Policy abstraction as a predictor of cognitive effort avoidance.

Sayalı, Ceyda; Rubin-McGregor, Jordan; Badre, David

doi:10.1037/xge0001449

Cited by 5 publications

(4 citation statements)

References 56 publications

(118 reference statements)

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“…However, we show that WM load was only minimally costly and that updating and interference had a greater influence on subjective cognitive effort. Other work has shown that WM maintenance demands minimally influence cognitive effort avoidance behavior [ 17 ] and do not evoke task performance costs [ 35 ]. Lure stimuli in WM storage demand an accurate maintenance of both stimulus identity and stimulus order.…”

Section: Discussionmentioning

confidence: 99%

“…Tasks which subjects demanded the most incentives to complete [ 5 – 7 ] or which subjects tended to avoid in favor of other tasks with equivalent rewards [ 4 , 8 , 9 ] are considered most effortful. Some costly aspects of these tasks are external, like time on task [ 10 – 12 ] or the complexity of the cognitive model required by the task [ 13 – 16 ], but other costs arise from the internal operations necessary to realize external actions, like the degree of hierarchical cognitive control required [ 17 ]. In general, cognitive resistance increases when tasks place substantial demands on working memory and cognitive control [ 5 , 18 – 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Wagers for work: Decomposing the costs of cognitive effort

Master,

Curtis,

Dayan

2024

PLoS Comput Biol

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Some aspects of cognition are more taxing than others. Accordingly, many people will avoid cognitively demanding tasks in favor of simpler alternatives. Which components of these tasks are costly, and how much, remains unknown. Here, we use a novel task design in which subjects request wages for completing cognitive tasks and a computational modeling procedure that decomposes their wages into the costs driving them. Using working memory as a test case, our approach revealed that gating new information into memory and protecting against interference are costly. Critically, other factors, like memory load, appeared less costly. Other key factors which may drive effort costs, such as error avoidance, had minimal influence on wage requests. Our approach is sensitive to individual differences, and could be used in psychiatric populations to understand the true underlying nature of apparent cognitive deficits.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wagers for work: Decomposing the costs of cognitive effort

Master,

Curtis,

Dayan

2024

PLoS Comput Biol

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“…At the Specific level, the number of simultaneously possible sequences is reduced to one. Therefore, each level represents a linear increment in abstraction policy: Sequence (first-order policy), Sub-Rule (second-order policy), Rule (third-order policy), and General (fourth-order policy; Sayalı et al. 2023 ).…”

Section: Methodsmentioning

confidence: 99%

Distinct neural mechanisms for action access and execution in the human brain: insights from an fMRI study

Papitto,

Friederici,

Zaccarella

2024

Cerebral Cortex

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Goal-directed actions are fundamental to human behavior, whereby inner goals are achieved through mapping action representations to motor outputs. The left premotor cortex (BA6) and the posterior portion of Broca’s area (BA44) are two modulatory poles of the action system. However, how these regions support the representation-output mapping within the system is not yet understood. To address this, we conducted a finger-tapping functional magnetic resonance imaging experiment using action categories ranging from specific to general. Our study found distinct neural behaviors in BA44 and BA6 during action category processing and motor execution. During access of action categories, activity in a posterior portion of BA44 (pBA44) decreased linearly as action categories became less specific. Conversely, during motor execution, activity in BA6 increased linearly with less specific categories. These findings highlight the differential roles of pBA44 and BA6 in action processing. We suggest that pBA44 facilitates access to action categories by utilizing motor information from the behavioral context while the premotor cortex integrates motor information to execute the selected action. This finding enhances our understanding of the interplay between prefrontal cortical regions and premotor cortex in mapping action representation to motor execution and, more in general, of the cortical mechanisms underlying human behavior.

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“…Westbrook & Braver, 2015). Several versions of the DST have been used to demonstrate that people avoid a wide range of cognitive control demands, such as response conflict (Schouppe et al, 2014), task switching (Kool et al, 2010;Sayalı & Badre, 2021), working memory maintenance (Kool et al, 2010), increasingly complex task policies (Sayalı et al, 2023), and even the exertion of empathy (Cameron et al, 2019).…”

mentioning

confidence: 99%

Humans do not avoid reactively implementing cognitive control.

Bustos,

Colvett,

Bugg

et al. 2024

Journal of Experimental Psychology: Human Perception and Perfor

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The ability to exert cognitive control allows us to achieve goals in the face of distraction and competing actions. However, control is costly-people generally aim to minimize its demands. Because control takes many forms, it is important to understand whether such costs apply universally. Specifically, reactive control, which is recruited in response to stimulus or contextual features, is theorized to be deployed automatically, and not depend on attentional resources. Here, we investigated whether people avoided implementing reactive control in three experiments. In all, participants performed a Stroop task in which certain items were mostly incongruent (MI), that is, associated with a high likelihood of conflict (triggering a focused control setting). Other items were mostly congruent, that is, associated with a low likelihood of conflict (triggering a relaxed control setting). Experiment 1 demonstrated that these control settings transfer to a subsequent unbiased transfer phase. In Experiments 2-3, we used a demand selection task to investigate whether people would avoid choice options that yielded items that were previously MI. In all, participants continued to retrieve focused control settings for previously MI items, but they did not avoid them in the demand selection task. Critically, we only found demand avoidance when there was an objective difference in demand between options. These findings are consistent with the idea that implementing reactive control does not register as costly. Public Significance StatementWhile humans use attentional control to achieve their goals and to avoid distractions, it has been theorized that it is not always deployed because of its mental costs. However, not all forms of control are equal: It has been suggested that adjusting attention in response to a stimulus may be relatively costfree. We provide a new test of this idea by integrating stimuli associated with different amounts of reactive control into a demand selection paradigm. We found that participants reactively focused their attention on items previously associated with higher demand and relaxed attention on items previously associated with lower demand. However, despite these differences in implemented control, participants did not avoid choice options associated with the previously high-demand options. This result indicates that reactively focusing attention is not costly. In addition to theoretical implications about the nature of control, these results indicate that setting up demands to rely on reactive control might substantially diminish subjective motivational and implementational constraints.

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Policy abstraction as a predictor of cognitive effort avoidance.

Cited by 5 publications

References 56 publications

Wagers for work: Decomposing the costs of cognitive effort

Wagers for work: Decomposing the costs of cognitive effort

Distinct neural mechanisms for action access and execution in the human brain: insights from an fMRI study

Humans do not avoid reactively implementing cognitive control.

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