Decision making in action planning and control

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Real-world action tasks involve a sequence of decision-making processes that determine, based on information extracted during the unfolding task, which movement to make next and when to make it. However, research on movement control and decision-making has largely evolved in isolation, and it is only recently that researchers have begun to examine the interplay between them. The broad aim of the proposed research is to better understand how the brain controls action by investigating decision-making processes in the context of human target-directed reaching tasks. The proposed research consists of four interrelated projects.Whereas most studies of reaching have focused on movements made to single targets, in the real world we are often confronted with multiple potential targets of action. The aim of PROJECT 1 is to investigate how the brain prepared a reaching movement under these conditions of target uncertainty. Recent work has shown that during reach preparation, the brain encodes multiple potential targets and that the initial direction of reaches initiated before the target is specified, is biased by the distribution of potential targets. These results are consistent with the idea that multiple reach plans to potential target are prepared but are also consistent with the notion that, in cases of target uncertainty, people plan a single reach in a strategic direction. We will critically test between these alternatives.Many natural tasks involve choosing a sequence of targets from alternatives at each step and optimal foraging theory provides a natural framework for examining how rewards and costs associated with different targets, or target sequences, influence target choice behaviour. Although a handful of studies have examined how values and cost influence the selection of single targets, to our knowledge no study has investigated sequential target selection. PROJECT 2 will investigate decision-making related to sequential target selection using a movement foraging task that we have recently developed.People are frequently confronted with decisions about whether it is worthwhile investing in learning a new skill, based on an evaluation of the costs and rewards associated with learning. However, to our knowledge such decision-making related to skill learning has not been quantitatively studied. PROJECT 3 will investigate the interaction between learning and reward optimization using reaching tasks in which participants can choose whether to engage in motor learning, which will ultimately enable them to obtain higher value rewards. A key aim is to assess participants’ ability to use knowledge about their own ability to learn new skills to make good decisions about whether to invest in such learning.Studies of action-observation have shown that observers extract information about the actor’s goals. However, no research has examined whether, when watching action tasks involving decision-making, observers extract potentially valuable information that guides the actor’s choices. We have previously shown that observers direct their gaze to the target of an actor’s movement as soon as they can predict the target. In PROJECT 4, we will record observer’s eye movements to test whether they learn to predict an actor’s choice behaviour when selecting reach targets, suggesting the observer may extract the values and costs that the actor associates with the targets.