ArticleFrontiers in behavioral neuroscience2015
Adaptive effort investment in cognitive and physical tasks: a neurocomputational model.
Article in Frontiers in behavioral neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The neural basis of cost-benefit trade-offs in effort investment: a quantitative activation likelihood estimation meta-analysis.Cognitive, affective & behavioral neuroscience · 2026Pooled it
- Trial
- Trial
- Executive functions as a transdiagnostic endophenotype in developmental psychopathology.Molecular psychiatry · 2026Review
- A Hitchhiker's Guide to Physical and Cognitive Effort.Sports medicine (Auckland, N.Z.) · 2026Review
- Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.Psychological review · 2026Article
- Shared and distinct features of common effort-based decision-making paradigms and their relation to brain structure and neuropsychiatric conditions: An integrated narrative review.Cognitive, affective & behavioral neuroscience · 2026Review
- Meta-Reinforcement Learning reconciles surprise, value, and control in the anterior cingulate cortex.PLoS computational biology · 2025Article
- The Cost of Regulating Effort: Reward and Difficulty Cues With Longer Prediction Horizons Have a Stronger Impact on Performance.Journal of cognition · 2025Article
- Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Learning when effort matters: neural dynamics underlying updating and adaptation to changes in performance efficacy.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Worth the work? Monkeys discount rewards by a subjective adapting effort cost.bioRxiv : the preprint server for biology · 2023Article
- Distinct neural representations for prosocial and self-benefiting effort.Current biology : CB · 2022Article
- Cognitive Control as a Multivariate Optimization Problem.Journal of cognitive neuroscience · 2022Article
- Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making.Neuroscience and biobehavioral reviews · 2022Review
- Thunderstruck: The ACDC model of flexible sequences and rhythms in recurrent neural circuits.PLoS computational biology · 2022Article
- A mosaic of cost-benefit control over cortico-striatal circuitry.Trends in cognitive sciences · 2021Review
- Neural and computational mechanisms of momentary fatigue and persistence in effort-based choice.Nature communications · 2021Article
- Causal role of lateral prefrontal cortex in mental effort and fatigue.Human brain mapping · 2020Article
- Cognitive Effort Modulates Connectivity between Dorsal Anterior Cingulate Cortex and Task-Relevant Cortical Areas.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite its importance in everyday life, the computational nature of effort investment remains poorly understood. We propose an effort model obtained from optimality considerations, and a neurocomputational approximation to the optimal model. Both are couched in the framework of reinforcement learning. It is shown that choosing when or when not to exert effort can be adaptively learned, depending on rewards, costs, and task difficulty. In the neurocomputational model, the limbic loop comprising anterior cingulate cortex (ACC) and ventral striatum in the basal ganglia allocates effort to cortical stimulus-action pathways whenever this is valuable. We demonstrate that the model approximates optimality. Next, we consider two hallmark effects from the cognitive control literature, namely proportion congruency and sequential congruency effects. It is shown that the model exerts both proactive and reactive cognitive control. Then, we simulate two physical effort tasks. In line with empirical work, impairing the model's dopaminergic pathway leads to apathetic behavior. Thus, we conceptually unify the exertion of cognitive and physical effort, studied across a variety of literatures (e.g., motivation and cognitive control) and animal species.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.