Toward a rational and mechanistic account of mental effort
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In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.
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Modern theories of motivation describe motivational states as the output of a computation where expected value of an action is weighed against anticipated costs (energetic, opportunity, hedonic).
“Consequently, modern theories of motivation increasingly describe motivational states as the output of a computation (calculation), where the expected value of an action is weighed against anticipated costs. These include energetic costs, as all goal pursuit will require the expenditure of metabolic energy, opportunity costs, as the pursuit of one goal might block progress towards another, hedonic”
From Motivation in the Service of Allostasis: The Role of Anterior Mid-Cingulate Cortex (2019) · cites this paper as Shenhav et al., 2017
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Can’t or Won’t? Immunometabolic Constraints on Dopaminergic Drive
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Calculated avoidance: Math anxiety predicts math avoidance in effort-based decision-making
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Rational metareasoning and the plasticity of cognitive control
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Self-citationDoing more with less: meta-reasoning and meta-learning in humans and machines
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Self-citationThe role of the opioid system in decision making and cognitive control: a review
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A model of listening engagement (MoLE)
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The Eighty Five Percent Rule for optimal learning
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Self-citationIdentifying the determinants of emotion regulation choice: a systematic review with meta-analysis
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Energizing leaders via self-reflection: A within-person field experiment.
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Widespread temporal coding of cognitive control in the human prefrontal cortex
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Self-citationTheta oscillations shift towards optimal frequency for cognitive control
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Aging Increases Prosocial Motivation for Effort
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People construct simplified mental representations to plan
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Self-citationDopamine restores cognitive motivation in Parkinson’s disease
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The exercise–cognition relationship: A virtuous circle
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Advances in modeling learning and decision-making in neuroscience
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Self-citationCognitive Control in Depression: Toward Clinical Models Informed by Cognitive Neuroscience
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Decomposing the Motivation to Exert Mental Effort
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Self-citationNeural and computational mechanisms of momentary fatigue and persistence in effort-based choice
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Outsourcing Memory to External Tools: A Review of ‘Intention Offloading’
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Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research
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Rewarding cognitive effort increases the intrinsic value of mental labor
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Measuring Cognitive Load: Are There More Valid Alternatives to Likert Rating Scales?
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Dopamine and the motivation of cognitive control
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How Outcome Uncertainty Mediates Attention, Learning, and Decision-Making
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The anterior cingulate cortex directs exploration of alternative strategies
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A resource-rational theory of set size effects in human visual working memory
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A mosaic of cost–benefit control over cortico-striatal circuitry
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Effort shapes social cognition and behaviour: A neuro-cognitive framework
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Anticipating cognitive effort: roles of perceived error-likelihood and time demands
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Predictive Smooth Pursuit Eye Movements
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Adolescent Development of Value-Guided Goal Pursuit
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An Integrative Model of Effortful Control
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The Best Laid Plans: Computational Principles of Anterior Cingulate Cortex
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Acute Psychosocial Stress Increases Cognitive-Effort Avoidance
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Worth the Effort: the Start and Stick to Desirable Difficulties (S2D2) Framework
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Linear reinforcement learning in planning, grid fields, and cognitive control
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Emotions as ComputationsPreprint
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Forced choices reveal a trade-off between cognitive effort and physical pain
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The cardinal exercise stopper: Muscle fatigue, muscle pain or perception of effort?
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Prefrontal cortex and cognitive control: new insights from human electrophysiology
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More Effort, Less Fatigue: The Role of Interest in Increasing Effort and Reducing Mental Fatigue
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- Authors
- Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M.
- Affiliations
- Brown University (US)
- Princeton University (US)
- University of California, Berkeley (US)
- Harvard University (US)
- Google DeepMind (United Kingdom) (GB)
- Corresponding author
- Shenhav, Amitai
- ORCID
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 2017-07-25
- Volume
- 40
- Issue
- 1
- Pages
- 99-124
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- OpenAlex
- W2600886565
- Cited by
- 1,077
- References
- 196
- Citations by year
- 2026: 124 · 2025: 122 · 2024: 149 · 2023: 117 · 2022: 123 · 2021: 124 · 2020: 112 · 2019: 117 · 2018: 60 · 2017: 23 · 2016: 3
- FWCI
- 9.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Life Sciences › Neuroscience › Cognitive Neuroscience › Free Will and Agency
- Keywords
- cognitive effort, cognitive control, effort cost, cognitive resource allocation, aversive experience, cognitive limitations
- MeSH terms
- Cognition, Decision Making, Humans, Motivation, Reward, Prefrontal Cortex, Executive Function
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