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<p>The investigation of brain–heart interplay (BHI) has gained significant momentum in recent years, and has emerged as a pivotal area of neurophysiological research. The applications of BHI span cognitive neuroscience, sleep research, and neurological disorders, where the analysis of cortical and autonomic dynamics can provide a mechanistic overview of functional regulation. Epilepsy is known to have an impact on cardiovascular function and autonomic regulation, and the analysis of BHI offers a valuable framework for understanding the dynamics behind autonomic dysfunction in epilepsy. In this work, we use the framework of network physiology (NP) to derive a time-varying time delay stability (TDS) metric to characterize the continuous evolution of the brain–heart network. We further validated the framework on a publicly available dataset of temporal lobe epilepsy (TLE) subjects. The results from the analysis revealed that TDS coupling between brain and heart dynamics changed significantly following an epileptic episode, suggesting instability in the brain–heart network that may reflect altered autonomic and cortical communication in that period. The methodology presented in this work may serve as an informative framework to characterize cortical and autonomic interplay, and could be further explored in the study of disorders characterized by cortical and autonomic dysregulation.</p>

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A continuous network physiology analysis of brain–heart interactions in epileptic seizures

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月10日

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  • Matteo Saibene,
  • Martin Ballegaard,
  • Ying Gu,
  • Tobias S. Andersen,
  • Jakob E. Bardram,
  • Sadasivan Puthusserypady

摘要

The investigation of brain–heart interplay (BHI) has gained significant momentum in recent years, and has emerged as a pivotal area of neurophysiological research. The applications of BHI span cognitive neuroscience, sleep research, and neurological disorders, where the analysis of cortical and autonomic dynamics can provide a mechanistic overview of functional regulation. Epilepsy is known to have an impact on cardiovascular function and autonomic regulation, and the analysis of BHI offers a valuable framework for understanding the dynamics behind autonomic dysfunction in epilepsy. In this work, we use the framework of network physiology (NP) to derive a time-varying time delay stability (TDS) metric to characterize the continuous evolution of the brain–heart network. We further validated the framework on a publicly available dataset of temporal lobe epilepsy (TLE) subjects. The results from the analysis revealed that TDS coupling between brain and heart dynamics changed significantly following an epileptic episode, suggesting instability in the brain–heart network that may reflect altered autonomic and cortical communication in that period. The methodology presented in this work may serve as an informative framework to characterize cortical and autonomic interplay, and could be further explored in the study of disorders characterized by cortical and autonomic dysregulation.