<p>The functional interactions between the brain and heart through analysis of electrical activity provide effective bio-markers for cognition, emotions, and morbidity. Conventional computational models designed for the brain and heart can be modified to understand the bidirectional interactions as the brain–heart interface for further clarification and treatment of morbidity. The electrical response of brain and heart is initiated by pulses associated with excitable cells. In this work, a unified computational model of excitable cells (neuron and cardiac myocyte) is proposed and simulated with adrenergic features. The electrical activity of the cardiac network is coupled to the spiking neural network, and the corresponding response of the neural network is recorded. The major findings of the study include i. Cardiac action potential heterogeneity is a significant factor in heart rate variability. ii. Spiking neural networks can accurately predict heart rate variability in real time from electrophysiological data of the cardiac network. iii. The electrical activity of the heart can be monitored and controlled by processing electrophysiological data of cardiac myocytes with spiking neural networks coupled with ion channels as voltage regulators to reduce the risk of cardiac morbidity and mortality. This work provides the initial phase of the brain–heart interface as a tool for the diagnosis of cardiac morbidity in real time. The recent advancements in nano- and bioelectronics will make it possible to deploy a brain–heart interface as a nano-chip to monitor and control the electrophysiological abnormality of the brain and heart by integrating nano-regulators with ion channels for stimulation.</p>