A Cerebellar Spiking Neural Model for Phase Reversal of Vestibulo-ocular Reflex.

Abstract

Cerebellum possesses very rich motor control and learning capability which is critical for animals. In this study, we proposed a spiking neural network model of cerebellum for gain and phase adaptation in vestibulo-ocular reflex (VOR). VOR is a critical adaptive reflexive eye movement for maintaining a stable visual field. In this model (with neuron number at the order of 104), synaptic plasticity at parallel fiber-Purkinje cell synapses was considered. In particular, we have shown that the inhibitory inputs from molecular layer interneurons on Purkinje cells play a critical role in phase adaptation of VOR. The inhibitory input from interneurons indirectly affects the strength of long-term potentiation (LTP) and long-term depression (LTD), resulting in more drastic phase shift upon learning and hence allowing phase reversal of VOR. The strength of inhibitory input also affects the maximum phase shift that can be achieved. Our result is consistent with experiments in mutant mice with blocked inhibitory inputs.