title: Motor planning under temporal uncertainty is suboptimal when the gain function is asymmetric.
abstract: For optimal action planning, the gain/loss associated with actions and the variability in motor output should both be considered. A number of studies make conflicting claims about the optimality of human action planning but cannot be reconciled due to their use of different movements and gain/loss functions. The disagreement is possibly because of differences in the experimental design and differences in the energetic cost of participant motor effort. We used a coincident timing task, which requires decision making with constant energetic cost, to test the optimality of participant's timing strategies under four configurations of the gain function. We compared participant strategies to an optimal timing strategy calculated from a Bayesian model that maximizes the expected gain. We found suboptimal timing strategies under two configurations of the gain function characterized by asymmetry, in which higher gain is associated with higher risk of zero gain. Participants showed a risk-seeking strategy by responding closer than optimal to the time of onset/offset of zero gain. Meanwhile, there was good agreement of the model with actual performance under two configurations of the gain function characterized by symmetry. Our findings show that human ability to make decisions that must reflect uncertainty in one's own motor output has limits that depend on the configuration of the gain function.
authors.affiliation: Laboratory of Sports Sciences, Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo Tokyo, Japan ; Research Fellow of Japan Society for the Promotion of Science Tokyo, Japan.
authors.forename: Keiji
authors.initials: K
authors.lastname: Ota
authors.affiliation: Laboratory of Sports Sciences, Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo Tokyo, Japan.
authors.forename: Masahiro
authors.initials: M
authors.lastname: Shinya
authors.affiliation: Laboratory of Sports Sciences, Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo Tokyo, Japan.
authors.forename: Kazutoshi
authors.initials: K
authors.lastname: Kudo
keywords: Bayesian decision model; coincident timing task; decision making; response variance; risk-sensitivity