Reward modulates adaptations to conflict

Braem, Senne; Verguts, Tom; Roggeman, Chantal; Notebaert, Wim

doi:10.1016/j.cognition.2012.07.015

Cited by 136 publications

(205 citation statements)

References 38 publications

Supporting

Mentioning

179

Contrasting

Order By: Relevance

“…In the Stroop task, when the colour of the word and its meaning do not correspond, interference from word meaning is selectively reduced for highly rewarded colours (Krebs, Boehler, & Woldorff, 2010). Similar effects have been reported in flanker and task-switching tasks (Braem, Verguts, Roggeman, & Notebaert, 2012), as well as the Simon task (Sturmer, Nigbur, Schacht, & Sommer, 2011), all classical indexes of cognitive control.…”

Section: Learning To Attend: Effects Of Predictiveness On Perception supporting

confidence: 58%

Automaticity and cognitive control in the learned predictiveness effect.

Shone¹,

Harris²,

Livesey³

2015

Journal of Experimental Psychology: Animal Learning and Cogniti

View full text Add to dashboard Cite

In novel contexts, learning is biased toward cues previously experienced as predictive compared with cues previously experienced as nonpredictive. This is known as learned predictiveness. A recent finding has shown that instructions issued about the causal status of cues influences the expression of learned predictiveness, suggesting that controlled, volitional processes play a role in this effect. Three experiments are reported further investigating the effects of instructional manipulations on learned predictiveness. Experiment 1 confirms the influence of inferential processes, extending previous work to suggest that instructions affect associative memory as well as causal reasoning. Experiments 2 and 3 used a procedure designed to tease apart inferential and automatic contributions to the bias by presenting instructed causes that were previously predictive and previously nonpredictive. The results demonstrate that the prior predictiveness of cues influences subsequent learning over and above the effect of explicit instruction. However, it appears that the relationship between explicit instruction and predictive history is interactive rather than additive. Potential explanations for this interactivity are discussed.

show abstract

Section: Learning To Attend: Effects Of Predictiveness On Perception supporting

confidence: 58%

Automaticity and cognitive control in the learned predictiveness effect.

Shone¹,

Harris²,

Livesey³

2015

Journal of Experimental Psychology: Animal Learning and Cogniti

View full text Add to dashboard Cite

show abstract

“…The Expected Value of Control (EVC) theory maintains that the brain therefore specifies how much control to exert according to a rational cost-benefit analysis, weighing these effort costs against attendant rewards for achieving one's goals [7]. In broad accord with the predictions of the EVC theory, previous research has found that control specification is context-sensitive [8,9] and modulated by reward across multiple domains [10,11], such as attention, response inhibition, interference control, and task switching. While previous theories account for that fact that people's performance in these task is sensitive to reward [7,[12][13][14], it remains unclear how these dependencies arise from people's experience.…”

Section: Introductionmentioning

confidence: 56%

“…For instance, it has been demonstrated that participants in visual search tasks gradually learn to allocate their attention to locations whose features predict the appearance of a target [17], and a recent study found that learning continuously adjusts how much cognitive control people exert in a Stroop task with changing difficulty [18]. Furthermore, it has been shown that people learn to exert more cognitive control after their performance on a controldemanding task was rewarded [10] and learn to exert more control in response to potentially control-demanding stimuli that are associated with reward than to those that are not [11].…”

Section: Introductionmentioning

confidence: 99%

Rational metareasoning and the plasticity of cognitive control

Lieder¹,

Shenhav²,

Musslick³

et al. 2017

Preprint

View full text Add to dashboard Cite

The human brain has the impressive capacity to adapt how it processes information to highlevel goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people's ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure. Author summaryThe human brain has the impressive ability to adapt how it processes information to high level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we derive a computational model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert from a formal theory of the function of cognitive control. Across five experiments, we find that our model correctly predicts that people learn to adaptively regulate their attention and decision- Funding: This research was supported by the Office of Naval Research through Grant No. MURI N00014-13-1-0431 to TLG. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests:The authors have declared that no competing interests exist.making and how these learning effects transfer to novel situations. Our findings elucidate how learning and experience might shape people's ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure.

show abstract

“…Interestingly, the authors demonstrated that correct performance on incongruent, relative to congruent, trials led to a significant benefit in reaction times for the evaluation of positive, relative to negative, words. Similarly, the authors predicted and interpreted this finding by suggesting that people find it more positively surprising to solve a difficult than an easy task (for a similar reasoning, see Alessandri, Darcheville, Delevoye-Turrell, & Zentall, 2008;Braem, Verguts, Roggeman, & Notebaert, 2012;Satterthwaite et al, 2012).…”

Section: Discussionmentioning

confidence: 97%

Open your eyes for prediction errors

Braem

Coenen

Bombeke

et al. 2015

Cogn Affect Behav Neurosci

Self Cite

View full text Add to dashboard Cite

Previous studies have demonstrated that autonomic arousal is increased following correct task performance on a difficult, relative to an easy, task. Here, we hypothesized that this arousal response reflects the (relative) surprise of correct performance following a difficult versus an easy task. Following this line of reasoning, we would expect to find a reversed pattern following erroneous responses, because errors are less expected during an easy than during a difficult task. To test this, participants performed a flanker task while pupil size was measured online. As predicted, the results demonstrated that pupil size was larger following difficult (incongruent) correct trials than following easy (congruent) correct trials, but smaller following difficult than following easy incorrect trials. Moreover, participants with larger congruency effects, and hence a larger difference in outcome expectancies between the two trial types, showed larger differences in pupil size after both correct and incorrect responses, further corroborating the idea that pupil size increased as a measure of performance prediction errors.

show abstract

Reward modulates adaptations to conflict

Cited by 136 publications

References 38 publications

Automaticity and cognitive control in the learned predictiveness effect.

Automaticity and cognitive control in the learned predictiveness effect.

Rational metareasoning and the plasticity of cognitive control

Open your eyes for prediction errors

Contact Info

Product

Resources

About