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Choice behaviour and model predictions. (a,b) Single participant choice behaviour. Frequency of choosing the lottery based on objective effort cost (a) and probability (b). Solid lines represent observed decision behaviour. Dashed lines represent model predictions based on fitted CPT parameters for SV model. (c,d) Frequency of choosing the lottery with increasing effort (c) and probability (d ). (c) When collapsed across all probabilities, increasing effort led to a decreased frequency of the group choosing the lottery (filled circles, observed group mean). Predicted frequencies based on the fitted parameters of the SV model were able to successfully capture these preferences (empty circles, mean model predictions). (d ) When collapsed across all effort levels, increasing probability of performing the lottery resulted in a decreased frequency of the group choosing that lottery. While the frequency of choosing the lottery tended to decrease with increases in either cost, the shape of these individual curves varied across individuals (coloured lines, observed behaviours of each individual).

Choice behaviour and model predictions. (a,b) Single participant choice behaviour. Frequency of choosing the lottery based on objective effort cost (a) and probability (b). Solid lines represent observed decision behaviour. Dashed lines represent model predictions based on fitted CPT parameters for SV model. (c,d) Frequency of choosing the lottery with increasing effort (c) and probability (d ). (c) When collapsed across all probabilities, increasing effort led to a decreased frequency of the group choosing the lottery (filled circles, observed group mean). Predicted frequencies based on the fitted parameters of the SV model were able to successfully capture these preferences (empty circles, mean model predictions). (d ) When collapsed across all effort levels, increasing probability of performing the lottery resulted in a decreased frequency of the group choosing that lottery. While the frequency of choosing the lottery tended to decrease with increases in either cost, the shape of these individual curves varied across individuals (coloured lines, observed behaviours of each individual).

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Economists have known for centuries that to understand an individual's decisions, we must consider not only the objective value of the goal at stake, but its subjective value as well. However, achieving that goal ultimately requires expenditure of effort. Surprisingly, despite the ubiquitous role of effort in decision-making and movement, we curren...

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Context 1
... the lottery option, we varied the value of the reach probability and effort levels using combinations of one of the five resistances in combination with one of five probabilities (53%, 63%, 72%, 84%, 95%), for a total of 25 lottery combinations, repeated 6 times for a total of 150 trials. As the level of effort and/or probability increased in the lottery option, participants were more likely to choose the reference option, confirming that participants were considering both effort and probability when making their decisions (Effort: figure 3a,c, β = 0.00013, Probability: figure 3b,d, β = 1.19, p's < 0.001). ...
Context 2
... the lottery option, we varied the value of the reach probability and effort levels using combinations of one of the five resistances in combination with one of five probabilities (53%, 63%, 72%, 84%, 95%), for a total of 25 lottery combinations, repeated 6 times for a total of 150 trials. As the level of effort and/or probability increased in the lottery option, participants were more likely to choose the reference option, confirming that participants were considering both effort and probability when making their decisions (Effort: figure 3a,c, β = 0.00013, Probability: figure 3b,d, β = 1.19, p's < 0.001). ...
Context 3
... to the behavioural data, as the effort cost of the lottery increased, the frequency of the model choosing the lottery decreased (β = 0.00012, p < 0.001; figure 3a,c). Also, as the probability of having to perform the lottery increased, the frequency of the model choosing the lottery decreased (β = 1.133, p < 0.001; figure 3b,d). Model-predicted choices were indistinguishable from actual choice data (linear mixed effects model, Effort: p = 0.742, Probability: p = 0.695). ...
Context 4
... the lottery option, we varied the value of the reach probability and effort levels using combinations of one of the five resistances in combination with one of five probabilities (53%, 63%, 72%, 84%, 95%), for a total of 25 lottery combinations, repeated 6 times for a total of 150 trials. As the level of effort and/or probability increased in the lottery option, participants were more likely to choose the reference option, confirming that participants were considering both effort and probability when making their decisions (Effort: figure 3a,c, β = 0.00013, Probability: figure 3b,d, β = 1.19, p's < 0.001). ...
Context 5
... the lottery option, we varied the value of the reach probability and effort levels using combinations of one of the five resistances in combination with one of five probabilities (53%, 63%, 72%, 84%, 95%), for a total of 25 lottery combinations, repeated 6 times for a total of 150 trials. As the level of effort and/or probability increased in the lottery option, participants were more likely to choose the reference option, confirming that participants were considering both effort and probability when making their decisions (Effort: figure 3a,c, β = 0.00013, Probability: figure 3b,d, β = 1.19, p's < 0.001). ...
Context 6
... to the behavioural data, as the effort cost of the lottery increased, the frequency of the model choosing the lottery decreased (β = 0.00012, p < 0.001; figure 3a,c). Also, as the probability of having to perform the lottery increased, the frequency of the model choosing the lottery decreased (β = 1.133, p < 0.001; figure 3b,d). Model-predicted choices were indistinguishable from actual choice data (linear mixed effects model, Effort: p = 0.742, Probability: p = 0.695). ...

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Article
How the brain determines the vigor of goal-directed movements is a fundamental question in neuroscience. Recent evidence has suggested that vigor results from a trade-off between a cost related to movement production (cost of movement) and a cost related to our brain's tendency to temporally discount the value of future reward (cost of time). However, whether it is critical to hypothesize a cost of time to explain the vigor of basic reaching movements with intangible reward is unclear because the cost of movement may be theoretically sufficient for this purpose. Here we directly address this issue by designing an isometric reaching task whose completion can be accurate and effortless in prefixed durations. The cost of time hypothesis predicts that participants should be prone to spend energy to save time even if the task can be accomplished at virtually no motor cost. Accordingly, we found that all participants generated substantial amounts of force to invigorate task accomplishment, especially when the prefixed duration was long enough. Remarkably, the time saved by each participant was linked to their original vigor in the task and predicted by an optimal control model balancing out movement and time costs. Taken together, these results supports the existence of an idiosyncratic, cognitive cost of time that underlies the invigoration of basic isometric reaching movements.