DYNAMIC MODELS FOR LATENCY ACCURACY RELATIONS IN MEMORY

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Explorations of the nature of psychological information and the cognitive processes that operate on information typically use either response latency or probability as a primary dependent measure. This is due partly to the clear difficulties associated with interpreting (for example) latencies in reduced-accuracy conditions or response probabilities when performance is near ceiling. Over the past few decades, the separate bodies of literature dealing with these two measures of performance have developed rather refined approaches to assessing aspects of psychosocial (on the basis of response probabilities) and the processes that operate on that information (on the basis of response latencies). The proposed project is intended to provide initial steps in developing and testing a theoretical language to relate response latency and probability in a variety of cognitive tasks. The theory will make use of linear dynamic systems formulations, augmented with stochastic components. It will be developed explicitly to make contact with two existing bodies of theory, each of which has explored fundamental characteristics of cognition. The first-systems factorial technology (e.g., Townsend & Nozawa, 1995)- addresses elementary processes characteristics, while the second-general recognition theory (e.g., Ashby & Townsend, 1986) addresses aspects of independence in psychological information. In addition, the work will be applied to developing and testing alternative representations for an hypothesis concerning memory for meaningful visual objects, such as faces.