Motor planning flexibly optimizes performance under uncertainty about task goals

Aaron L. Wong () and Adrian M. Haith
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Aaron L. Wong: Johns Hopkins University School of Medicine
Adrian M. Haith: Johns Hopkins University School of Medicine

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract In an environment full of potential goals, how does the brain determine which movement to execute? Existing theories posit that the motor system prepares for all potential goals by generating several motor plans in parallel. One major line of evidence for such theories is that presenting two competing goals often results in a movement intermediate between them. These intermediate movements are thought to reflect an unintentional averaging of the competing plans. However, normative theories suggest instead that intermediate movements might actually be deliberate, generated because they improve task performance over a random guessing strategy. To test this hypothesis, we vary the benefit of making an intermediate movement by changing movement speed. We find that participants generate intermediate movements only at (slower) speeds where they measurably improve performance. Our findings support the normative view that the motor system selects only a single, flexible motor plan, optimized for uncertain goals.

Date: 2017
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DOI: 10.1038/ncomms14624

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