There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity.
One of the main functions of the brain is to select sequences of actions that lead to rewarding outcomes (e.g., food). However, such rewards are often not readily available; instead physical effort may be required to obtain them, or their arrival may be delayed. The ability to integrate the costs and benefits of potential courses of action is severely impaired in several common disorders, such as depression and schizophrenia. Mathematical models can describe how individuals depreciate rewards based on the costs associated with them. For example, models of how a reward loses appeal with increasing temporal delays can provide individual impulsivity scores, and can serve as a predictor of financial mismanagement. To date, there is no established model to describe accurately how humans depreciate rewards when obtaining them requires physical effort. This is surprising given the prevalence of disorders related to a diminished willingness to exert effort. Here we derive a biologically plausible mathematical model that can describe how healthy humans make decisions tied to physical efforts. We show that effort and delay influence reward valuation in different ways, contrary to common assumptions. Our model will be important for characterizing decision-making deficits in clinical disorders characterized by behavioral inactivity.