A Learning Model for Forced - Choice Deteciion Experiments

Several signal detection experiments are analyzed in terms of a model that incorporates two distinct processes: an activation process and a decision process. The activation process specifies the relation between external signal events and hypothetized sensory states of the subject. The decision process specifies the relation between the sensory states and the observable responses of the sUbject. The act iva-tion process is assumed to be fixed throughout an experiment, whereas the decision process is viewed as varying from trial to trial as a function of the particular sequence of preceding events. The changes in the decision process are governed by a simple stochastic learning mechanism, and the experimental studies reported here are designed specifically to test the adequacy of this and related representations.