Our present knowledge of brain structure and function requires that any model of neuronal circuitry designed to account for learning must satisfy three conditions. It must (1) meet economy restrictions on the number of cells in the brain, (2) use the same set of cells to account for a number of different behaviors, and (3) not require a detailed embryological specification of its connections. Previously published models have failed to meet one or more of these conditions. In this paper, a model is presented which does satisfy them, and in doing so accounts in detail for classical conditioning, operant conditioning, and other learning tasks. The model employs the types of synapses proposed by Burke and Hebb in simple modular circuits as a means of providing independent storage of information at each modifiable synapse.
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