Joseph Sirosh, Risto Miikkulainen
A neural network model for the self-organization of ocular dominance and lateral connections from binocular input is presented. The self-organizing process results in a network where (1) afferent weights of each neuron or(cid:173) ganize into smooth hill-shaped receptive fields primarily on one of the reti(cid:173) nas, (2) neurons with common eye preference form connected, intertwined patches, and (3) lateral connections primarily link regions of the same eye preference. Similar self-organization of cortical structures has been ob(cid:173) served experimentally in strabismic kittens. The model shows how pat(cid:173) terned lateral connections in the cortex may develop based on correlated activity and explains why lateral connection patterns follow receptive field properties such as ocular dominance.