You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention

Feldmann-Wüstefeld, Tobias; Uengoer, Metin; Schubö, Anna

doi:10.1111/psyp.12514

Cited by 87 publications

(110 citation statements)

References 51 publications

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“…Consistent with this idea, Le Pelley et al (2013) demonstrated that providing more time for participants to consciously process the stimuli-by increasing the SOA on dot probe trials to 1000 ms-significantly weakened the influence of predictiveness on dot probe responding. This supports the idea that the bias towards predictive cues observed in the short SOA condition was not a result of goal-directed, controlled processing but instead an automatic, rapid, and short-lived attentional process within the region of 250 milliseconds after cue-onset (for convergent evidence, see Feldmann-Wüstefeld, Uengoer, & Schubö, 2015). …”

supporting

confidence: 69%

Prediction and Uncertainty in Associative Learning: Examining Controlled and Automatic Components of Learned Attentional Biases

Luque

Vadillo

Pelley

et al. 2017

Quarterly Journal of Experimental Psychology

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It has been suggested that attention is guided by two factors that operate during associative learning: a predictiveness principle, by which attention is allocated to the best predictors of outcomes, and an uncertainty principle, by which attention is allocated to learn about the less-known features of the environment. Recent studies have shown that predictivenessdriven attention can operate rapidly and in an automatic way to exploit known relationships. The corresponding characteristics of uncertainty-driven attention, on the other hand, remain unexplored. In two experiments we examined whether both predictiveness and uncertainty modulate attentional processing in an adaptation of the dot probe task. This task provides a measure of automatic orientation to cues during associative learning. The stimulus-onset-asynchrony of the probe display was manipulated in order to explore temporal characteristics of predictiveness-and uncertainty-driven attentional effects. Results showed that the predictive status of cues determined selective attention, with faster attentional capture to predictive than to nonpredictive cues. In contrast, the level of uncertainty slowed down responses to the probe regardless of the predictive status of the cues. Both predictiveness-and uncertainty-driven attentional effects were very rapid (at 250 ms from cue onset) and automatically activated. Keywords: attention, associative learning, dot probe, predictiveness, uncertainty.Downloaded by [University of London] at 09:14 13 May 2016 3 Visual attention determines which stimuli are preferentially processed. It allows for the focusing of limited cognitive resources on important aspects of the environment, to the detriment of processing less important information. Thus, in order to understand our cognitive system, it is crucial to investigate which factors modulate this selection process.These factors are usually divided into two mutually exclusive functional categories according to whether attentional modulation is caused by physical characteristics of the stimuli (i.e., stimulus-driven modulation) or is caused by cognitive factors such as goal-directed intentions or motivations (i.e., goal-directed modulation) (e.g., Corbetta & Shulman, 2002;Yantis, 2000). For example, when driving we might use goal-directed, top-down attention to prioritize processing of events on the road ahead, and to ignore conversation from the backseat. But a physically salient event (e.g., a sudden bang from behind the car) will capture our attention in an bottom-up, stimulus-driven fashion regardless of our goals (e.g., Theeuwes, 1992;Folk, Remington, & Johnston, 1992).However, it has recently been argued that there is a third category of influences on attentional selection that is neither fully goal-directed nor stimulus-driven, and which comes into play when people have had previous experience with stimuli. Specifically, it has been suggested that our attention is influenced by what we have learned about how stimuli relate to other events in the environment (...

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supporting

confidence: 69%

Prediction and Uncertainty in Associative Learning: Examining Controlled and Automatic Components of Learned Attentional Biases

Luque

Vadillo

Pelley

et al. 2017

Quarterly Journal of Experimental Psychology

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“…However, no difference was found between participants that were aware and unaware of the reward assignment. Thirdly, the N D and P D observed for distractors resembled in shape and timing of N D and P D components that were found in similar paradigms in which no reward or other incentive was used to render salient distractors objects of potential interest (Feldmann‐Wüstefeld & Schubö, ; Feldmann‐Wüstefeld, Uengoer, & Schubö, ). In sum, it seems that voluntary attention deployment in a top‐down manner toward rewarded distractors may not explain the present pattern of results, and neither do differences in bottom‐up processing (as colors were counterbalanced across participants).…”

