Simulation framework for electrophysiological networks: effect of syncytial properties on smooth-muscle synaptic potentials

Abstract

A building block-based software framework was developed to simulate electrophysiological networks. The synaptic potentials generated during neurotransmission were simulated in an existing discrete bidomain model of smooth muscle, using cubic, three-dimensional grids of varying sizes. The model is automatically derived and numerically solved, and the results of the simulation agree with previous results obtained analytically. An enhanced model was also proposed, incorporating an additional (junctional) capacitance in the network. The correctness of the model was verified, and the effect of the extra capacitance on the synaptic potentials was explored. It was found that, with a junctional capacitance C-i of 1.4 x 10(-10) F incorporated, the peak amplitude of the spontaneous excitatory junction potential V-peak declined by similar to13% at node 0 and by similar to37% at node 3x for a system size of 9(3). Similar results were obtained for different system sizes. V-peak also declined as the junctional capacitance C-i was increased. In a system of size 11(3), a 200-fold increase in C-i induced a 55% reduction at node 0. It is suggested that the type of modular simulation framework developed here may find general applicability for simulations of other physiological systems.