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Biomedical subjects

F Benninger

Publications and source records attributed to F Benninger.

12 recordsLinked to original sources
PubMed2004

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.

Adolescent↗
PubMed2001

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.

Adult↗
PubMed1999

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.

Adolescent↗
PubMed1998

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.

Algorithms↗
PubMed1997

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.

Algorithms↗
PubMed1996

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.

Child↗
PubMed1995

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.

Adolescent↗
PubMed1989

[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].

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).

Child↗
PubMed1986

[Data display and reduction in computer-assisted EEG analysis in the time domain].

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.

Computers↗
PubMed1986

[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].

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.

Computers↗
PubMed1986

[Automatic EEG analysis in the time domain and its possible clinical significance--presentation of a flexible software package].

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.

Brain Diseases↗