Incorporating developmental factors into models of accommodation and vergence

eye movements, neural network models Purpose: To investigate how known developmental factors can be incorporated into neural network models of the accommodation and vergence systems. To demonstrate that models of this type can learn adult-like linkages between accommodation and vergence by simple associative mechanisms. Methods: Existing linear systems models were used as a starting point for the design of a series of multi-layer neural network models of accommodation and vergence. Unlike the systems models that are generally specified in detail by hand, the neural models learn for themselves how to perform appropriately. A general connectionist framework was set up and trained, by updating initially small random connection weights using gradient descent, so that the network outputs for realistic patterns of input cues (blur, disparity, etc.) corresponded to appropriate patterns of accommodation and vergence responses. Maturational factors were incorporated into the models by using empirical infant data to define starting points, by varying parameters such as depth of field durin