Integration of Vergence, Cyclovergence, and Saccades through Active Efficient Coding

This paper describes a unified computational model for the joint development of early visual representations and the control of three types of eye movements, i.e., vergence, cyclovergence, and saccades. The model is based on the Active Efficient Coding (AEC) framework, an extension of Barlow's efficient coding hypothesis to active perception. AEC describes the joint learning of sensory encoding and behavioral control. The present work relaxes the assumptions made in our previous work by learning vergence, cyclovergence, and saccades all from random initialization. Our results also demonstrate the importance of the interaction between the learning of these eye movements in terms of learning speed and accuracy. Overall, we find that AEC provides a parsimonious framework to account for the simultaneous learning of active vision skills.