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What do fast response times tell us about attentional control?

The mental experience of attention capture has attracted a great deal of intrigue among researchers seeking to explain the interactions between stimulus-driven and goal-driven attentional control. In recent years, researchers have increasingly begun to analyze cumulative response time (RT) distribut...

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Bibliographic Details
Published in:Journal of vision (Charlottesville, Va.) Va.), 2013-10, Vol.13 (3), p.31-31
Main Authors: Leber, Andrew B, Lechak, Jennifer R, Tower-Richardi, Sarah M
Format: Article
Language:English
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Summary:The mental experience of attention capture has attracted a great deal of intrigue among researchers seeking to explain the interactions between stimulus-driven and goal-driven attentional control. In recent years, researchers have increasingly begun to analyze cumulative response time (RT) distributions to test modern accounts of the capture phenomenon, particularly accounts claiming that there are changes in susceptibility to distraction as a function of time. In this paper, we raise a criticism of this approach, which centers on a problematic assumption. The assumption is that variability in these distributions is primarily determined by fluctuations in the observer's internal control state (e.g., readiness for the trial). However, it is also the case that faster segments of the distributions are overrepresented by trials that are objectively easy, while slower segments are overrepresented by trials that are objectively difficult. That is, incidental aspects of the trial stimuli influence task performance independently of the observer's internal control state. Here, we demonstrate empirically that contributions of incidental stimulus factors distort cumulative RT distributions in such a way that confounds proper interpretation of experimental data. The results have implications for theoretical accounts of attentional control, and they also raise caution about the assumptions that are sometimes made when analyzing cumulative RT distributions.
ISSN:1534-7362
1534-7362
DOI:10.1167/13.3.31