Self-Organization, Plasticity, and Low-Level Visual Phenomena in a Laterally Connected Map Model of the Primary Visual Cortex (1997)
Based on a Hebbian adaptation process, the afferent and lateral connections in the RF-LISSOM model organize simultaneously and cooperatively, and form structures such as those observed in the primary visual cortex. The neurons in the model develop local receptive fields that are organized into orientation, ocular dominance, and size selectivity columns. At the same time, patterned lateral connections form between neurons that follow the receptive field organization. This structure is in a continuously-adapting dynamic equilibrium with the external and intrinsic input, and can account for reorganization of the adult cortex following retinal and cortical lesions. The same learning processes may be responsible for a number of low-level functional phenomena such as tilt aftereffects, and combined with the leaky integrator model of the spiking neuron, for segmentation and binding. The model can also be used to verify quantitatively the hypothesis that the visual cortex forms a sparse, redundancy-reduced encoding of the input, which allows it to process massive amounts of visual information efficiently.
In Perceptual Learning, R. L. Goldstone and P. G. Schyns and D. L. Medin (Eds.), pp. 257-308 1997.

James A. Bednar Postdoctoral Alumni jbednar [at] inf ed ac uk
Yoonsuck Choe Ph.D. Alumni choe [at] tamu edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Joseph Sirosh Ph.D. Alumni joseph sirosh [at] gmail com

The LISSOM package contains the C++, Python, and Scheme source code and examples for training and testing firing-rate...