A Neural Model of Coordinated Head and Eye Movement Control

Gaze shifts require the coordinated movement of both the eyes and the head in both animals and humanoid robots. To achieve this the brain and the robot control system needs to be able to perform complex non-linear sensory-motor transformations between many degrees of freedom and resolve the redundancy in such a system. In this article we propose a hierarchical neural network model for performing 3-D coordinated gaze shifts. The network is based on the PC/BC-DIM (Predictive Coding/Biased Competition with Divisive Input Modulation) basis function model. The proposed model consists of independent eyes and head controlled circuits with mutual interactions for the appropriate adjustment of coordination behaviour. Based on the initial eyes and head positions the network resolves redundancies involved in 3-D gaze shifts and produces accurate gaze control without any kinematic analysis or imposing any constraints. Furthermore the behaviour of the proposed model is consistent with coordinated eye and head movements observed in primates.