A Computational Model of Transduction Cells in the Vestibular System

The human brain, and even the brains of the lowest vertebrates, are diabolically complex, and complete understanding of these systems would take hundreds of careers to build. One key way of dealing with this complexity is to look back in time, and study the evolution of neurons and brains. This allows researchers to investigate the selection pressures driving the evolution of the brain, and how these influenced its development. Another method is to study simple parts of the brain, figure out how they work, and see if this can be generalised to other brain regions. The vestibular system, responsible for detection of head acceleration, is of particular interest due to its early evolution, and the simplicity of its role of dynamical inference. Constructing computational models of cells involved in vestibular transduction provides a framework which can be used by researchers to test and extend understanding of how the system works. This thesis describes work building a computational model of the transduction cells of the vestibular system, known as hair cells, and extension of the model to include the firing of vestibular afferent neurons. All modelling was carried out using the Julia programming language. The model of a vestibular hair cell built somewhat replicated the behaviour of biological hair cells, however, further refinement or experimentation is necessary to accurately reproduce the characteristics of any single hair cell. A concerning discovery was that the range of parameter values reported for hair cells in the literature, using state of the art modelling frameworks, was unable to replicate thirty two percent of the observed range of resting membrane potentials of these cells. The extension of the model used scaled calcium concentration of a resting hair cell, which fluctuates due to Brownian motion of the transduction apparatus, as input for a leaky integrate-and-fire neuron. It was found that this input could be scaled to reproduce the diverse statistical distributions of resting discharge observed in vestibular afferent neurons. Together, my studies provide improved documentation and reporting of vestibular hair cell models, directions for future research, and an interesting first model including both vestibular hair cells and vestibular afferent neurons