Abstract
Influential models of visual search assume that dimension-specific feature contrast signals are summed into a master saliency map in a coactive fashion. The main source of evidence for coactivation models, and against parallel race models, is violations of the race model inequality (RMI; Miller, 1982) by redundantly defined singleton feature targets. However, RMI violations do not rule out serial exhaustive (Townsend & Nozawa, 1997) or interactive race (Mordkoff & Yantis, 1991) architectures. These alternatives were tested in two experiments. In Experiment 1, we used a double-factorial design with singleton targets defined in two dimensions and at two levels of intensity, to distinguish between serial versus parallel models and self-terminating versus exhaustive stopping rules. In Experiment 2, we manipulated contingency benefits that are expected to affect the magnitude of redundancy gains and/or RMI violations on the assumption of an interactive race. The results of both experiments revealed redundancy gains as well as violations of the RMI, but the data pattern excluded serial-exhaustive and interactive race models as possible explanations for RMI violations. This result supports saliency summation (coactivation) models of search for singleton feature targets.
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This research was supported by the following grants: DFG Excellence Cluster EC 142 “CoTeSys” (H.J.M. & M.Z.), the DFG Research Group FOR480 (J.K. & H.J.M.), and Swiss National Science Foundation Project PP001-110543/1 (J.K.).
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Zehetleitner, M., Krummenacher, J. & Müller, H.J. The detection of feature singletons defined in two dimensions is based on salience summation, rather than on serial exhaustive or interactive race architectures. Attention, Perception, & Psychophysics 71, 1739–1759 (2009). https://doi.org/10.3758/APP.71.8.1739
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DOI: https://doi.org/10.3758/APP.71.8.1739