The structure of sequential effects

There is a long history of research into sequential effects, extending more than one hundred years. The pattern of sequential effects varies widely with both experimental conditions as well as for different individuals performing the same experiment. Yet this great diversity of results is poorly understood, particularly with respect to individual variation, which save for some passing mentions has largely gone unreported in the literature. Here we seek to understand the way in which sequential effects vary by identifying the causes underlying the differences observed in sequential effects. In order to achieve this goal we perform principal component analysis on a dataset of 158 individual results from participants performing different experiments with the aim of identifying hidden variables responsible for sequential effects. We find a latent structure consisting of 3 components related to sequential effects-2 main and 1 minor. A relationship between the 2 main components and the separate processing of stimuli and of responses is proposed on the basis of previous empirical evidence. It is further speculated that the minor component of sequential effects arises as the consequence of processing delays. Independently of the explanation for the latent variables encountered, this work provides a unified descriptive model for a wide range of different types of sequential effects previously identified in the literature. In addition to explaining individual differences themselves, it is demonstrated how the latent structure uncovered here is useful in understanding the classical problem of the dependence of sequential effects on the interval between successive stimuli.