In modelling the development of the oculomotor control system using neural networks, it is important to determine the appropriate cost function on which to train the models. Whilst blur and disparity are fairly obvious error components, choosing the regularization component is less easy. In this paper we explore the consequences of a number of the most reasonable possibilities and investigate the extent to which other factors may dominate their influence.
John A. Bullinaria, Patricia M. Riddell