Mehmood Asif, Ilyas Ayesha, Ilyas Hajira
Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan.
Faculty of Medicine, Jalal Abad State University, Jalal Abad, Kyrgyzstan.
Neuroinformatics. 2025 Feb 1;23(2):18. doi: 10.1007/s12021-025-09717-6.
The bidirectional interactions between brain and heart through autonomic nervous system is the prime focus of neuro-cardiology community. The computer models designed to analyze brain and heart signals are either complex in terms of molecular and cellular interactions or not capable of representing the complex ion channel dynamics. Therefore, scientists are unable to extract the overall behavior of organs by electrical response of heterogeneous cells of brain and heart. In this study, a unified model of excitable cells is proposed that can be modulated by adrenergic features. By implementing the proposed model, a network of one thousand sparsely coupled cardio-neural network is simulated. The major findings of study include i. cardiac heterogeneity in electrical behavior of cardiac myocytes is the prime factor of heart rate variability ii. Brain-heart interplay through electrical pulses holds the necessary information of brain and heart signals that can be analyzed through spiking neural networks iii. Heart rate variability can be predicted and monitored by spiking neural networks from electrophysiological recordings of brain and heart iv. Heart rate variability related to tachycardia and bradycardia depends upon the polarization protocols of cardiac myocytes during plateau phase of action potential. This study provides the modeling and simulation phase of brain-heart interface to predict the morbidity at early stages. The recent advancements in nano-electronics will make is possible to develop brain-heart interface as nano-chip to deploy in subject to stimulate the brain-heart interplay through electrophysiological signals.
大脑与心脏通过自主神经系统的双向相互作用是神经心脏病学界的主要研究重点。旨在分析大脑和心脏信号的计算机模型，要么在分子和细胞相互作用方面很复杂，要么无法呈现复杂的离子通道动力学。因此，科学家们无法通过大脑和心脏异质细胞的电反应来提取器官的整体行为。在本研究中，提出了一种可由肾上腺素能特征调节的可兴奋细胞统一模型。通过实施所提出的模型，模拟了一个由一千个稀疏耦合的心神经网络组成的网络。该研究的主要发现包括：i. 心肌细胞电行为中的心脏异质性是心率变异性的主要因素；ii. 通过电脉冲的脑心相互作用包含可通过尖峰神经网络分析的大脑和心脏信号的必要信息；iii. 心率变异性可通过尖峰神经网络根据大脑和心脏的电生理记录进行预测和监测；iv. 与心动过速和心动过缓相关的心率变异性取决于动作电位平台期心肌细胞的极化协议。本研究提供了脑心界面的建模和模拟阶段，以在早期阶段预测发病率。纳米电子学的最新进展将使开发脑心界面纳米芯片成为可能，该芯片可植入受试者体内，通过电生理信号刺激脑心相互作用。
