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What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control

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  • Pierre Morel
  • Philipp Ulbrich
  • Alexander Gail

Abstract

When deciding between alternative options, a rational agent chooses on the basis of the desirability of each outcome, including associated costs. As different options typically result in different actions, the effort associated with each action is an essential cost parameter. How do humans discount physical effort when deciding between movements? We used an action-selection task to characterize how subjective effort depends on the parameters of arm transport movements and controlled for potential confounding factors such as delay discounting and performance. First, by repeatedly asking subjects to choose between 2 arm movements of different amplitudes or durations, performed against different levels of force, we identified parameter combinations that subjects experienced as identical in effort (isoeffort curves). Movements with a long duration were judged more effortful than short-duration movements against the same force, while movement amplitudes did not influence effort. Biomechanics of the movements also affected effort, as movements towards the body midline were preferred to movements away from it. Second, by introducing movement repetitions, we further determined that the cost function for choosing between effortful movements had a quadratic relationship with force, while choices were made on the basis of the logarithm of these costs. Our results show that effort-based action selection during reaching cannot easily be explained by metabolic costs. Instead, force-loaded reaches, a widely occurring natural behavior, imposed an effort cost for decision making similar to cost functions in motor control. Our results thereby support the idea that motor control and economic choice are governed by partly overlapping optimization principles.Author summary: Economic choice in humans and animals can be understood as a weighing of benefits (e.g., reward) against costs (e.g., effort, delay, risk), leading to a preference for the behavioral option with highest expected utility. The costs of the action associated with a choice can thereby affect its utility: for equivalent benefits, an action that requires less physical effort will be preferred to a more effortful one. Here, we characterized how human subjects assess physical effort when choosing between arm movements. We show that the effort cost of a movement increases with its duration and with the square of the force it is performed against but not with the distance covered. Therefore, the subjective cost that determines decisions does not reflect the objective energetic cost of the actions—i.e., the corresponding metabolic expenditure. Instead, the subjective cost has commonalities with the cost that our central nervous system is believed to minimize for controlling the motor execution of actions. Our findings thus argue in favor of action selection and action control sharing common underlying optimization principles.

Suggested Citation

  • Pierre Morel & Philipp Ulbrich & Alexander Gail, 2017. "What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control," PLOS Biology, Public Library of Science, vol. 15(6), pages 1-23, June.
  • Handle: RePEc:plo:pbio00:2001323
    DOI: 10.1371/journal.pbio.2001323
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    References listed on IDEAS

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    1. Lionel Rigoux & Emmanuel Guigon, 2012. "A Model of Reward- and Effort-Based Optimal Decision Making and Motor Control," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-13, October.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. Konrad P Körding & Izumi Fukunaga & Ian S Howard & James N Ingram & Daniel M Wolpert, 2004. "A Neuroeconomics Approach to Inferring Utility Functions in Sensorimotor Control," PLOS Biology, Public Library of Science, vol. 2(10), pages 1-1, September.
    4. Christopher M. Harris & Daniel M. Wolpert, 1998. "Signal-dependent noise determines motor planning," Nature, Nature, vol. 394(6695), pages 780-784, August.
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    Cited by:

    1. Arkady Zgonnikov & Nadim A. A. Atiya & Denis O'Hora & Iñaki Rañò & KongFatt Wong-Lin, 2019. "Beyond reach: Do symmetric changes in motor costs affect decision making? A registered report," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(4), pages 455-469, July.
    2. repec:cup:judgdm:v:14:y:2019:i:4:p:455-469 is not listed on IDEAS
    3. Megan K O’Brien & Alaa A Ahmed, 2019. "Asymmetric valuation of gains and losses in effort-based decision making," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-21, October.

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