Asymmetric valuation of gains and losses in effort-based decision making

Autoři: Megan K. O’Brien aff001;  Alaa A. Ahmed aff001
Působiště autorů: Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, United States of America aff001
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article


Our decisions are often swayed by a desire to avoid losses over a desire to acquire gains. While loss aversion has been confirmed for decisions about money or commodities, it is unclear how individuals generally value gains relative to losses in effort-based decisions. For example, do individuals avoid greater work more than they seek out less work? We examined this question in the context of physical effort, using an arm-reaching task in which decreased effort was framed as a gain and increased effort was framed as a loss. Subjects performed reaching movements against different levels of resistance that increased or decreased the effort demands of the reaches. They then chose to accept or reject various lotteries, each with a possibility of performing less effortful reaches and a possibility of performing more effortful reaches, compared to the certain outcome of performing reaches against a fixed reference level of effort. Subjects avoided higher effort conditions more than they sought lower effort conditions, demonstrating asymmetric valuation of gains and losses. Using prospect theory, we explored various model formulations to determine subject-specific valuation of effort in these mixed gambles. A nonlinear model of effort valuation demonstrating increasing sensitivity to absolute effort best described the effort lottery choices. In contrast to the loss-aversion observed in financial decisions, there was no evidence of loss aversion in effort-based decisions. Rather, we observed moderate relief-seeking behavior. This model confirms that gains and losses are valued asymmetrically. This is due to the combined effects of increasing sensitivity to absolute effort and moderate relief-seeking, leading to a net effect of greater avoidance of higher effort. Asymmetric valuation was magnified on a later day of testing. In contrast, subjects were loss-averse in a comparable financial task. We suggest that consideration of nonlinear effort valuation can inform future studies of sensorimotor control and exercise motivation.

Klíčová slova:

Behavior – Decision making – Experimental economics – Finance – Learning – Simulation and modeling – Decision theory


1. Tversky A, Kahneman D. Loss aversion in riskless choice: a reference-dependent model. Q J Econ. 1991;106(4): 1039–1061.

2. Kahneman D, Knetcht J, Thaler R. Anomalies: the endowment effect, loss aversion, and status quo bias. J Econ Perspect. 1991;5(1): 193–206.

3. Tversky A, Kahneman D. Advances in prospect theory: cumulative representation of uncertainty. J Risk Uncertain. 1992;5: 297–323.

4. Hull C. Unadaptive habits and experimental extinction. In: Elliot RM, ed. Principles of Behavior. New York: Appleton-Century-Crofts Inc; 1943. pp 293–295.

5. Shadmehr R, Huang HJ, Ahmed AA. A representation of effort in decision-making and motor control. Curr. Biol. 2016;26: 1929–1934. doi: 10.1016/j.cub.2016.05.065 27374338

6. Wang W, Dounskaia N. Load emphasizes muscle effort minimization during selection of arm movement direction. J Neuroeng Rehabil. 2012;9: 70. doi: 10.1186/1743-0003-9-70 23035925

7. Cos I, Belanger N, Cisek P. The influence of predicted arm biomechanics on decision making. J Neurophysiol. 2011;105: 3022–3033. doi: 10.1152/jn.00975.2010 21451055

8. Bitgood S, Dukes S. Not another step! Economy of movement and pedestrian choice point behavior in shopping malls. Environ Behav. 2005;38(3): 394–405.

9. Rosenbaum DA, Gaydos MJ. A method for obtaining psychophysical estimates of movement costs. J Mot Behav. 2008;40: 11–17. doi: 10.3200/JMBR.40.1.11-17 18316293

10. Ranganathan R, Adewuyi A, Mussa-Ivaldi FA. Learning to be lazy: exploiting redundancy in a novel task to minimize movement-related effort. J Neurosci. 2013;33(7): 2754–2760. doi: 10.1523/JNEUROSCI.1553-12.2013 23407935

11. Burk D, Ingram JN, Franklin DW, Shadlen MN, Wolpert DM. Motor effort alters changes of mind in sensorimotor decision making. PLOS One. 2014;9(3): e92681. doi: 10.1371/journal.pone.0092681 24651615

12. Huang HJ, Kram R, Ahmed AA. Reduction of metabolic cost during motor learning of arm-reaching dynamics. J Neurosci. 2012;32(6): 2182–2190. doi: 10.1523/JNEUROSCI.4003-11.2012 22323730

13. Huang HJ, Ahmed AA. Older adults learn less, but still reduce metabolic cost, during motor adaptation. J Neurophys. 2014;111: 135–144.

14. Huang HJ, Ahmed AA. Reductions in muscle coactivation and metabolic cost during visuomotor adaptation. J Neurophys. 2014;112: 2264–2274.

