Attentional economics links value-modulated attentional capture and decision-making

Pearson, Daniel; Watson, Poppy; Albertella, Lucy; Pelley, Mike E. Le

doi:10.1038/s44159-022-00053-z

Cited by 24 publications

(39 citation statements)

References 220 publications

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“…Prior research has shown that stimuli associated with reward (e.g., money or tasty food) become more likely to capture our attention in a way that we have little control over, and can do little to resist (see Anderson, 2016;Le Pelley et al, 2016;Pearson et al, 2022;Rusz et al, 2020). Importantly for current purposes, recent findings are in line with the idea that this reward-related attentional bias can modulate choice behavior (Gluth et al, 2018(Gluth et al, , 2020.…”

Section: Experiments 1: Reward-related Attention and Choicesupporting

confidence: 75%

Reward-driven and memory-driven attentional biases automatically modulate rapid choice

Pelley¹,

Newell²

2023

Preprint

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In two experiments we examined the influence of ‘history-driven’ attentional biases on choice behavior. In Experiment 1 we used a value-modulated attentional capture procedure to induce an automatic reward-related attentional bias, and found that this bias shaped choice in a subsequent task in which participants were required to pick the highest number from a briefly displayed choice array. In Experiment 2 we investigated the influence of a working memory manipulation, and found that choice in the number-selection task was influenced by the current (and prior) contents of memory, consistent with an influence of memory-driven attentional bias on information encoding. Our findings indicate that history-driven attentional biases can translate to an influence on overt, downstream processes of behavioural choice, and should be incorporated into models of the interaction between attention and choice.

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Section: Experiments 1: Reward-related Attention and Choicesupporting

confidence: 75%

Reward-driven and memory-driven attentional biases automatically modulate rapid choice

Pelley¹,

Newell²

2023

Preprint

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show abstract

“…The reasons for this discrepancy are unclear, but several points of difference are worth noting here. First, Ju and Cho used a two-phase procedure (see Pearson et al, 2022;Rusz et al, 2020) in which the critical reward-signalling colours defined the targets of search during an initial training phase, before becoming distractors in a subsequent test phase -in contrast to the current one-phase procedure in which the reward-signalling colours were never the search target and were distractors throughout.…”

Section: Discussionmentioning

confidence: 99%

“…One component of selection history relates to a stimulus's learned value: previous experience of the relationship between a stimulus and motivationally significant outcomessuch as reward (e.g., Anderson & Halpern, 2017;Anderson et al, 2011;Le Pelley et al, 2015;Le Pelley et al, 2019) and punishment (e.g., Anderson & Britton, 2020;Mikhael et al, 2021;Wentura et al, 2014)-automatically increases the attentional priority of that stimulus, making it more likely to capture attention regardless of our current goals (for recent reviews see: Pearson et al, 2022;Watson et al, 2019). For example, in a study by Le Pelley et al (2019), participants completed a visual search task in which they were required to make a rapid eye movement to a shape target (a diamond among circles) on each trial to earn reward.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty-modulated attentional capture: Outcome variance increases attentional priority

Pearson¹,

Chong²,

Garner³

et al. 2023

Preprint

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Previous research has shown that capture of visual attention is influenced by prior learning about reward: signals of high reward value are more likely to capture attention (and gaze) than signals of low reward value. In the current study, we show in two experiments that attentional priority is modulated not only by reward magnitude, but also by the uncertainty associated with that reward. Participants completed a visual search task in which they were required to make a saccade to a target shape to earn monetary reward. The color of a color-singleton distractor in the search array signaled the reward outcome(s) that were available. Different distractor colors were associated with different degrees of variance and expected value in reward outcome. Notably, participants were never required to look at the colored distractor, and doing so would slow their response to the target. Nevertheless participants often made eye-movements towards the distractor, and across both experiments they were more likely to look at distractors associated with high outcome variance versus low outcome variance. This pattern was observed when all distractors had equal expected value (Experiment 1), and when the difference in variance was opposed by a substantial difference in expected value (i.e., the high-variance distractor had low expected value, and vice versa: Experiment 2). Our results suggest that reward variance exerts a critical role in modulating rapid attentional and oculomotor priority. More generally, these findings are consistent with theoretical accounts that propose an information-seeking role for visual attention, and suggest that prioritization in line with “attentional exploration” can operate rapidly and on a learned basis.

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“…A number of influential new theories of attention have highlighted the need to integrate selection history into models of dynamic attentional priority (Awh et al, 2012; Chelazzi et al, 2019; Liesefeld & Müller, 2019; Pearson et al, 2022; Theeuwes et al, 2022). The current results advance this project by providing a novel method of visualizing the history-mediated layer of the attentional priority map while also suggesting the neural mechanisms underlying such latent biases.…”

Section: Discussionmentioning

confidence: 99%

Pinging the brain to reveal the hidden attentional priority map using encephalography

Duncan

Moorselaar

Theeuwes

2022

Preprint

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Priority maps are winner-take-all neural mechanisms that are thought to guide the allocation of attention. Within these maps, attentional priority is coded as weights on a topographic representation of physical space. Research has shown that these weights are not just influenced by the current stimuli presented but also by selection episodes that occurred in the past – called selection history. The current study demonstrates, for the first time, that these latent, implicitly-learned spatial biases can be visualized by ‘pinging’ the brain (a technique previously used to study activity-silent working memory). By briefly flashing high-contrast, task-irrelevant visual stimuli in the inter-stimulus interval between searches, participants’ current history-trained latent attentional priority could be decoded via scalp encephalography. Our findings not only offer a novel method of visualizing this latent attentional priority map, but also shed light on the underlying mechanisms allowing our past experiences to influence future behaviour.

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Attentional economics links value-modulated attentional capture and decision-making

Cited by 24 publications

References 220 publications

Reward-driven and memory-driven attentional biases automatically modulate rapid choice

Reward-driven and memory-driven attentional biases automatically modulate rapid choice

Uncertainty-modulated attentional capture: Outcome variance increases attentional priority

Pinging the brain to reveal the hidden attentional priority map using encephalography

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