Although a considerable amount of knowledge has been accumulated about the activity of individual nerve cells in the brain, little is known about their mutual interactions at the local level. The method presented in this paper allows the reconstruction of functional relations within a group of neurons as recorded by a single microelectrode. Data are sampled at 10 or 13 kHz. Prominent spikes produced by one or more single cells are selected and sorted by K-means cluster analysis. The activities of single cells are then related to the background firing of neurons in their vicinity. Auto-correlograms of the leading cells, auto-correlograms of the background cells (mass correlograms) and cross-correlograms between these two levels of firing are computed and evaluated. The statistical probability of mutual interactions is determined, and the statistically significant, most common interspike intervals are stored and attributed to real pairs of spikes in the original record. Selected pairs of spikes, characterized by statistically significant intervals between them, are then assembled into a working model of the system. This method has revealed substantial differences between the information processing in the visual cortex, the inferior colliculus, the rostral ventromedial medulla and the ventrobasal complex of the thalamus. Even short 1-s records of the multiple neuronal activity may provide meaningful and statistically significant results.