Studying the dynamics of visual search behavior using RT hazard and micro-level speed-accuracy tradeoff functions: A role for recurrent object recognition and cognitive control processes.

Abstract

Thanks to the work of Anne Treisman and many others, the visual search paradigm has become one of the most popular paradigms in the study of visual attention. However, statistics like mean correct response time (RT) and percent error do not usually suffice to decide between the different search models that have been developed. Recently, to move beyond mean performance measures in visual search, RT histograms have been plotted, theoretical waiting time distributions have been fitted, and whole RT and error distributions have been simulated. Here we promote and illustrate the general application of discrete-time hazard analysis to response times, and of micro-level speed-accuracy tradeoff analysis to timed response accuracies. An exploratory analysis of published benchmark search data from feature, conjunction, and spatial configuration search tasks reveals new features of visual search behavior, such as a relatively flat hazard function in the right tail of the RT distributions for all tasks, a clear effect of set size on the shape of the RT distribution for the feature search task, and individual differences in the presence of a systematic pattern of early errors. Our findings suggest that the temporal dynamics of visual search behavior results from a decision process that is temporally modulated by concurrently active recurrent object recognition, learning, and cognitive control processes, next to attentional selection processes.