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A neural network model is proposed to obtain a numerical description of pain mechanisms. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature and by ourselves. Those studies, especially on the neural connections between the neural units concerned in the pain mechanisms do not give conclusive evidence, and some of the results are claimed by other investigators. The assumptions used are unverified for this reason. The quantitative model presented is only a simplified one and simulates only one directional ascending and descending pathway for the pain sensation in which peripheral receptors, afferent A, A 5, and C fibers, and the receptive cells of spinal cord, brain stem, thalamus, and the cerebral cortex are involved. No interactions from the lateral adjacent fields such as lateral inhibition and facilitation have been proposed, and no analytical elucidation of spatial information processing mechanisms has been made. Only the firing characteristics of the neural cells related to pain generation are investigated and compared with the physiological results. Adaptation effect and conduction velocity of neural fibers are considered in the model, however the fibers in each neural unit are assumed to have constant conduction velocity and firing threshold. Model simulation has been carried out for the single square-wave pulse and the periodic repetitive pulse stimulation applied on peripheral receptors.