterisation of the scalp area reflecting epileptic activity. The results obtained were in perfect concordance with those obtained during pre-surgical work-up and confirmed by the post-operative outcome.

Nonlinear dynamics of 3 Hz spike-and-wave discharges recorded during typical absence seizures in children.

One-channel routine recordings of the scalp electroencephalogram (EEG) from unmedicated children strictly classified as unprovoked typical (3 c/s) absence seizures were selected. The dynamics of spike-and-wave discharges (SWD) were then examined by means of autocorrelation, correlation dimension, averaged pointwise dimension and largest Lyapunov exponent. For one EEG signal with pronounced spike-and-wave (SW) patterns, these measures were used complementary to a surrogate data method, a nonlinear (SETAR) modeling approach, and a SW simulation procedure providing five types of SW test signals. The SETAR model exhibited stationary SW dynamics, visually very similar to the EEG target signal, and with clear nonlinear structure. According to the results, the EEG episodes investigated represent low-dimensional dynamics, possibly recorded during nonstationary periods. Arguments that justify the assumption of deterministic chaos in our EEG signals were not obtained with the current methods. From the results one may conclude that two global oscillatory modes are present for the model, and three modes are active during the EEG recording period.

Simultaneous spike detection and topographic classification in pediatric surface EEGs.

In this study, an algorithm is introduced for the automatic detection and simultaneous topographic classification of interictal regional spike activity in pediatric surface EEG records. The algorithm is based on the classification of the topographic distribution of instantaneous power by means of a 'group' trained classifier. The results of automatic spike analysis were compared with the decisions of two experienced electroencephalographers. Four routine EEG records exhibiting (multi)regional spikes were examined. The mean selectivity for the automatic spike detector was 84.6% (mean sensitivity 88.1%, mean specificity 89.3%) and for the electroencephalographers 85.3%. All spikes detected by the algorithm were simultaneously classified according to their topographic characteristics. The results of automatic spike classification (lateralization/localization) corresponded to the results of visual analysis.

Analysis and classification of interictal spike discharges in benign partial epilepsy of childhood on the basis of the Hilbert transformation.

The spatial distribution of instantaneous power during the occurrence of rolandic spikes (computed via Hilbert transformation) can be utilized for classification of topographically different spike types. By visual analysis of the instantaneous power maps we found seven characteristic spike classes which correspond to the results of visual analysis of potential distribution. A neural network (NN) was trained with representatives of these classes. Single instantaneous power maps of 55/56 visually selected rolandic spikes, as well as map sequences of averaged spike segments (on-line) of 17 patients, were correctly classified by means of NN. The sensitivity of the NN for spikes from unknown patients was 98%. The classification scheme enables an objective classification of (multi-) regional spikes for selective averaging and for studies dealing with syndrome classification.

Slow potential shifts preceding human focal paroxysmal discharges, as represented by spikes of benign rolandic epilepsy of childhood.

We examined the slow potential shifts preceding interictal spikes in the scalp EEGs of the children with benign rolandic epilepsy of childhood (BREC). In contrast to our expectations and the observations reported by Stodieck and Wieser (1987), we were not able to detect focal negative slow shifts preceding interictal discharges. Possible reasons for this result are as follows. The cerebral event to which we triggered might have been too 'weak'. Another problem is that not every single spike generated in the deep reaches the surface. Thus, the moment, a spike occurs in the scalp-recordings does not necessarily represent the moment the brain changes from one state to another. The reference electrode might also play a role in obscuring any slow shift.

[Strategies of data reduction in computer-assisted EEG analysis in the time domain--measurement of theoretical aspects and redundancy relations within and between various strategies of data reduction]. / Strategien der Datenreduktion bei computerassistierter EEG-Analyse im Zeitbereich--Messtheoretische Gesichtspunkte und Redundanzverhältnisse innerhalb und zwischen verschiedenen Strategien der Datenreduktion.

