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A Model of Reward- and Effort-Based Optimal Decision Making and Motor Control

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  • Lionel Rigoux
  • Emmanuel Guigon

Abstract

Costs (e.g. energetic expenditure) and benefits (e.g. food) are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories). Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control. Author Summary: Behavior is made of decisions and actions. The decisions are based on the costs and benefits of potential actions, and the chosen actions are executed through the proper control of body segments. The corresponding processes are generally considered in separate theories of decision making and motor control, which cannot explain how the actual costs and benefits of a chosen action can be consistent with the expected costs and benefits involved at the decision stage. Here, we propose an overarching optimal model of decision and motor control based on the maximization of a mixed function of costs and benefits. The model provides a unified account of decision in cost/benefit situations (e.g. choice between small reward/low effort and large reward/high effort options), and motor control in realistic motor tasks. The model appears suitable to advance our understanding of the neural bases and pathological aspects of decision making and motor control.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pcbi00:1002716
    DOI: 10.1371/journal.pcbi.1002716
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    References listed on IDEAS

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    3. 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..
    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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    1. 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.
    2. Bastien Berret & Adrien Conessa & Nicolas Schweighofer & Etienne Burdet, 2021. "Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision," PLOS Computational Biology, Public Library of Science, vol. 17(6), pages 1-24, June.
    3. Nathan F Lepora & Giovanni Pezzulo, 2015. "Embodied Choice: How Action Influences Perceptual Decision Making," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-22, April.
    4. Wojciech Białaszek & Przemysław Marcowski & Paweł Ostaszewski, 2017. "Physical and cognitive effort discounting across different reward magnitudes: Tests of discounting models," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-25, July.
    5. Alizée Lopez-Persem & Lionel Rigoux & Sacha Bourgeois-Gironde & Jean Daunizeau & Mathias Pessiglione, 2017. "Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-18, November.
    6. Ignasi Cos, 2017. "Perceived effort for motor control and decision-making," PLOS Biology, Public Library of Science, vol. 15(8), pages 1-6, August.

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