Autonomic dysregulation in children with epilepsy with postictal generalized EEG suppression following generalized convulsive seizures

Okanari, Kazuo; Maruyama, Shinsuke; Suzuki, Hiroharu; Shibata, Takashi; Pulcine, Elizabeth; Donner, Elizabeth; Otsubo, Hiroshi

doi:10.1016/j.yebeh.2019.106688

Cited by 14 publications

(16 citation statements)

References 24 publications

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“…In agreement with our own findings, two studies 16,20 showed that PGES was correlated with post‐ictal decrease in parasympathetic activity (HF power 16 and RMSSD 20 ). In contrast, two other series failed to replicate these results, 17,21 while another study found that GTCS with PGES was associated with a smaller decrease in post‐ictal parasympathetic activity (RMSSD) 22 than GTCS without PGES. We also found a significant correlation between PGES and pre‐ictal decrease in parasympathetic activity (HF power) that has not been reported previously.…”

Section: Discussionmentioning

confidence: 97%

Peri‐ictal heart rate variability parameters as surrogate markers of seizure severity

et al. 2020

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This study aims at defining objective parameters reflecting the severity of peri‐ictal autonomic changes and their relation to post‐ictal generalized electroencephalography (EEG) suppression (PGES), with the view that such changes could be detected by wearable seizure detection systems and prove useful to assess the risk of sudden unexpected death in epilepsy (SUDEP). To this purpose, we assessed peri‐ictal changes in heart rate variability (HRV) and correlated them with seizure duration, intensity of electromyography‐based ictal muscle activity, and presence and duration of post‐ictal generalized EEG suppression (PGES). We evaluated 75 motor seizures from 40 patients, including 61 generalized tonic‐clonic seizures (GTCS) and 14 other major motor seizure types. For all major motor seizures, HRV measurements demonstrated a significantly decreased parasympathetic activity and increased sympathetic activity in the post‐ictal period. The post‐ictal increased sympathetic activity was significantly higher for GTCS as compared with non‐GTCS. The degree of peri‐ictal decreased parasympathetic activity and increased sympathetic activity was associated with longer PGES (>20 s), longer seizure duration, and greater intensity of ictal muscle activity. Mean post‐ictal heart rate (HR) was an independent predictor of PGES duration, seizure duration, and intensity of ictal muscle contraction. Our results indicate that peri‐ictal changes in HRV are potential biomarkers of major motor seizure severity.

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Section: Discussionmentioning

confidence: 97%

Peri‐ictal heart rate variability parameters as surrogate markers of seizure severity

et al. 2020

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“…In addition, using the EEG signals from subjects with wide age range one might expect developmental changes in characteristics (e.g., seizure semiology [56] or interictal discharges [57]) that should be evaluated separately in narrower age groups during thorough studies, including the developmental characteristics of the information dynamics measures. On the other hand, comparable group sizes are used in other works on the dynamics of epilepsy, such as in [58] for recurrence quantification analysis, or in [59] for studying heart rate variability as an indicator of autonomic dysregulation. While application on larger benchmarking datasets is a primary focus of future work, the aim of this paper was to present the proposed framework addressing all technical aspects and its evaluation in a simulation setting, while also showing its potential in a clinical application.…”

Section: Discussionmentioning

confidence: 99%

A Framework to Assess the Information Dynamics of Source EEG Activity and Its Application to Epileptic Brain Networks

