A realistic neural-network simulation of both slow and quick phase components of the guinea pig VOR

Abstract

A realistic neural-network model was constructed to simulate production of both the slow-phase and quick-phase components of vestibular nystagmus by incorporating a quick-phase pathway into a previous model of the slow phase. The neurons in the network were modelled by multicompartmental Hodgkin–Huxley-style spiking neurons based on known responses and projections of physiologically identified vestibular neurons. The modelling used the GENESIS software package. The slow-phase network consisted of ganglion and medial vestibular nucleus (MVN) neurons; the latter were constructed using biophysical models of MVN type A and B neurons. The quick-phase network contained several types of bursting cells which have been shown to have major roles in the generation of the quick phase: burster-driver neurons, long-lead burst neurons, pause neurons, excitatory burst neurons and inhibitory burst neurons. Comparison of the output neural responses from the model with guinea pig behavioural responses from the companion paper showed consistency between model and animal data for neuron firing patterns, maximal firing rates, and timing, duration and number of quick phases. Comparisons were made for stable head input and for sinusoidal angular stimuli at a range of frequencies from 0.1 to 2 Hz. Except for data at 0.1 Hz, where the simulation produced one more quick phase per half cycle than the animal data, the number of quick phases was consistent between the model and the animal data. The model was also used to simulate the effects both of unilateral vestibular deafferentation (UVD) and of vestibular compensation after UVD, and the responses in the modelled MVN neurons were affected in a way similar to those measured in guinea pig MVN neurons: the number of quick phases and their timing changed in a similar fashion to that observed in behavioural data.