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The principles of a general method for modeling the dynamics of interacting neural cell populations are presented. Hoffman's reflex, an electrically evoked spinal reflex of the lower leg, is used as an illustration of the method. Since the variables and structure of the resulting model are in direct correspondence with measurable physiological and anatomic quantities, it is suitable for the prediction of nervous system activity over a wide range of time scales and stimulus amplitudes. A relatively efficient representation of feedback interconnections among neural cell populations is also obtained.