http://cogprints.org/1913/
Modeling the self-organization of directional selectivity in the primary visual cortex
A model is proposed to demonstrate how neurons in the primary visual cortex could self-organize to represent the direction of motion. The model is based on a temporal extension of the Self-Organizing Map where neurons act as leaky integrators. The map is trained with moving Gaussian inputs, and it develops a retinotopic map with orientation columns that divide into areas of opposite direction selectivity, as found in the visual cortex.
Farkas, Igor
Miikkulainen, Risto
Neural Nets
Neural Modelling
Igor
Farkas
Risto
Miikkulainen