A neural network model for cognitive activity.
A consideration of the storage of information as an energized neuronal state leads to the development of a new type of neural network model which is capable of pattern recognition, concept formation and recognition of patterns of events in time. The network consists of several layers of cells, each cell representing by connections from the lower levels some combination of features or concepts. Information travels toward higher layers by such connections during an association phase, and then reverses during a recognition phase, where higher-order concepts can redirect the flow to more appropriate elements, revising the perception of the environment. This permits a more efficient method of distinguishing closely-related patterns and also permits the formation of negative associations, which is a likely requirement for formation of "abstract" concepts.
D001245:Association Learning / Q000502:physiology; D003071:Cognition / Q000502:physiology*; D003201:Computers; D003210:Concept Formation / Q000502:physiology; D003491:Cybernetics; D006801:Humans; D007092:Imagination / Q000502:physiology; D008959:Models, Neurological; D008960:Models, Psychological; D010364:Pattern Recognition, Visual / Q000502:physiology