Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation

• Published in: PLoS computational biology 2015-03, Vol.11 (3), p.e1004116-e1004116
• Main Authors: Klein-Flügge, Miriam C, Kennerley, Steven W, Saraiva, Ana C, Penny, Will D, Bestmann, Sven
• Format: Article
• Language: English
• Subjects: Accuracy; Adult; Behavior; Choice Behavior - physiology; Computational Biology; Costs; Decision making; Economic models; Experiments; Female; Hand Strength - physiology; Human behavior; Humans; Impulsivity; Male; Mathematical models; Models, Biological; Parameter estimation; Reward; Schizophrenia; Task Performance and Analysis; Young Adult
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1004116

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.