Mathematical modelling of the oxytocin and vasopressin secretory system

Abstract

Magnocellular oxytocin and vasopressin neurons of the hypothalamus project to the posterior pituitary where they secrete their peptide hormone signals directly into the bloodstream. Their large anatomically distinct secretory mechanisms provide a uniquely accessible system in which to unite experimental and modelling approaches in the investigation of how input signals and electrophysiological properties of neurons relate to physiological function. We describe how the mechanisms have been translated and assembled into a mathematical model representation that can explain and simulate the complex and highly non-linear stimulus-secretion coupling of these neurons, and how this model has been applied to further understand these systems.

Keywords: Modelling; Oxytocin; Secretion; System; Vasopressin.

Figure 1

Frequency facilitation and fatigue in the stimulus-secretion coupling. Frequency dependence was investigated in vitro [7] by stimulating posterior pituitary glands with 156 pulses at four different frequencies and measuring the hormone secretion by radioimmunoassay. Facilitation peaks at 13Hz for vasopressin but continues to rise for oxytocin. Fatigue was measured [6] by stimulating at 13Hz for four different durations. Vasopressin shows a fall in secretion rate, while oxytocin shows no fatigue on this timescale.

Figure 2

Coupled spiking, secretion, and plasma diffusion model. The secretion model [15], taking model generated spike events as an input, matches the secretion properties by combining representations of the vesicle pools and the competing excitatory and inhibitory Ca²⁺ dynamics at the secretory terminals. A few parameter changes, mainly reducing the Ca²⁺ dependent negative feedbacks, are sufficient to adapt between vasopressin and oxytocin secretion properties. The plasma diffusion model [17] accurately translates the secretion rate into plasma concentration, giving a strong quantitative match to experimental data.