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

Piper, Diana; Schiecke, Karin; Leistritz, Lutz; Pester, Britta; Benninger, Franz; Feucht, Martha; Ungureanu, Mihaela; Strungaru, Rodica; Witte, Herbert

doi:10.1515/bmt-2013-0139

Cited by 16 publications

(14 citation statements)

References 41 publications

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“…The analysis concept presented in figure 1 is based on and considerably advances our previous work [20]. In that study tvCOH between EEG envelopes of fixed frequency band components and the HRV was computed.…”

Section: Methodsmentioning

confidence: 99%

“…In a previous study [20] we demonstrated that statistically significant coherence values between the HRV's low-frequency (HRV-LF) oscillation at about 0.1 Hz and the envelope of EEG delta-activity before and after the TLE seizure occur. Significant coherence values testify significant correlative coupling (synchronization) between two oscillatory signals of the same frequency.…”

mentioning

confidence: 94%

“…For the computation of the coherence, the IMF envelopes were down sampled to 8 Hz to match the sampling frequency of the HRV; the time-variant spectra of the envelopes and HRV were obtained with the continuous Morlet wavelet transform (CMWT) (frequency range 0-0.5 Hz) and a time smoothing of the timevariant cross-spectrum and the two time-variant spectra was performed using a 512 points window. Details of the Hilbert transform and the computation of tvCOH can be found in [20] and in the appendix section.…”

Section: Multivariate Empirical Mode Decomposition Memd Was Introducmentioning

confidence: 99%

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Time-variant coherence between heart rate variability and EEG activity in epileptic patients: an advanced coupling analysis between physiological networks

et al. 2014

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Time-variant coherence analysis between the heart rate variability (HRV) and the channel-related envelopes of adaptively selected EEG components was used as an indicator for the occurrence of (correlative) couplings between the central autonomic network (CAN) and the epileptic network before, during and after epileptic seizures. Two groups of patients were investigated, a group with left and a group with right hemispheric temporal lobe epilepsy. The individual EEG components were extracted by a signal-adaptive approach, the multivariate empirical mode decomposition, and the envelopes of each resulting intrinsic mode function (IMF) were computed by using Hilbert transform. Two IMFs, whose envelopes were strongly correlated with the HRV's low-frequency oscillation (HRV-LF; ≈0.1 Hz) before and after the seizure were identified. The frequency ranges of these IMFs correspond to the EEG delta-band. The timevariant coherence was statistically quantified and tensor decomposition of the time-frequency coherence maps was applied to explore the topography-timefrequency characteristics of the coherence analysis. Results allow the hypothesis 4 Both authors contributed equally to the publication, and are considered as first author. that couplings between the CAN, which controls the cardiovascularcardiorespiratory system, and the 'epileptic neural network' exist. Additionally, our results confirm the hypothesis of a right hemispheric lateralization of sympathetic cardiac control of the HRV-LF.Epileptic seizure activity can cause alterations of the autonomic nervous system (ANS) in different ways and heart rate variability (HRV) is most frequently used to investigate both longterm and short-term alterations of the ANS in response to the type of epilepsy and to the evolution of the epileptic seizure [1,2]. HRV is an indicator for neuronal influences on the cardiac pacemaker and is one of the important functions of the ANS. Therefore, seizure-related HRV reactions may provide more information on the organization of the ANS [3] and the mechanisms supporting ANS changes.The main divisions of the ANS are the parasympathetic and the sympathetic nervous systems, which typically function in opposition to each other. The coordination of 'autonomic functions and the ongoing behavioral needs of the organism through the activities of the somatomotor, endocrine and autonomic systems ' [4] can be attributed to a central autonomic network (CAN) [5], which involves several interconnected areas distributed throughout brainstem and forebrain. According to the ANS's structure some of these CAN areas regulate parasympathetic output whereas others regulate sympathetic output, e.g. in order to control visceral function and homeostasis as well as to adapt to internal or external challenges [6].From the point of view of network physiology [7], the temporal lobe epilepsy (TLE)related 'epileptic network' and the CAN can be considered as coupled networks. Taking this into account, couplings between EEG and HRV signals before, during and after an epilepti...

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 94%

Section: Multivariate Empirical Mode Decomposition Memd Was Introducmentioning

confidence: 99%

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Time-variant coherence between heart rate variability and EEG activity in epileptic patients: an advanced coupling analysis between physiological networks

et al. 2014

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“…The data were described in [1]. 20 EEG channels were used for analysis and the HRV was computed by means of the French-Holden algorithm.…”

Section: Methodsmentioning

confidence: 99%

“…Accordingly, changes of the heart rate (HR) and HR variability (HRV) are measures used most frequently to investigate the long-term and short-term alterations of the ANS in response to the type of epilepsy and to the evolution of the epileptic seizure. We have recently shown that significant synchronization between a HRV low-frequency sub-band (0.08 -0.12 Hz) and the EEG delta-envelope (1.5 -4 Hz) can be observed both in the preictal and early postictal periods of a seizure [1]. In this study the results of the time-variant coherence analysis are used in order to analyze them by means of tensor decomposition.…”

Section: Introductionmentioning

confidence: 99%

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

Piper

Pester

Schiecke

et al. 2014

2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)

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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.

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Predicting Epileptic Seizures—An Update

Lehnertz

2021

Understanding Complex Systems

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

Cited by 16 publications

References 41 publications

Time-variant coherence between heart rate variability and EEG activity in epileptic patients: an advanced coupling analysis between physiological networks

Time-variant coherence between heart rate variability and EEG activity in epileptic patients: an advanced coupling analysis between physiological networks

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

Predicting Epileptic Seizures—An Update

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