RESEARCH ARTICLE Undesirable Choice Biases with Small Differences in the Spatial Structure of Chance Stimulus Sequences

In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use ran-dom numbers derived from a discrete binomial distribution to create a 'full random training schedule ' (FRS). When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases ' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'). As an alternative, a 'Gellerman-like training schedule ' (GLS) can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypoth-esized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by