Data analyzed in this study were derived from the responses of 128 spinothalamic tract (STT) cells and 110 thalamic neurons recorded in 75 anesthetized monkeys. A k-means cluster analysis, a nonhierarchical clustering technique, was performed using the relative magnitudes of responses to a graded series of innocuous and noxious mechanical stimuli applied to the receptive field. For comparison, a parallel analysis was performed based on definitions of low-threshold (LT), wide dynamic range (WDR), and high-threshold (HT) cells used by our laboratory. For 128 STT cells, a classification scheme with three clusters was found statistically to be the best. This yielded groups of 22, 57, and 49 cells in clusters 1, 2, and 3, respectively. Cluster 1 cells were activated best by low-intensity mechanical stimuli, whereas cluster 3 cells were activated primarily by nociceptive stimuli. Cluster 2 cells had intermediate characteristics. When the classification scheme based on the cluster analysis was compared with the classification of the same neurons as LT, WDR, and HT cells, cluster 1 cells were divided into LT and WDR cells, whereas cluster 2 and 3 cells included WDR and HT cells. For 110 thalamic neurons, a classification scheme with five clusters was found statistically to be the best. Clusters 1-5 contained 25, 34, 17, 10, and 24 cells, respectively. Response characteristics of cells in each group indicated a gradual change in sensitivity to higher intensities of peripheral input from cluster 1 to 5. When this classification scheme was compared with the classification scheme previously used by our laboratory, cluster 1 cells belonged to the LT group, clusters 2 and 3 split into LT and WDR cells, and clusters 4 and 5 included WDR and HT cells. It is concluded that a classification scheme based on a cluster analysis of the responses of neurons to standardized stimuli may provide an objective and functionally meaningful way to categorize somatosensory neurons.