Processing of hierarchic stimulus structures has advantages in humans and animals.

Carmesin and Schwegler (1994) have determined theoretically that a linear hierarchical stimulus structure can be encoded by a parallel network of minimal complexity. The experiments reported here compare the efficiency with which humans and pigeons process sets of stimulus pairs embodying different inequality structures. Groups of subjects of each species were taught to discriminate all 10 pairwise combinations of 5 stimuli with an operant conditioning method. For one group, the reward/punishment allocations within the pairs agreed with a linear hierarchy. For a second and third group, the reinforcement allocations of one or three, respectively, of the stimulus pairs deviated from such ordering. The time it took the subjects to learn the tasks as well as the final choice latencies and/or error rates increased with the number of deviating inequalities. The results agree with the assumption that both humans and pigeons encode stimulus inequality structures with parallel processing neural networks rather than with a sequentially processing algorithm.