High-fidelity musculoskeletal modeling reveals a motor planning contribution to the speed-accuracy tradeoff

  1. Mazen Al Borno  Is a corresponding author
  2. Saurabh Vyas
  3. Krishna V Shenoy
  4. Scott L Delp
  1. Stanford University, United States

Abstract

A long-standing challenge in motor neuroscience is to understand the relationship between movement speed and accuracy, known as the speed-accuracy tradeoff. Here, we introduce a biomechanically realistic computational model of three-dimensional upper extremity movements that reproduces well-known features of reaching movements. This model revealed that the speed-accuracy tradeoff, as described by Fitts' law, emerges even without the presence of motor noise, which is commonly believed to underlie the speed-accuracy tradeoff. Next, we analyzed motor cortical neural activity from monkeys reaching to targets of different sizes. We found that the contribution of preparatory neural activity to movement duration variability is greater for smaller targets than larger targets, and that movements to smaller targets exhibit less variability in population-level preparatory activity, but greater movement duration variability. These results propose a new theory underlying the speed-accuracy tradeoff: Fitts' law emerges from greater task demands constraining the optimization landscape in a fashion that reduces the number of 'good' control solutions (i.e., faster reaches). Thus, contrary to current beliefs, the speed-accuracy tradeoff could be a consequence of motor planning variability and not exclusively signal-dependent noise.

Data availability

The source code for the computer simulations and our data are available at https://simtk.org/projects/ue-reaching. Users must first create a free account (https://simtk.org/account/register.php) before they can download the datasets from the site.

Article and author information

Author details

  1. Mazen Al Borno

    Bioengineering, Stanford University, Palo Alto, United States
    For correspondence
    malborno@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2208-9934
  2. Saurabh Vyas

    Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Krishna V Shenoy

    Department of Electrical Engineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Scott L Delp

    Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (U54EB020405)

  • Scott L Delp

National Institute of Neurological Disorders and Stroke (R01NS076460)

  • Krishna V Shenoy

National Institute of Mental Health (R01MH09964703)

  • Krishna V Shenoy

Defense Advanced Research Projects Agency (N66001-10-C-2010)

  • Krishna V Shenoy

National Institutes of Health (8DP1HD075623)

  • Krishna V Shenoy

Simons Foundation (325380 and 543045)

  • Krishna V Shenoy

National Institutes of Health (5F31NS103409-02)

  • Saurabh Vyas

National Science Foundation (Graduate Fellowship)

  • Saurabh Vyas

Stanford University (Ric Weiland Stanford Graduate Fellowship)

  • Saurabh Vyas

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All surgical and animal care procedures were performed in accordance with NationalInstitutes of Health guidelines and were approved by the Stanford University InstitutionalAnimal Care and Use Committee (8856).

Human subjects: Subjects gave written informed consent, and consent to publish, approved by the Stanford University Institutional Review Board (42787). The guidelines followed are specified in the Human Research Protection Program (HRPP Stanford University).

Reviewing Editor

  1. J Andrew Pruszynski, Western University, Canada

Publication history

  1. Received: March 18, 2020
  2. Accepted: December 15, 2020
  3. Accepted Manuscript published: December 16, 2020 (version 1)
  4. Version of Record published: January 6, 2021 (version 2)

Copyright

© 2020, Al Borno et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Mazen Al Borno
  2. Saurabh Vyas
  3. Krishna V Shenoy
  4. Scott L Delp
(2020)
High-fidelity musculoskeletal modeling reveals a motor planning contribution to the speed-accuracy tradeoff
eLife 9:e57021.
https://doi.org/10.7554/eLife.57021

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