et al. 2020

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This study introduces a framework for the information-theoretic analysis of brain functional connectivity performed at the level of electroencephalogram (EEG) sources. The framework combines the use of common spatial patterns to select the EEG components which maximize the variance between two experimental conditions, simultaneous implementation of vector autoregressive modeling (VAR) with independent component analysis to describe the joint source dynamics and their projection to the scalp, and computation of information dynamics measures (information storage, information transfer, statistically significant network links) from the source VAR parameters. The proposed framework was tested on simulated EEGs obtained mixing source signals generated under different coupling conditions, showing its ability to retrieve source information dynamics from the scalp signals. Then, it was applied to investigate scalp and source brain connectivity in a group of children manifesting episodes of focal and generalized epilepsy; the analysis was performed on EEG signals lasting 5 s, collected in two consecutive windows preceding and one window following each ictal episode. Our results show that generalized seizures are associated with a significant decrease from pre-ictal to post-ictal periods of the information stored in the signals and of the information transferred among them, reflecting reduced self-predictability and causal connectivity at the level of both scalp and source brain dynamics. On the contrary, in the case of focal seizures the scalp EEG activity was not discriminated across conditions by any information measure, while source analysis revealed a tendency of the measures of information transfer to increase just before seizures and to decrease just after seizures. These results suggest that focal epileptic seizures are associated with a reorganization of the topology of EEG brain networks which is only visible analyzing connectivity among the brain sources. Our findings emphasize the importance of EEG modeling approaches able to deal with the adverse effects of volume conduction on brain connectivity analysis, and their potential relevance to the development of strategies for prediction and clinical treatment of epilepsy.

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“…Interestingly, pediatric epileptic patients have been reported to show a stronger sympathetic activation and a higher vagal suppression following GTCS, compared to adult individuals (Sarkis et al., 2015). In support, in pediatric patients with generalized convulsive seizures, those with generalized electroencephalographic suppression (PGES) after seizures were observed to have a decrease in HRV values as well, but whether this decrease is greater than adults is yet to be determined (Okanari et al., 2020). Since pediatric epileptic patients may potentially have a greater adverse impact from sympathetic and parasympathetic imbalance, this suggests that age may be an important factor on autonomic disorders accompanying epilepsy.…”

Section: Cardiorespiratory Findingsmentioning

confidence: 99%

Cardiorespiratory findings in epilepsy: A recent review on outcomes and pathophysiology

Akyüz

Uner

Köklü

et al. 2021

J of Neuroscience Research

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Epilepsy is a debilitating disorder of uncontrollable recurrent seizures that occurs as a result of imbalances in the brain excitatory and inhibitory neuronal signals, that could stem from a range of functional and structural neuronal impairments. Globally, nearly 70 million people are negatively impacted by epilepsy and its comorbidities. One such comorbidity is the effect epilepsy has on the autonomic nervous system (ANS), which plays a role in the control of blood circulation, respiration and gastrointestinal function. These epilepsy‐induced impairments in the circulatory and respiratory systems may contribute toward sudden unexpected death in epilepsy (SUDEP). Although, various hypotheses have been proposed regarding the role of epilepsy on ANS, the linking pathological mechanism still remains unclear. Channelopathies and seizure‐induced damages in ANS‐control brain structures were some of the causal/pathological candidates of cardiorespiratory comorbidities in epilepsy patients, especially in those who were drug resistant. However, emerging preclinical research suggest that neurotransmitter/receptor dysfunction and synaptic changes in the ANS may also contribute to the epilepsy‐related autonomic disorders. Thus, pathological mechanisms of cardiorespiratory dysfunction should be elucidated by considering the modifications in anatomy and physiology of the autonomic system caused by seizures. In this regard, we present a comprehensive review of the current literature, both clinical and preclinical animal studies, on the cardiorespiratory findings in epilepsy and elucidate the possible pathological mechanisms of these findings, in hopes to prevent SUDEP especially in patients who are drug resistant.

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Autonomic dysregulation in children with epilepsy with postictal generalized EEG suppression following generalized convulsive seizures

Cited by 14 publications

References 24 publications

Peri‐ictal heart rate variability parameters as surrogate markers of seizure severity

Peri‐ictal heart rate variability parameters as surrogate markers of seizure severity

A Framework to Assess the Information Dynamics of Source EEG Activity and Its Application to Epileptic Brain Networks

Cardiorespiratory findings in epilepsy: A recent review on outcomes and pathophysiology

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