1. A brief outline of the evolution of neuron modeling is given and an argument is presented for studying neural behavior by “black-box” logical equivalence. 2. An electronic circuit incorporating many of the digital and analog properties of neurons is described. Having such properties as variable threshold, summation, all-or-none output, absolute and relative refractoriness, and inhibition, it exhibits a considerable amount of functional equivalence to biological structures. 3. Properties of the model are described in detail and relevance to biological neuron measurements are shown. Such behavior as time-intensity trade, repetitive firing and temporal summation are readily achieved and are shown to approximate in vivo behavior. 4. The model is sufficiently flexible so that with simple parameter changes and external circuit configurations, a wide variety of neurological phenomena can be exhibited and studied closely. By adding stimulus-derived inhibition for example, accommodation and adaptation are obtained. 5. Experiments with the model have suggested new relationships which nervous structures may exhibit. A linear dependence of burst pulse number on accommodation time constant, and a summation-division phenomenon are examples of such findings. 6. Models of this sort have utility not only for studying single unit properties but also for investigating group interactions. Such studies may be relevant to elucidation of neural network behavior.