Achieving Synchronization in Cardiac Oscillators with Suitable Neural InputAuthor : T S Murugesh
Volume 5 No.1 January-June 2016 pp 43-53
The normal cardiac rhythm is the result of collective, synchronized action of a large number of cardiac oscillators which play a crucial role in the determination of the sinus rhythm. The physiological function of the cardiovascular system is under the control of the autonomic nervous system (ANS). The two limbs of the ANS, sympathetic and parasympathetic, are critical in determining the oscillations within the heart. The pumping effectiveness of the heart is controlled by the sympathetic and parasympathetic nerves, which abundantly supply the heart that act in opposing ways. However, the two divisions act together to regulate the activity of the internal organs as per the needs of the body at any particular time. The cardiac centers in the central nervous system exert an influence on the heart’s activity through sympathetic and parasympathetic nerves. This influence governs the rate of beat, the systolic contractile force and the velocity of atrioventricular conduction. The parasympathetic stimulation causes a decrease in heart rate whereas sympathetic stimulation increases it. The intrinsic cardiac nervous system is seen to play an active role in regulating cardiac function which consists of sympathetic and parasympathetic neurons and interconnecting local circuits. An appropriate mathematical model that describes the electrical activity and ion exchange in the sinoatrial node (SAN) is considered and the dynamical equations describing the behaviour of the chosen model are solved with the corresponding source code developed and implemented using Matlab.An Integrate and Fire Neuron (IFN) model is developed that mimics the role of ANS which acts as an external influence to the preferred SAN cell to in order to coax synchronization between the coupled cell pair. The influence of the suitable neuron model in effecting synchrony between the coupled SAN cell pair is demonstrated with the aid of simulation studies.
Cardiac rhythm, autonomic nervous system, Integrate and Fire Neuron, Synchronization, sinoatrial node
 Brading A (1999), The autonomic nervous system and its effectors. Malden, MA: Blackwell Science.
 Malpas S C (1998), The rhythmicity of sympathetic nerve activity. Progress in neurobiology Vol.56, No.1: 65-96.  Morrison S F (2001), Differential control of sympathetic outflow. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology Vol.281, No.3: R683-R698.  Critchley H D (2005), Neural Mechanisms of Autonomic, Affective, and Cognitive Integration. Journal of Comparative Neurology Vol.493, No.1: 154-166.
 Guyton A C and Hall J E (2007), Textbook of Medical Physiology. Eleventh Edition, Elsevier.
 Malpas S C (2010), Sympathetic nervous system over activity and its role in the development of cardiovascular disease. Physiological Reviews Vol.90, No.2: 513-557.  Armour J A, Murphy D A, Yuan B X, Macdonald S and Hopkins D A (1997), Gross and Microscopic Anatomy of the Human Intrinsic Cardiac Nervous System. The Anatomical Record Vol.247, No.2: 289-298.
 Randall D C, Brown D R, McGuirt A S, Thompson G W, Armour J A and Ardell J L (2003), Interactions within the intrinsic cardiac nervous system contribute to chronotropic regulation. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology Vol.285, No.5: R1066-R1075.
 Strogatz S H (1994), Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering (Studies in Nonlinearity). Addison Wesley.
 Murugesh T S, Krishnan J and Malathi R (2013), Investigations on the intrinsic frequency of the cardiac cells in effecting synchronization.International Journal of Current Research Vol.5, Issue 10, pp. 3140-3148.  Demir S S, Clark J W, Murphey C R and Giles W R (1994), A mathematical model of a rabbit sinoatrial node cell; Modeling in Physiology. American Journal of Physiology-Cell Physiology Vol.266, No.3: C832-C852.  Pikovsky A, Rosenblum R and Kurths J (2001), Synchronization: A Universal Concept in Nonlinear Sciences. Cambridge University Press.  T S Murugesh, Assessment of Gap Junctional Conductance Magnitude in Cardiac Synchronization – A Computational Study (2015), Journal of Emerging Technologies and Innovative Research Vol.2, Issue 12, pp 258-266.