Motor Plans under Uncertainty Reflect a Trade-Off between Maximizing Reward and Success

Abstract

When faced with multiple potential movement options, individuals either reach directly to one of the options, or initiate a reach intermediate between the options. It remains unclear why people generate these two types of behaviors. Using the go-before-you-know task (commonly used to study behavior under choice uncertainty) in humans, we examined two key questions. First, do these two types of responses actually reflect distinct movement strategies? If so, the relative desirability (i.e., weighing the success likelihood vs the attainable reward) of the two target options would not need to be computed identically for direct and intermediate reaches. We showed that indeed, when reward and success likelihood differed between the two options, reach direction was preferentially biased toward different directions for direct versus intermediate reaches. Importantly, this suggests that the computation of subjective values depends on the choice of movement strategy. Second, what drives individual differences in how people respond under uncertainty? We found that risk/reward-seeking individuals tended to generate more intermediate reaches and were more responsive to changes in reward, suggesting these movements may reflect a strategy to maximize reward versus success. Together, these findings suggest that when faced with choice uncertainty, individuals adopt movement strategies consistent with their risk/reward attitude, preferentially biasing behavior toward exogenous rewards or endogenous success and consequently modulating the relative desirability of the available options.

Allocation of visuospatial attention indexes evidence accumulation for reach decisions

“…We first extend the delayed-cueing paradigm to hand reaches and demonstrate that the gradual increase of visuospatial attention and its distribution across relevant locations is a general computational principle across effector systems. We then show that the probability with which a given target will later become the instructed movement goal -a variable known to affect decision-making (Platt and Glimcher, 1999;Ratcliff et al, 1999;Hudson et al, 2007;Wong et al, 2022) -modulates both the spatiotemporal characteristics of attentional allocation and reach behavior, indicating that top-down information about upcoming actions alters attentional prioritization. Finally, we bridge attentional and motor aspects by fitting a sequential sampling model of decisionmaking to the movement data.…”