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1. General biological theories of learning are mentioned. The importance of developing more specific formulations is argued. 2. A neural-behavioral model of operant learning is presented. The model shows hypothesized, functional connections among various neurons and the muscles which control behavior. The operation and role of various neurons are described in detail. This model demonstrates the necessary condition that the physiological changes which result from an organism's reinforcement and feedback reaction to its response are able to account for the increased probability of correct response observed behaviorally when an organism is retested following training. Proposed changes occur only at those neurons which are instrumental in establishing response. Therefore fortuitous changes are avoided. 3. A synaptic-neural model is proposed as part of the neural-behavioral model in order to explain how changes in learning may be physically realized. This model involves the interaction of transmitter molecules but only to a significant extent when two adjacent synapses of the neural-behavioral model are concurrently highly active. The suggested result of the transmitter interaction is a blockage of postsynaptic receptor sites. A kinetic description is proposed for these reactions and solved numerically by computer techniques. With suitably selected values for the rate constants, this model is shown to yield a formulation consistent with the requirements of the neural-behavioral model. 4. The features and assumptions of the model presented and of several other biological models are discussed. More experimental investigations into the interaction of presynaptic terminals on the same neuron during paired excitation are encouraged. Some predictions about behavior are derived from the model. Comparison with behavioral data is made. The goals of hypothetical modeling are stated.

A model is formulated for the conversion of a motoneuron's spike train to tension in a muscle. This model demonstrates that a spike train whose adjacent interspike intervals are negatively correlated results in a steady-state tension which fluctuates less about its mean value than if the interspike intervals are randomly arranged. The ability of a spike train to develop more distinguishable levels of tension by negative correlation between adjacent interspike intervals is more significant for interspike interval distributions with greater dispersion. The number of distinguishable tension levels increases by about 33 percent when a typical set of neuromuscular parameters are used. These results may be generalized to the smoothing of postsynaptic potentials and the regulation of blood pressure.