Getting a Grip on Cognitive Flexibility

Braem, Senne; Egner, Tobias

doi:10.1177/0963721418787475

Cited by 186 publications

(161 citation statements)

References 41 publications

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“…These findings are consistent with a number of previous observations indicating that abstract goals or cognitive control functions can bind to contextual features in our environment, allowing for the recruitment of these functions upon contextual demand (Abrahamse et al, 2016). A more recent line of studies also extended this observation to the domain of "cognitive flexibility"the ability to quickly reconfigure our task sets to meet new goals (for a review, see Braem & Egner, 2018). For example, in a design where specific task items were associated to more task switches than others, Chiu and Egner (2017) demonstrated that the efficiency with which one switches between tasks (as measured by the task switch cost) is modulated by the degree to which the current item is associated to "the act of task switching".…”

Section: Discussionsupporting

confidence: 89%

“…More recently, Whitehead, Pfeuffer, and Egner (2020) showed this learning of stimulusflexibility associations can even occur after a single instance of experiencing a given stimulus under task repetition versus task switching conditions. The present study further extends this idea that cognitive flexibility can be regulated by the context, by showing context-specific cognitive flexibility under conditions where people do not just have to alternate between two or three tasks (Chiu and Egner, 2017;Whitehead et al, 2020), but between many new tasks, consistent with the idea of regulating a general updating threshold (Braem & Egner, 2018;Dreisbach & Fröber, 2018;Goschke, 2003;Goschke & Bolte, 2014).…”

Section: Discussionsupporting

confidence: 83%

“…associative learning or reinforcement learning mechanisms (Abrahamse et al, 2016;Braem & Egner, 2018;Chiu & Egner, 2019;Egner, 2014;Eisenreich et al, 2017;Lieder et al, 2018;Verguts & Notebaert, 2008). By learning that certain control funtions are applied more (or more valuable) in certain environments than others, these control functions become associated in memory with contextual features that characterize those environments.…”

mentioning

confidence: 99%

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Learning when to learn: Context-specific instruction encoding

Braem

Xu²,

Liefooghe³

et al. 2020

Preprint

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Humans are very efficient at learning new behaviors through verbal instructions, bypassing the need for trial-and-error learning. However, we encounter a plethora of instructions in daily life, which raises the question how people can quickly determine when to rely on certain instructions, and how strongly. Recent theories emphasize that abstract functions of cognition can be (up)regulated by contextual features in our environment with which they are associated. Here, we tested whether the act of encoding a new task instruction can be enhanced in contexts where one frequently learns new task instructions. Specifically, participants had to encode and execute several new task instructions, but were more likely to encounter a new (relative to old) task instruction when the instruction was presented above or below the center of the screen (Experiment 1) or in a blue or green font (Experiment 2). The results show that retaining new task instructions interfered more with secondary task performance (which is suggestive of stronger task representations), when these mappings were instructed in contexts where one is more used to seeing new task instructions. Similarly, the results showed that participants were also faster to encode new instructions in these contexts. Finally, a post-hoc analysis indicated that, over time, participants were also faster to execute new instructions in contexts where they are more used to execute new instructions. Together, these findings suggest that the encoding (and execution) of new task instructions can bind to a specific context, providing a (self-)regulating mechanism for cognitive control processes like instruction encoding.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 83%

mentioning

confidence: 99%

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Learning when to learn: Context-specific instruction encoding

Braem

Xu²,

Liefooghe³

et al. 2020

Preprint

Self Cite

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show abstract

“…In fact, the distinction between inhibitory control, working memory, and cognitive flexibility that Heyes relies on has also been partly challenged by the very authors who originally introduced this distinction (Friedman & Miyake 2017). Therefore, there is increasing evidence that executive functions are highly contextualized and "sticky" (Mayr & Bryck 2005), which we take as a strong hint that they might be grounded in associative learning (Abrahamse et al 2016;Braem & Egner 2018;Egner 2014). This makes executive functions ideally suited to develop through social communication and transfer to meet contextual and cultural demands (Hommel & Colzato 2017).…”

Section: Open Peer Commentarymentioning

confidence: 99%

Imitation: Neither instinct nor gadget, but a cultural starting point?

Powell

2019

Behav Brain Sci

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“…Cognitive flexibility is suboptimal compared to behaviours that require less flexible processing (Kleinsorge & Rinkenauer, 2012;Shen & Chun, 2011) but can be improved by motivational factors, such as the prospect of reward for fast and accurate performance (Braem & Egner, 2018). When the prospect of reward is high, performance improves on flexible rule-based tasks (Etzel et al, 2016;Kleinsorge & Rinkenauer, 2012), suggesting that reward might optimise cognitive flexibility by tuning rule-based neural coding patterns.…”

Section: Introductionmentioning

confidence: 99%

Reward boosts neural coding of task rules to optimise cognitive flexibility

Hall-McMaster

Muhle-Karbe

Myers

et al. 2019

Preprint

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Cognitive flexibility is critical for intelligent behaviour. However, its execution is effortful and often suboptimal. Recent work indicates that flexible behaviour can be improved by the prospect of reward, suggesting that rewards optimise flexible control processes. Here we investigated how different reward prospects influence neural encoding of task rule information to optimise cognitive flexibility. We applied representational similarity analysis (RSA) to human electroencephalograms, recorded while participants performed a rule-guided decision-making task. During the task, the prospect of reward varied from trial to trial. Participants made faster, more accurate judgements on high reward trials. Critically, high reward boosted neural coding of the active task rule and the extent of this increase was associated with improvements in task performance. These results suggest that reward motivation can improve cognitive performance by strengthening neural coding of task rule information, improving cognitive flexibility during complex behaviour. Significance StatementThe importance of motivation is evident in the ubiquity with which reward prospect guides adaptive behaviour and the striking number of neurological conditions where motivation is impaired. In this study, we investigated how dynamic changes in motivation, as manipulated through reward, shape neural coding for task rules during a flexible decision-making task. The results of this work suggest that motivation to obtain reward modulates encoding of task rules needed for flexible behaviour.The extent to which reward increased task rule coding also tracked improvements in behavioural performance under high reward conditions. These findings help inform how motivation shapes neural processing in the healthy human brain.

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Getting a Grip on Cognitive Flexibility

Cited by 186 publications

References 41 publications

Learning when to learn: Context-specific instruction encoding

Learning when to learn: Context-specific instruction encoding

Imitation: Neither instinct nor gadget, but a cultural starting point?

Reward boosts neural coding of task rules to optimise cognitive flexibility

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