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

PLoS Biol. 2017 Jun 6;15(6):e2001323. doi: 10.1371/journal.pbio.2001323. eCollection 2017 Jun.

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.

Publication types

  • Comparative Study
  • Validation Study

MeSH terms

  • Accident Prevention
  • Adult
  • Algorithms
  • Arm
  • Bayes Theorem
  • Choice Behavior
  • Decision Making*
  • Delay Discounting*
  • Discrimination, Psychological
  • Germany
  • Humans
  • Markov Chains
  • Models, Biological*
  • Models, Psychological*
  • Monte Carlo Method
  • Motor Activity*
  • Motor Skills*
  • Muscle Contraction
  • Physical Exertion*
  • Young Adult

Grant support

German Research Foundation (DFG, Germany) http://www.dfg.de/en/ (grant number FOR-1847-GA1475-B2). Received by AG. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. German Research Foundation (DFG, Germany) http://www.dfg.de/en/ (grant number SFB-889). Received by AG. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Federal Ministry for Education and Research (BMBF, Germany) https://www.bmbf.de (grant number 01GQ1005C). Received by AG. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.