Syncytial basis for diversity in spike shapes and their propagation in detrusor smooth muscle

AbstractSyncytial tissues, such as the smooth muscle of the urinary bladder wall, are known to produce action potentials (spikes) with marked differences in their shapes and sizes. The need for this diversity is currently unknown, and neither is their origin understood. The small size of the cells, their syncytial arrangement, and the complex nature of innervation poses significant challenges for the experimental investigation of such tissues. To obtain better insight, we present here a three-dimensional electrical model of smooth muscle syncytium, developed using the compartmental modeling technique, with each cell possessing active channel mechanisms capable of producing an action potential. This enables investigation of the syncytial effect on action potential shapes and their propagation. We show how a single spike shape could undergo modulation, resulting in diverse shapes, owing to the syncytial nature of the tissue. Differences in the action potential features could impact their capacity to propagate through a syncytium. This is illustrated through comparison of two distinct action potential mechanisms. A better understanding of the origin of the various spike shapes would have significant implications in pathology, assisting in evaluating the underlying cause and directing their treatment

Modeling extracellular fields for a three-dimensional network of cells using NEURON

Background: Computational modeling of biological cells usually ignores their extracellular fields, assuming them to be inconsequential. Though such an assumption might be justified in certain cases, it is debatable for networks of tightly packed cells, such as in the central nervous system and the syncytial tissues of cardiac and smooth muscle. New method: In the present work, we demonstrate a technique to couple the extracellular fields of individual cells within the NEURON simulation environment. The existing features of the simulator are extended by explicitly defining current balance equations, resulting in the coupling of the extracellular fields of adjacent cells. Results: With this technique, we achieved continuity of extracellular space for a network model, thereby allowing the exploration of extracellular interactions computationally. Using a three-dimensional network model, passive and active electrical properties were evaluated under varying levels of extracellular volumes. Simultaneous intracellular and extracellular recordings for synaptic and action potentials were analyzed, and the potential of ephaptic transmission towards functional coupling of cells was explored. Comparison with existing method(s): We have implemented a true bi-domain representation of a network of cells, with the extracellular domain being continuous throughout the entire model. This has hitherto not been achieved using NEURON, or other compartmental modeling platforms. Conclusions: We have demonstrated the coupling of the extracellular field of every cell in a threedimensional model to obtain a continuous uniform extracellulat" space. This technique provides a framework for the investigation of interactions in tightly packed networks of cells via their extracellular fields. (C) 2017 Elsevier B.V. All rights reserved

Effect of variations in gap junctional coupling on the frequency of oscillatory action potentials in a smooth muscle syncytium

Gap junctions provide pathways for intercellular communication between adjacent cells, allowing exchange of ions and small molecules. Based on the constituent protein subunits, gap junctions are classified into different subtypes varying in their properties such as unitary conductances, sensitivity to transjunctional voltage, and gating kinetics. Gap junctions couple cells electrically, and therefore the electrical activity originating in one cell can affect and modulate the electrical activity in adjacent cells. Action potentials can propagate through networks of such electrically coupled cells, and this spread is influenced by the nature of gap junctional coupling. Our study aims to computationally explore the effect of differences in gap junctional properties on oscillating action potentials in electrically coupled tissues. Further, we also explore variations in the biophysical environment by altering the size of the syncytium, the location of the pacemaking cell, as well as the occurrence of multiple pacemaking cells within the same syncytium. Our simulation results suggest that the frequency of oscillations is governed by the extent of coupling between cells and the gating kinetics of different gap junction subtypes. The location of pacemaking cells is found to alter the syncytial behavior, and when multiple oscillators are present, there exists an interplay between the oscillator frequency and their relative location within the syncytium. Such variations in the frequency of oscillations can have important implications for the physiological functioning of syncytial tissues