Editorial

A special issue on applications of Signal Detection Theory to visual perception Like most theories that have wide application, signal detection theory is based upon simple ideas. The stimulus factors that influence perceptual decisions are corrupted by random variations — noise. Observers collect noisy information and distill it down to a single quantity, represented by the decision variable. The value of that variable after a given observation is compared against a criterion value and the result determines the choice of the observer. Thus, according to signal detection theory, to predict the behavior of the observer one needs to understand both the deterministic and random aspects of the stimulus information, the task characteristics that influence the collection and distillation, and the motivational factors that influence the criterion. These ideas were most famously systematized by Peterson et al. (1954) but in vision had been employed earlier. In particular, Hecht et al. (1942), and later Baker (1953) and Barlow (1957), were concerned with the photon fluctuations of light an