Learning mechanisms in the temporal lobe visual cortex

Abstract

Neurophysiological experiments are described which show that neurons form ensemble encoded representations of stimuli such as faces which are relatively invariant with respect to size, contrast, spatial frequency, translation, and view. It is shown that new representations of objects can be formed with less than 5 s of visual experience with those objects. Mechanisms by which the brain could perform this invariant recognition, and learn the representations required for recognition, are described. A neural network simulation of these mechanisms for learning invariant representations is then described. The model uses a multistage feed-forward architecture, and is able to learn invariant representations of objects including faces by use of a Hebbian synaptic modification rule which incorporates a short memory trace (0.5 s) of preceding activity. This trace rule enables the network to learn the properties of objects which are spatio-temporally invariant over this time scale.