Franz Benninger

Time-Variant, Frequency-Selective, Linear and Nonlinear Analysis of Heart Rate Variability in Children With Temporal Lobe Epilepsy

The major aim of our study is to demonstrate that a concerted combination of time-variant, frequency-selective, linear and nonlinear analysis approaches can be beneficially used for the analysis of heart rate variability (HRV) in epileptic patients to reveal premonitory information regarding an imminent seizure and to provide more information on the mechanisms leading to changes of the autonomic nervous system. The quest is to demonstrate that the combined approach gains new insights into specific short-term patterns in HRV during preictal, ictal, and postictal periods in epileptic children. The continuous Morlet-wavelet transform was used to explore the time-frequency characteristics of the HRV using spectrogram, phase-locking, band-power and quadratic phase coupling analyses. These results are completed by time-variant characteristics derived from a signal-adaptive approach. Advanced empirical mode decomposition was utilized to separate out certain HRV components, in particular blood-pressure-related Mayer waves (≈0.1 Hz) and respiratory sinus arrhythmia (≈0.3 Hz). Their time-variant nonlinear predictability was analyzed using local estimations of the largest Lyapunov exponent (point prediction error). Approximately 80-100 s before the seizure onset timing and coordination of both HRV components can be observed. A higher degree of synchronization is found and with it a higher predictability of the HRV. All investigated linear and nonlinear analyses contribute with a specific importance to these results.

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.

The ketogenic diet in infants – Advantages of early use

OBJECTIVE To evaluate the efficacy and safety of the ketogenic diet (KD) in infants (< 1.5 years of age) compared with older children. METHODS Patients with complete follow-up data of ≥ 3 months after initiation of the KD were analyzed retrospectively. Infants < 1.5 years at initiation of the KD (Group A) were compared with children > 1.5 years (Group B). RESULTS 127 children were screened, 115 (Group A: 58/Group B: 57) were included. There were no significant differences between groups with respect to responder rates (63.8% vs. 57.9% at 3 months), but more infants became seizure free (34.5% vs. 19% at 3 months; 32.7% vs. 17.5% at 6 and 12 months). This result remained stable also after termination of the KD (30.6% vs. 3.9% at last follow-up) (p = 0.000). Looking at infants < 9 months of age separately (n = 42), this result was even stronger with significantly more infants being seizure free at 6 and at 12 months (p = 0.005, p = 0.014, respectively). In addition, a significantly higher number of infants remained seizure free in the long-term (p = 0.001). No group differences between infants and children with respect to safety were observed. Overall 52/115 patients (45.21%) reported side effects, but withdrawal of the KD was only necessary in one infant. Acceptance of the KD was better in infants compared with children at 3 months (0 vs. 14, p = 0.000), but became difficult when solid food was introduced (16 vs. 14; n.s.). SIGNIFICANCE According to our results, the KD is highly effective and well tolerated in infants with epilepsy. Seizure freedom is more often achieved and maintained in infants. Acceptance of the diet is better before the introduction of solid food. Therefore, we recommend the early use of the KD during the course of epilepsy.

Nonlinear Directed Interactions Between HRV and EEG Activity in Children With TLE

Objective: Epileptic seizure activity influences the autonomic nervous system (ANS) in different ways. Heart rate variability (HRV) is used as indicator for alterations of the ANS. It was shown that linear, nondirected interactions between HRV and EEG activity before, during, and after epileptic seizure occur. Accordingly, investigations of directed nonlinear interactions are logical steps to provide, e.g., deeper insight into the development of seizure onsets. Methods: Convergent cross mapping (CCM) investigates nonlinear, directed interactions between time series by using nonlinear state space reconstruction. CCM is applied to simulated and clinically relevant data, i.e., interactions between HRV and specific EEG components of children with temporal lobe epilepsy (TLE). In addition, time-variant multivariate Autoregressive model (AR)-based estimation of partial directed coherence (PDC) was performed for the same data. Results: Influence of estimation parameters and time-varying behavior of CCM estimation could be demonstrated by means of simulated data. AR-based estimation of PDC failed for the investigation of our clinical data. Time-varying interval-based application of CCM on these data revealed directed interactions between HRV and delta-related EEG activity. Interactions between HRV and alpha-related EEG activity were visible but less pronounced. EEG components mainly drive HRV. The interaction pattern and directionality clearly changed with onset of seizure. Statistical relevant interactions were quantified by bootstrapping and surrogate data approach. Conclusion and Significance: In contrast to AR-based estimation of PDC CCM was able to reveal time-courses and frequency-selective views of nonlinear interactions for the further understanding of complex interactions between the epileptic network and the ANS in children with TLE.

Synchronization analysis between heart rate variability and EEG activity before, during, and after epileptic seizure

Abstract An innovative concept for synchronization analysis between heart rate (HR) components and rhythms in EEG envelopes is represented; it applies time-variant analyses to heart rate variability (HRV) and EEG, and it was tested in children with temporal lobe epilepsy (TLE). After a removal of ocular and movement-related artifacts, EEG band activity was computed by means of the frequency-selective Hilbert transform providing envelopes of frequency bands. Synchronization between HRV and EEG envelopes was quantified by Morlet wavelet coherence. A surrogate data approach was adapted to test for statistical significance of time-variant coherences. Using this processing scheme, significant coherence values between a HRV low-frequency sub-band (0.08–0.12 Hz) and the EEG δ envelope (1.5–4 Hz) occurring both in the preictal and early postictal periods of a seizure can be shown. Investigations were performed for all electrodes at 20-s intervals and for selected electrode pairs (T3÷C3, T4÷C4) in a time-variant mode. Synchronization was more pronounced in the group of right hemispheric TLE patients than in the left hemispheric group. Such a group-specific augmentation of synchronization confirms the hypothesis of a right hemispheric lateralization of sympathetic cardiac control of the low-frequency HRV components.

