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Motor planning flexibly optimizes performance under uncertainty about task goals

Author

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  • Aaron L. Wong

    (Johns Hopkins University School of Medicine)

  • Adrian M. Haith

    (Johns Hopkins University School of Medicine)

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.

Suggested Citation

  • Aaron L. Wong & Adrian M. Haith, 2017. "Motor planning flexibly optimizes performance under uncertainty about task goals," Nature Communications, Nature, vol. 8(1), pages 1-10, April.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms14624
    DOI: 10.1038/ncomms14624
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    Cited by:

    1. Ryoji Onagawa & Kae Mukai & Kazutoshi Kudo, 2022. "Different planning policies for the initial movement velocity depending on whether the known uncertainty is in the cursor or in the target: Motor planning in situations where two potential movement di," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-19, March.

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