The enormous amount of data after performing computer assisted EEG-analysis makes necessary reduction methods. Different strategies have been proposed. Traditionally the distribution of frequencies is shown by using frequency bands. The aim of this paper is to compare different strategies of data reduction regarding frequency distribution and to discuss results concerning validity. Three data reduction methods and their mutual relations will be discussed. The classification with regard to frequency bands, the computation of quartils of the frequency spectrum and the search for prominent frequencies. It will be shown wether or not calculated values are redundant and reflect identical information (latent dimensions).

[Data display and reduction in computer-assisted EEG analysis in the time domain]. / Zum Problem der Darstellung und Reduktion von Daten bei der computer-assistierten EEG-Analyse im Zeitbereich.

Analysis of EEG frequency spectra leads in two fields to problems demanding optimal data reduction methods: especially if topological aspects have to be considered, it is likely that the rather limited memory capacity of laboratory computer systems will be exceeded; furthermore severe methodological problems arise in statistical analysis of combined data sets, including frequency spectra, other physiological, and non-physiological data. Three data reduction methods are discussed: the classification with respect to frequency bands, the search for prominent frequencies, and the computation of quartiles of the frequency spectra. There is some evidence in favour of the method of prominent frequencies. This method seems to preserve much of the differential information of the frequency spectra.

[Demonstration of an interpolation method for determining approximate maximum and minimum points as a prerequisite for EEG analysis in the time domain using computers with limited memory capacity]. / Darstellung einer Interpolationsmethode zur Bestimmung von angenäherten Maxima- und Minimapunkten als Voraussetzung von EEG-Analysen im Zeitbereich mittels EDV-Anlagen geringer Speicherkapazität.

The EEG analysis in the time domain provides several advantages compared to the power spectra analysis, based on a FFT. There is the possibility to differentiate frequency, amplitude and other elementary characteristics of the wave form. This technique of EEG analysis is based on the definition of distinct characteristics of the wave form. Problems for calculating the frequency distribution arise--according to Harner, 1977--due to the fact, that the digitalization rate has to be very fast to reach an adequate resolution. On the other hand a high digitalization rate of 5 ms or below produces problems concerning the limited memory capacity of laboratory computers, especially if more than one derivation should be analysed simultaneously, to make further topological analyses possible. Three procedures of EEG analysis to calculate frequency distributions are shown, two of them are based on an interpolation technique to calculate adjusted minima-maxima. The results of these procedures using two different digitalization rates, were compared and discussed to respect similarity of resulting frequency distributions.

[Automatic EEG analysis in the time domain and its possible clinical significance--presentation of a flexible software package]. / Automatische EEG-Analyse in der Time Domain und ihre mögliche klinische Bedeutung--Präsentation eines flexiblen Software-Pakets.

The intention of the automatic EEG analysis is to take several EEG characteristics into account and therefore be usable for different applications to quantify events in the EEG. This procedure of analysis is based on the estimation of maxima and minima points within the measured data and the calculation of the wavelength of the half-waves. This is done by correction of the actually measured maxima-minima-points along the t-axis by means of an interpolation technique, and the frequency of half waves are calculated from this solution with an accuracy of half a Hertz. This method was necessary because our equipment allows only a digitalisation rate of 8 ms (Harner, 1977). Using this procedure it is possible to record the frequency distribution, the distribution of amplitudes, and the distribution of steepness as distributions of elementary EEG characteristics. To characterize specified EEG patterns, the EEG data can be classified according to categories of combinations of quantified characteristics. If we consider topological aspects as well there are the following possibilities: 1 element. characteristic--1 EEG channel; 1 element. characteristic--2 or more EEG channels; several element. characteristics--1 EEG channel; several element. characteristics--2 or more channels. There are possibilities of data reduction, exemplified on the distribution of frequencies without taking into account the topological aspects. The above mentioned methods of data reduction are useful for one EEG channel. On the other hand a comparison of the EEG activity in different channels can be done.