New determinants of firing rates and patterns of vasopressinergic magnocellular neurons: predictions using a mathematical model of osmodetection

Abstract

Arginine vasopressin (AVP), one of the most important hormones involved in hydromineral homeostasis, is secreted by hypothalamic magnocellular neurons (MCNs). Here, we implemented two critical parameters for MCN physiology into a Hodgkin-Huxley simulation of the MCN. By incorporating the mechanosensitive channel (MSC) responsible for osmodetection and the synaptic inputs whose frequencies are modulated by changes in ambient osmolality into our model, we were able to develop an improved model with increased physiological relevance and gain new insight into the determinants of the firing patterns of AVP magnocellular neurons. Our results with this MCN model predict that 1) a single MCN is able to display all the firing patterns experimentally observed: silent, irregular, phasic and continuous firing patterns; 2) under conditions of hyperosmolality, burst durations are regulated by the frequency-dependent fatigue of dynorphin secretion; and 3) the transitions between firing patterns are controlled by EPSP and IPSP frequencies (0, 2, 4, 8, 16, 32, 64 and 128 Hz). Moreover, this simulation predicts that EPSPs and IPSPs do not modify the spiking frequency (SF) of phasic firing patterns (0.0034 Hz/Hz [EPSP]; 0.0012 Hz/Hz [IPSP]). Rather, these afferents strongly regulate SF during irregular and continuous firing patterns (0.075 Hz/Hz [EPSP]; 0.027 Hz/Hz [IPSP]). The use of the realistic MCN model developed here allows for an improved understanding of the determinants driving the firing patterns and spiking frequencies of vasopressinergic magnocellular neurons.