Date Published: July 10, 2017
Publisher: Public Library of Science
Author(s): Guy Kember, Jeffrey L. Ardell, Kalyanam Shivkumar, J. Andrew Armour, Gennady Cymbalyuk.
The cardiac nervous system continuously controls cardiac function whether or not pathology is present. While myocardial infarction typically has a major and catastrophic impact, population studies have shown that longer-term risk for recurrent myocardial infarction and the related potential for sudden cardiac death depends mainly upon standard atherosclerotic variables and autonomic nervous system maladaptations. Investigative neurocardiology has demonstrated that autonomic control of cardiac function includes local circuit neurons for networked control within the peripheral nervous system. The structural and adaptive characteristics of such networked interactions define the dynamics and a new normal for cardiac control that results in the aftermath of recurrent myocardial infarction and/or unstable angina that may or may not precipitate autonomic derangement. These features are explored here via a mathematical model of cardiac regulation. A main observation is that the control environment during pathology is an extrapolation to a setting outside prior experience. Although global bounds guarantee stability, the resulting closed-loop dynamics exhibited while the network adapts during pathology are aptly described as ‘free-floating’ in order to emphasize their dependence upon details of the network structure. The totality of the results provide a mechanistic reasoning that validates the clinical practice of reducing sympathetic efferent neuronal tone while aggressively targeting autonomic derangement in the treatment of ischemic heart disease.
From an autonomic perspective, unstable angina and recurrent myocardial infarction (MI) overlap in a mechanistic sense and, as such, preventing their pathological adaptation during the progression of heart disease would relieve a significant health burden . While population studies do not typically address the autonomic nervous system in a direct fashion, it is understood that the autonomic nervous system plays a role in the production of ventricular arrhythmias and sudden cardiac death ( and ).
The focus of this study has been on the adaptive response to unstable angina vs. recurrent MI of a networked model for autonomic cardiac regulation. While the network evolution is subject to global constraints, the network adaptations take place in a pathological setting that is outside prior experience. As such, the pathways followed by the system are described here as ‘free-floating’ implying that collective neuronal activities depend upon past events and changes in the network balance reflect experience accumulated from each myocardial ischemic episode. Details of the networked structure, the degree of neural diversity etc., all play a role in determining the system dynamics during pathology and the form of the network that emerges in the aftermath of pathology. The complexity of the dependence of neural network evolution upon network structure, neural diversity, and neural adaptability studied here for cardiac control is a current topic of wider interest within neuroscience involving questions of complexity and mechanisms for compensation in neural networks (e.g. [20–22] and ).