Neural field model of oculomotor preparation and disengagement

Seeking to develop an artificial neural network model that can match the behavior of the primate oculomotor system and is solidly grounded in the most up-to-date neuroscientific knowledge, we chose, from among extant models, an abstract, neural field model (Kopecz, 1995) as a starting point. Originally designed to reproduce the “gap effect”, this model appealed to us because: (1) its motor programming units appear analogous to “buildup” neurons in the middle layer of the superior colliculus, and (2) in contrast to most other models, this one explicitly allows for intentional inputs to motor programming. Our behavioral data reveals a small effect of voluntary preparation (target location probability) in the overlap and step conditions which becomes very large in the gap condition (fixation is removed 200 ms prior to the appearance of the target). Although the original model could not match this pattern, a match was achieved by modifying the temporal pattern of intentional inputs, a modification that also produced a better match between the dynamic properties of our “abstract” motor programming units and actual “buildup” neurons