Present-day techniques of multiple-electrode together with computer-aided separation of impulses arising from different neurons permit the simultaneous recording of nerve-impulse timings in sets of neurons exceeding 20 in number. This in turn makes it feasible to search for functional groups of neurons, defined as subsets that tend to fire in near simultaneity significantly more often than would independent neurons at corresponding mean rates. A statistical technique is described that permits the detection and identification of such functional groups. The method is accretional, based on identification of associated neurons through interative application of a significance test on multiple coincidences of neuronal firings within an observational window. Examples of the operation of the method and indications as to its sensitivity are furnished through computer simulations of neural networks. The entire algorithm may be used as a screening technique to select smaller groups of neurons for cross-correlational and related finer-grained temporal analyses, or it may be used in its own right to detect and characterize functional groups that are not distinguishable by other statistical procedures.