A computational model of early visual cortex using konio-cellular pathway projections

We present a computational model of the visual cortex using anatomically realistic projections incorporating two color opponent channels and a luminance channel. We model the visual cortex area V1 with a red-green opponent channel projecting to a simulated layer 4c beta, and a luminance channel projecting to layer 4c alpha. Both these layers project to a cortical layer 2/3. We specifically model the konio-cellular pathway, providing direct blue-yellow chromatic input to layer 2/3 within targeted blob regions. We utilize a self-organizing map algorithm to learn synaptic weights while the system is driven by artificial inputs initially, and followed by natural image stimuli. The same algorithm is used for learning in all the hierarchically structured maps. We produce maps of orientation and color selectivity, and apply statistical measures to examine the variations in these maps between the blob and interblob regions. We show that an orientation map exists throughout layer 2/3, whereas a complete color hue map is produced in the blob regions. Both orientation and color selectivity are present throughout layer 2/3. The mean orientation selectivity is lower in the blob regions as compared to the interblob regions. However, there is greater color selectivity in the blob regions compared to the interblob regions. We make a testable prediction that a statistically significant difference in color selectivity in neuronal populations will be observed in the primate visual cortex between blob and interblob regions.