Ideal observer analysis for continuous tracking experiments

Continuous tracking is a newly developed technique that allows fast and efficient data acquisition by asking participants to “track” a stimulus varying in some property (usually position in space). Tracking is a promising paradigm for the investigation of dynamic features of perception and could be particularly well suited for testing ecologically relevant situations difficult to study with classical psychophysical paradigms. The high rate of data collection may be useful in studies on clinical populations and children, who are unable to undergo long testing sessions. In this study, we designed tracking experiments with two novel stimulus features, numerosity and size, proving the feasibility of the technique outside standard object tracking. We went on to develop an ideal observer model that characterizes the results in terms of efficiency of conversion of stimulus strength into responses, and identification of early and late noise sources. Our ideal observer closely modeled results from human participants, providing a generalized framework for the interpretation of tracking data. The proposed model allows to use the tracking paradigm in various perceptual domains, and to study the divergence of human participants from ideal behavior.