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Simulations were performed of layers I and II of olfactory paleocortex, as connected to its primary input structure, olfactory bulb. Induction of synaptic long-term potentiation by means of repetitive sampling of inputs caused the simulation to organize encodings of learned cues into a hierarchical memory that uncovered statistical relationships in the cue environment, corresponding to the performance of hierarchical clustering by the biological network. Simplification led to characterization of those parts of the network responsible for the mechanism, resulting in a novel, efficient algorithm for hierarchical clustering. The hypothesis is put forward that these corticobulbar networks and circuitry of similar design in other brain regions contain computational elements sufficient to construct perceptual hierarchies for use in recognizing environmental cues.