Overt attentional capture by reward-related stimuli overcomes inhibitory suppression.

Abstract

Salient-but-irrelevant distractors can automatically capture attention and eye-gaze in visual search. However, recent findings have suggested that attention to salient-but-irrelevant stimuli can be suppressed when observers use a specific target template to guide their search (i.e., feature search). A separate line of research has indicated that attentional selection is influenced by factors other than the physical salience of a stimulus and the observer's goals.For instance, pairing a stimulus with reward has been shown to increase the extent to which it captures attention and gaze (as though it has become more physically salient), even when such capture has negative consequences for the observer. Here we used eye-tracking with a rewarded visual search task to investigate whether capture by reward can be suppressed in the same way as capture by physical salience. When participants were encouraged to use feature search, attention to a distractor paired with relatively small reward was suppressed. However, under the same conditions attention was captured by a distractor paired with large reward, even when such capture resulted in reward omission. These findings suggest that reward-related stimuli are given special priority within the visual attention system over and above physically-salient stimuli, and have implications for our understanding of real-world biases to reward-related stimuli, such as those seen in addiction.Word count: 8515 REWARD OVERCOMES ATTENTIONAL SUPPRESSION 3 Overt attentional capture by reward-related stimuli overcomes inhibitory suppression

Reward learning and statistical learning independently influence attentional priority of salient distractors in visual search

“…In this case, the independent effects of value and location indicate that a fixed, limited amount of suppression was applied to this frequent location, and this suppression applied equally to both types of distractor. Consequently, high-value distractors were more likely to 'break through' this suppression and capture attention, thus LOCATION-BASED SUPPRESSION AND REWARD LEARNING 28 slowing search -an idea that is consistent with conclusions from previous research that has examined effects of reward in the context of other forms of inhibition (Pearson et al, 2020;Wang et al, 2014).…”

“…Previous studies have found medium to very large effect sizes (d z = 0.54-2.20) for the influence of reward on attention in tasks similar to that used here (e.g., Le Pelley et al, 2015;Pearson et al, 2015Pearson et al, , 2016Watson et al, 2019aWatson et al, , 2019bWatson et al, , 2020, and large effect sizes (d z = 0.69-2.15) for the influence of statistical learning about distractor location (Failing, Feldmann-Wüstefeld, et al, 2019;Failing & Theeuwes, 2020;).…”

“…Critically (and unlike the current study), Failing and Theeuwes found that this manipulation of physical salience generated significantly stronger suppression in the frequent location of the high-salience distractor than in the frequent location of the low-salience distractor. In summary, then, it seems that differences in physical salience of distractors can result in different levels of suppression arising from statistical learning, but differences in value (or incentive salience: Berridge & Robinson, 1998;Colaizzi et al, 2020;Pearson et al, 2020) do not. Again this conclusion is consistent with the idea that suppression develops at the level of salience maps relating to physical features, rather than maps encoding value.…”

Learning to avoid looking: Competing influences of reward on overt attentional selection

“…Even though looking at the high-reward-signalling distractor was counterproductive (as it triggered the omission of a relatively large reward), participants came to look at it more often than the low-reward-signalling distractor, thereby cancelling more high rewards. Subsequent research has indicated that this overt attentional bias to signals of reward is largely immune to top-down control, in that it persists when participants are explicitly instructed that looking at the reward-signalling distractor will result in reward omission (Kim & Anderson, 2019;Pearson, Donkin, Tran, Most, & Le Pelley, 2015), and under search conditions that allow physically salient distractors to be suppressed (Pearson, Watson, Cheng, & Le Pelley, 2020). However, the magnitude of VMAC has been shown to increase when cognitive control resources are depleted (Watson, Pearson, Chow, et al, 2019), which suggests a limited role for top-down control processes in reducing (but not preventing) the likelihood of capture by signals of reward.…”

Reward Does Not Modulate the Preview Benefit in Visual Search

“…There are various pathways through which reward might be expected to influence performance in this procedure. Notably, evidence suggests that reward-signaling stimuli are more likely (than non-reward stimuli) to capture and hold attention (Anderson, 2016;Failing & Theeuwes, 2018;Le Pelley et al, 2016;Watson, Pearson, Theeuwes, Most & Le Pelley, 2020) and are particularly difficult to suppress via inhibitory processes (e.g., Pearson, Watson, Cheng & Le Pelley, 2020;Wang, Duan, Theeuwes & Zhou, 2014). Hence, we hypothesized that participants may have difficulty disengaging attention from reward-signaling stimuli in the preview display, which would enhance performance when the target subsequently appeared at one of these previewed THE EFFECT OF REWARD ON PREVIEW BENEFIT locations (i.e., old-target-location trials) and impair performance when the target appeared at a new location.…”