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Action plan co-optimization reveals the parallel encoding of competing reach movements

Author

Listed:
  • Jason P. Gallivan

    (Queen’s University
    Centre for Neuroscience Studies, Queen’s University)

  • Kathryn S. Barton

    (Queen’s University)

  • Craig S. Chapman

    (Faculty of Physical Education and Recreation, University of Alberta)

  • Daniel M. Wolpert

    (University of Cambridge)

  • J. Randall Flanagan

    (Queen’s University
    Centre for Neuroscience Studies, Queen’s University)

Abstract

Several influential cognitive theories propose that in situations affording more than one possible target of action, we prepare multiple competing movements before selecting one. Here we provide direct evidence for this provocative but largely untested idea and demonstrate why preparing multiple movements is computationally advantageous. Using a reaching task in which movements are initiated after one of two potential targets is cued, we show that the movement generated for the cued target borrows components of the movement that would have been required for the other, competing target. This interaction can only arise if multiple potential movements are fully specified in advance and we demonstrate that it reduces the time required to launch a given action plan. Our findings suggest that this co-optimization of motor plans is highly automatic and largely occurs outside conscious awareness.

Suggested Citation

  • Jason P. Gallivan & Kathryn S. Barton & Craig S. Chapman & Daniel M. Wolpert & J. Randall Flanagan, 2015. "Action plan co-optimization reveals the parallel encoding of competing reach movements," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms8428
    DOI: 10.1038/ncomms8428
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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.
    2. Takashi Yamauchi, 2018. "Modeling Mindsets with Kalman Filter," Mathematics, MDPI, vol. 6(10), pages 1-18, October.

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