ArticleCognitive, affective & behavioral neuroscience2026
Motivation to exert effort dynamically adapts to reward context and environmental controllability.
Article in Cognitive, affective & behavioral neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Working hard to pursue our dreams should get us there sooner or later. However, no matter how hard we try, sometimes, things are simply beyond our control, and our efforts may even be detrimental. Swiftly adapting our efforts to the controllability of the environment is a critical skill that is impaired in many neuropsychiatric disorders. Yet, how exactly we calibrate our efforts to the controllability and the richness of the environment (i.e., the overall amount of reward available in the current context) remains largely unexplored. We developed the novel Controllability and Mental Effort Task (CoMET) to investigate how varying controllability and reward context impact the motivation to exert effort for reward (n = 61). Importantly, we tested the impact of controllability while controlling for average reward rate. As hypothesized, participants were more willing to exert effort in controllable environments than in uncontrollable ones and adjusted their decisions to exert effort dynamically as a function of varying controllability. Their willingness to exert effort was also sensitive to the reward context: in reward-poor contexts, participants engaged in more effort when the momentary reward was high. Drift Diffusion modeling of decisions to exert effort showed that controllability, high momentary reward, and low effort enhanced the value integration process with increased drift rates, and controllability specifically increased decision threshold. Interestingly, individuals with higher subclinical depression traits were more sensitive to controllability, showing diminished motivation, particularly in an uncontrollable high-reward context. Taken together, these results indicate that people dynamically track multiple environmental features and integrate them into their effort allocation strategies.
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