Self-organizing neural network that discovers surfaces in random-dot stereograms

THE standard form of back-propagation learning1 is implausible as a model of perceptual learning because it requires an external teacher to specify the desired output of the network. We show how the external teacher can be replaced by internally derived teaching signals. These signals are generated by using the assumption that different parts of the perceptual input have common causes in the external world. Small modules that look at separate …