Using response time distributions to examine top-down influences on attentional capture

Abstract

Three experiments examined contingent attentional capture, which is the finding that cuing effects are larger when cues are perceptually similar to a target than when they are dissimilar to the target. This study also analyzed response times (RTs) in terms of the underlying distributions for valid cues and invalid cues. Specifically, an ex-Gaussian analysis and a vincentile analysis examined the influence of top-down attentional control settings on the shift and skew of RT distributions and how the shift and the skew contributed to the cuing effects in the mean RTs. The results showed that cue/ target similarity influenced the size of cuing effects. The RT distribution analyses showed that the cuing effects reflected only a shifting effect, not a skewing effect, in the RT distribution between valid cues and invalid cues. That is, top-down attentional control moderated the cuing effects in the mean RTs through distribution shifting, not distribution skewing. The results support the contingent orienting hypothesis (Folk, Remington, & Johnston, Journal of Experimental Psychology: Human Perception and Performance, 18, 1030-1044, 1992) over the attentional disengagement account (Theeuwes, Atchley, & Kramer, 2000) as an explanation for when top-down attentional settings influence the selection of salient stimuli.Keywords Attentional capture . Attentional control . Response time distributionHow and when do top-down settings and bottom-up signals moderate the allocation of attention toward salient items? Some propose that salient items receive priority and are selected in a stimulus-driven manner (e.g., Theeuwes, 1992Theeuwes, , 1994Theeuwes, , 2010Yantis, 1993Yantis, , 2000Yantis & Egeth, 1999). Others propose that salient items are selected only if they are relevant to current goals (e.g., Folk, Remington, & Johnston, 1992;Folk, Remington, & Wright, 1994). Although top-down modulation of attention is well-established, the issue of how and when this modulation occurs is contested. Part of the issue may be the reliance on measures of central tendency of behavioral responses-namely, mean response times (M RT )-to infer when top-down modulation occurs. Results of studies using differences in M RT (or lack thereof) between conditions do not unambiguously support one side of the debate. This study went beyond using measures of central tendency by examining top-down modulation of the shift and skew of RT distributions in attentional capture tasks. Identifying how top-down control influences RT distributions provided insight as to when top-down control modulates the selection of salient stimuli.Evidence that salient items are selected only if they are featurally relevant comes from Folk et al. (1992), in which a color cue or onset cue appeared 150 ms prior to a target that was an onset singleton for some subjects and a color singleton for others. Folk et al. (1992) hypothesized that subjects would enter the target-defining feature into an attentional set that would moderate shifting attention toward the cues. Specifi...

The contribution of color to attention capture effects during search for onset targets

“…Furthermore, the stronger cueing effects of cues with a color matching that of the searched-for targets than of cues with a color different from the targets were present from the fastest responses onward. This observation is in line with the theory of top-down contingent capture because, according to this theory, participants would set up their attentional control settings in advance, so that each stimulus that matched the setting would have a chance of capturing attention more efficiently from the fastest responses onward (Ansorge & Horstmann, 2007;Burnham, 2013). In the present study, we found no direct support for the deallocation theory, which predicts an increase of the cueing-effect difference between matching and nonmatching cues across time.…”

“…In any case, the difference between the cueing effects of matching white color cues and of nonmatching red color cues was present from the fastest responses onward. This is also in line with a contingent-capture account, since control settings are assumed to be set up in advance and can therefore effectively determine which stimuli capture attention directly, from stimulus onset onward (Ansorge & Horstmann, 2007;Burnham, 2013). In contrast, positive evidence for more deallocation (Theeuwes, 2010;Theeuwes et al, 2000) with nonmatching cues than with matching cues would have consisted of a significant cueing effect by nonmatching cues in the earliest quintile(s) and its decrement with increasing RTs (as more time would have passed since the initial capture).…”

Effects of relevant and irrelevant color singletons on inhibition of return and attentional capture

“…In line with the contingent capture view, among the fastest responses, capture effects were restricted to the matching cueing conditions (see Ansorge & Horstmann, 2007;Burnham, 2013). Again, however, it is equally possible that intertrial priming increased the capture effect in the matching conditions.…”

Change in intraindividual variability over time as a key metric for defining performance-based cognitive fatigability

“…5D). Ex-Gaussian models have been previously used to understand the source of reaction time changes in psychological tasks (Burnham, 2012; Heathcote et al, 1991). Given that top-down control processes are slower than stimulus driven processes, it has been hypothesized that changes in the exponential component τ are more likely due to alterations in top-down influences (Burnham, 2012).…”

“…Ex-Gaussian models have been previously used to understand the source of reaction time changes in psychological tasks (Burnham, 2012; Heathcote et al, 1991). Given that top-down control processes are slower than stimulus driven processes, it has been hypothesized that changes in the exponential component τ are more likely due to alterations in top-down influences (Burnham, 2012). This interpretation would be consistent with other evidence suggesting that fatigue specifically affects aspects of tasks and neurophysiological markers of cognitive control (Boksem, Meijman, & Lorist, 2006).…”