Matching Pursuit-Based Time-Variant Bispectral Analysis and its Application to Biomedical Signals

Objective: Principle aim of this study is to investigate the performance of a matching pursuit (MP)-based bispectral analysis in the detection and quantification of quadratic phase couplings (QPC) in biomedical signals. Nonlinear approaches such as time-variant bispectral analysis are able to provide information about phase relations between oscillatory signal components. Methods: Time-variant QPC analysis is commonly performed using Gabor transform (GT) or Morlet wavelet transform (MWT), and is affected by either constant or frequency-dependent time-frequency resolution (TFR). The matched Gabor transform (MGT), which emerges from the incorporation of GT into MP, can overcome this obstacle by providing a complex time-frequency plane with an individually tailored TFR for each transient oscillatory component. QPC analysis was performed by MGT, and MWT was used as the state-of-the-art method for comparison. Results: Results were demonstrated using simulated data, which present the general case of QPC, and biomedical benchmark data with a priori knowledge about specific signal components. HRV of children during temporal lobe epilepsy and EEG during burst-interburst pattern of neonates during quiet sleep were used for the biomedical signal analysis to investigate the two main areas of biomedical signal analysis: The cardiovascular-cardiorespiratory system and neurophysiological brain activities, respectively. Simulations were able to show the applicability and reliability of the MGT for bispectral analysis. HRV and EEG analysis demonstrate the general validity of the MGT for QPC detection by quantifying statistically significant time patterns of QPC. Conclusion and Significance: Results confirm that MGT-based bispectral analysis provides significant benefits for the analysis of QPC in biomedical signals.

Advantages of signal-adaptive approaches for the nonlinear, time-variant analysis of heart rate variability of children with temporal lobe epilepsy.

Major aim of our study is to demonstrate that signal-adaptive approaches improve the nonlinear and time-variant analysis of heart rate variability (HRV) of children with temporal lobe epilepsy (TLE). Nonlinear HRV analyses are frequently applied in epileptic patients. As HRV is characterized by components with oscillatory properties frequency-selective methods are in the focus, whereby application of nonlinear analysis to linear filtered signals seems to be doubtful. Signal-adaptive methods that preserve nonlinear properties and utilize only the signal data for an automatic computation of the result could benefit to nonlinear analysis of HRV. Combinations of (1) the signal-adaptive Matched Gabor Transform with time-variant nonlinear bispectral analysis and of (2) signal-adaptive Empirical Mode Decomposition methods with time-variant nonlinear stability analysis are investigated with regard to their application in the analysis of specific HRV components (respiratory sinus arrhythmia and Mayer wave associated low-frequency HRV components) of 18 children with TLE. Changes of timing and coordination of both HRV components during preictal, ictal and postictal periods occur which can be better quantified by advanced signal-adaptive methods. Both approaches contribute with specific importance to the analysis.

Correlates of electroencephalographic resting states and erythrocyte membrane docosahexaenoic and eicosapentaenoic acid levels in individuals at ultra-high risk of psychosis

Objective: Abnormal levels of polyunsaturated fatty acids (PUFAs) have been reported in individuals suffering from schizophrenia. The main aim of the present study was to investigate the relationship between erythrocyte membrane fatty acid levels and resting-state brain activity occurring in individuals at ultra-high risk (UHR) of psychosis. Method: The association between erythrocyte membrane fatty acids levels and resting-state brain activity and its value in predicting psychosis was examined in 72 UHR individuals. Results: In the frontal area, the activity in the fast frequency band Beta2 was positively associated with docosahexaenoic acid (DHA) levels (R = 0.321, P = 0.017), and in the fronto-central area, Beta2 activity showed a positive correlation with eicosapentaenoic acid (EPA) levels (R = 0.305, P = 0.009), regardless of psychosis transition status. Conversely, the slow frequency band Theta was significantly negatively associated with EPA levels in the parieto-occipital region (R = −0.251, P = 0.033. Results also showed that Alpha power was negatively correlated with DHA levels in UHR individuals who did not transition to psychosis, while this correlation was not present in individuals who later transitioned. Conclusion: Our results suggest that individuals at UHR for psychosis who have higher basal omega-3 fatty acids levels present with resting EEG features associated with better states of alertness and vigilance. Furthermore, the improvement in the Alpha synchrony observed along with increased DHA levels in participants who did not transition to psychosis is disturbed in those who did transition. However, these interesting results are limited by the small sample size and low statistical power of the study.

Ketogenic parenteral nutrition in 17 pediatric patients with epilepsy

Ketogenic parenteral nutrition (kPN) is indicated when enteral intake is temporarily limited or impossible, but evidence‐based prescriptions are lacking. Objective was to evaluate the efficacy and safety of kPN in children with epileptic encephalopathies using a new computer‐based algorithm for accurate component calculating.

Tensor decomposition of time-variant coherence between heart rate variability and EEG envelopes in children with epilepsy

Time-variant coherence between the heart rate variability and the channel-related envelopes of the EEG delta activity was used as an indicator for interactions between the autonomic nervous system and cortical processes before, during and after epileptic seizures. The tensor decomposition was applied to explore the topography-time-frequency characteristics of these correlative interactions for each patient and for two sub-groups (left and right hemispheric seizure). It can be demonstrated that tensor decomposition strongly supports the interaction analysis and its interpretation.