Skip to Main content Skip to Navigation
Journal articles

Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks

Abstract : A standard view in neuroeconomics is that to make a choice, an agent first assigns subjective values to available options, and then compares them to select the best. In choice tasks, these cardinal values are typically inferred from the preference expressed by subjects between options presented in pairs. Alternatively, cardinal values can be directly elicited by asking subjects to place a cursor on an analog scale (rating task) or to exert a force on a power grip (effort task). These tasks can vary in many respects: they can notably be more or less costly and consequential. Here, we compared the value functions elicited by choice, rating and effort tasks on options composed of two monetary amounts: one for the subject (gain) and one for a charity (donation). Bayesian model selection showed that despite important differences between the three tasks, they all elicited a same value function, with similar weighting of gain and donation, but variable concavity. Moreover, value functions elicited by the different tasks could predict choices with equivalent accuracy. Our finding therefore suggests that comparable value functions can account for various motivated behaviors, beyond economic choice. Nevertheless, we report slight differences in the computational efficiency of parameter estimation that may guide the design of future studies.
Document type :
Journal articles
Complete list of metadata

Cited literature [36 references]  Display  Hide  Download
Contributor : Myriam Bodescot Connect in order to contact the contributor
Submitted on : Thursday, June 6, 2019 - 11:50:42 AM
Last modification on : Thursday, May 26, 2022 - 3:57:20 AM


Publication funded by an institution



Alizée Lopez-Persem, Lionel Rigoux, Sacha Bourgeois-Gironde, Jean Daunizeau, Mathias Pessiglione. Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks. PLoS Computational Biology, Public Library of Science, 2017, 13 (11), pp.e1005848. ⟨10.1371/journal.pcbi.1005848⟩. ⟨inserm-02149305⟩



Record views


Files downloads