A Computational Model of the Dendron of the GnRH Neuron

Gonadotropin-releasing hormone (GnRH) neurons have two major processes that have properties of both dendrites (they receive synaptic input from other neurons) and axons (they actively propagate action potentials to the synaptic terminal). These processes have thus been termed dendrons. We construct a stochastic spatiotemporal model of the dendron of the GnRH neuron, with the goal of studying how stochastic synaptic input along the length of the dendron affects the initiation and propagation of action potentials. We show (1) that synaptic inputs closer to the soma are effective controllers of action potential initiation and electrical bursting and (2) that although the effects on the amplitude and width of propagating action potentials are critically dependent on the timing and location of synaptic input addition, the effects remain small. We conclude that although stochastic synaptic input along the length of the dendron is likely to be a major determinant of action potential initiation, it is an unlikely mechanism for controlling whether or not action potentials reach the synaptic terminal. Thus, the role of synaptic inputs situated along the dendron a long way from the site of action potential initiation remains unclear. We also show that the actions of kisspeptin can result in significant modulation of the amount of calcium released by an action potential at the synaptic terminal. Furthermore, we show that the actions of kisspeptin are greatest when multiple effects operate together and that a kisspeptin-induced increase in firing rate is, by itself, less effective at increasing Ca2+ release than is a combination of an increased firing rate, an increase in Ca2+ influx, and an increase in inositol trisphosphate (IP3) production. We conclude that the inherent synergies in the various actions of kisspeptin make it a likely candidate for the precise control of Ca2+ transients at the synaptic terminal.