Testable predictions from realistic neural network simulations of vestibular compensation: integrating the behavioural and physiological data

Neural network simulations have been used previously in the investigation o f the horizontal vestibule-ocular reflex (HVOR) and vestibular compensation . The simulations involved in the present research were based on known anat omy and physiology of the vestibular pathway. This enabled the straightforw ard comparison of the network response, both in terms of behavioural (eye m ovement) and physiological (neural activity) data to empirical data obtaine d from guinea pig. The network simulations matched the empirical data close ly both in terms of the static symptoms (spontaneous nystagmus) of unilater al vestibular deafferentation (UVD) as well as in terms of the dynamic symp toms (decrease in VOR gain). The use of multiple versions of the basic netw ork, trained to simulate individual guinea pigs, highlighted the importance of the particular connections: the vestibular ganglion to the type I media l vestibular nucleus (MVN) cells on the contralesional side. It also indica ted the significance of the relative firing rate in type I MVN cells which make excitatory connections with abducens cells as contributors to the vari ability seen in the level of compensated response following UVD. There was an absence of any difference (both in terms of behavioural and neural respo nse) between labyrinthectomised and neurectomised simulations. The fact tha t a dynamic VOR gain asymmetry remained following the elimination of the sp ontaneous nystagmus in the network suggested that the amelioration of both the static and dynamic symptoms of UVD may be mediated by a single network. The networks were trained on high acceleration impulse stimuli but display ed the ability to generalise to low frequency, low acceleration sinusoids a nd closely approximated the behavioural responses to those stimuli.