Section: Discussionmentioning

confidence: 79%

Rewarded visual items capture attention only in heterogeneous contexts

2016

Self Cite

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Reward is known to affect visual search performance. Rewarding targets can increase search performance, whereas rewarding distractors can decrease search performance. We used subcomponents of the N2pc in the event-related EEG, the NT (target negativity) and ND /PD (distractor negativity/positivity), in a visual search task to disentangle target and distractor processing related to reward. The visual search task comprised homogeneous and heterogeneous contexts in which a target and a colored distractor were embedded. After each correct trial, participants were given a monetary reward that depended on the color of the distractor. We found longer response times for displays with high-reward distractors compared to displays with low-reward distractors, indicating reward-induced interference, however, only for heterogeneous contexts. The NT component, indicative of attention deployment to the target, showed that target selection was impaired by high-reward distractors, regardless of the context homogeneity. Processing of distractors was not affected by reward in homogeneous contexts. In heterogeneous contexts, however, high-reward distractors were more likely to capture attention (ND ) and required more effort to be suppressed (PD ) than low-reward distractors. In sum the results showed that, despite the fact that target selection is impaired by high-reward distractors in both homogeneous and heterogeneous background contexts, high-reward distractors capture attention only in scenarios that foster attentional capture.

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“…This fast suppression is consistent with recent studies that claimed that suppression of salient singletons in the additional singleton task can be feature-based (Gaspelin, Leonard, & Luck, 2015; Moher & Egeth, 2012; Sawaki & Luck, 2010; Vatterott & Vecera, 2012). Such fast suppression can also take place at the level of whole perceptual dimensions (Feldmann-Wüstefeld, Uengoer, & Schubö, 2015). Alternatively, the results from Experiment 2 could reflect the unresolved conflict between reward- and goal-driven attentional biases, possibly resulting in an impaired performance at the ISI 100-ms condition for both reward- and goal-congruent trials.…”

Section: Discussionmentioning

confidence: 99%

Mixed signals: The effect of conflicting reward- and goal-driven biases on selective attention

Preciado

Munneke

Theeuwes

2017

Atten Percept Psychophys

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Attentional selection depends on the interaction between exogenous (stimulus-driven), endogenous (goal-driven), and selection history (experience-driven) factors. While endogenous and exogenous biases have been widely investigated, less is known about their interplay with value-driven attention. The present study investigated the interaction between reward-history and goal-driven biases on perceptual sensitivity (d’) and response time (RT) in a modified cueing paradigm presenting two coloured cues, followed by sinusoidal gratings. Participants responded to the orientation of one of these gratings. In Experiment 1, one cue signalled reward availability but was otherwise task irrelevant. In Experiment 2, the same cue signalled reward, and indicated the target’s most likely location at the opposite side of the display. This design introduced a conflict between reward-driven biases attracting attention and goal-driven biases directing it away. Attentional effects were examined comparing trials in which cue and target appeared at the same versus opposite locations. Two interstimulus interval (ISI) levels were used to probe the time course of attentional effects. Experiment 1 showed performance benefits at the location of the reward-signalling cue and costs at the opposite for both ISIs, indicating value-driven capture. Experiment 2 showed performance benefits only for the long ISI when the target was at the opposite to the reward-associated cue. At the short ISI, only performance costs were observed. These results reveal the time course of these biases, indicating that reward-driven effects influence attention early but can be overcome later by goal-driven control. This suggests that reward-driven biases are integrated as attentional priorities, just as exogenous and endogenous factors.

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You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention

Cited by 87 publications

References 51 publications

Prediction and Uncertainty in Associative Learning: Examining Controlled and Automatic Components of Learned Attentional Biases

Prediction and Uncertainty in Associative Learning: Examining Controlled and Automatic Components of Learned Attentional Biases

Rewarded visual items capture attention only in heterogeneous contexts

Mixed signals: The effect of conflicting reward- and goal-driven biases on selective attention

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