15. Kool W, McGuire JT, Rosen ZB, Botvinick MM. Decision making and the avoidance of cognitive demand. J Exp Psychol Gen. 2010;139: 665–682. doi: 10.1037/a0020198 20853993

16. Stevens JR, Gosati AG, Ross KR, Hauser MD. Will travel for food: spatial discounting in two new world monkeys. Curr Biol. 2005;15(20): 1855–1860. doi: 10.1016/j.cub.2005.09.016 16243033

17. Prévost C, Pessiglione M, Cléry-Melin M-L, Dreher J-C. Separate valuation subsystems for delay and effort decision costs. J Neurosci. 2010;30(42): 14080–14090. doi: 10.1523/JNEUROSCI.2752-10.2010 20962229

18. Hartmann MN, Hager OM, Tobler PN, Kaiser S. Parabolic discounting of monetary rewards by physical effort. Behav Processes. 2013;100: 192–196. doi: 10.1016/j.beproc.2013.09.014 24140077

19. Klein-Flügge MC, Kennerley SW, Saraiva AC, Penny WD, Bestmann S. Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation. PLoS Comput Biol. 2015;11(3): e1004116. doi: 10.1371/journal.pcbi.1004116 25816114

20. Apps MAJ, Grima LL, Manohar S, Husain M. The role of cognitive effort in subjective reward devaluation and risky decision-making. Sci Rep. 2015;5: 16880. doi: 10.1038/srep16880 26586084

21. Nagengast AJ, Braun DA, Wolpert DM. Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control. Proc R Soc Lond B Biol Sci. 2011;278: 2325–2332. doi: 10.1098/rspb.2010.2518 21208966

22. Russ DW, Elliott MA, Vandenborne K, Walter GA, and Binder-Macleod SA. Metabolic costs of isometric force generation and maintenance of human skeletal muscle. Am J Physiol Endocrinol Metab. 2002;282(2): E448–E457. doi: 10.1152/ajpendo.00285.2001 11788378

23. Kushmerick MJ and Paul RJ. Aerobic recovery metabolism following a single isometric tetanus in frog sartorius muscle at 0 degrees C. J Physiol. 1976;254(3): 693–709. doi: 10.1113/jphysiol.1976.sp011253 1082933

24. Uno Y, Kawato M, Suzuki R. Formation and control of optimal trajectory in human multijoint arm movement. Minimum torque-change model. Biol Cybern. 1989;61(2):89–101. doi: 10.1007/bf00204593 2742921

25. Todorov E, Jordan MI. Optimal feedback control as a theory of motor coordination Nat Neurosci. 2002;5:1226–1235. doi: 10.1038/nn963 12404008

26. O’Sullivan I, Burdet E, Diedrichsen J. Dissociating variability and effort as determinants of coordination. PLoS Comput Biol. 2009;5:e1000345. doi: 10.1371/journal.pcbi.1000345 19360132

27. Izawa J, Rane T, Donchin O, Shadmehr R. Motor adaptation as a process of reoptimization. J Neurosci. 2008;28:2883–2891. doi: 10.1523/JNEUROSCI.5359-07.2008 18337419

28. Hartmann MN, Hager OM, Tobler PN, Kaiser S. Parabolic discounting of monetary rewards by physical effort. Behav Processes. 2013;100:192–196. doi: 10.1016/j.beproc.2013.09.014 24140077

29. Białaszek W, Marcowski P, Ostaszewski P. Physical and cognitive effort discounting across different reward magnitudes: Tests of discounting models. PLoS ONE. 2017;12(7):e0182353. doi: 10.1371/journal.pone.0182353 28759631

30. Berret B, Chiovetto E, Nori F, Pozzo T. Evidence for Composite Cost Functions in Arm Movement Planning: An Inverse Optimal Control Approach. PLoS Comput Biol. 2011;7(10): e1002183. doi: 10.1371/journal.pcbi.1002183 22022242

31. Morel P, Ulbrich P, Gail A. What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control. PLoS Biol. 2017;15(6):e2001323. doi: 10.1371/journal.pbio.2001323 28586347

32. Sokol-Hessner P, Hsu M, Curley NG, Delgado MR, Camerer CF, Phelps EA. Thinking like a trader selectively reduces individuals' loss aversion. Proc Natl Acad Sci. 2009;106(13):5035–5040. doi: 10.1073/pnas.0806761106 19289824

33. Chumbley JR, Krajbich I, Engelmann JB, Russell E, Van Uum S, Koren G Fehr E. Endogenous cortisol predicts decreased loss aversion in young men. Psychol Sci. 2014;25(11):2102–2105. doi: 10.1177/0956797614546555 25212582

34. Novemsky N, Kahneman D. How do intentions affect loss aversion? J Mark Res. 2005;42(2): 139–140.

35. Kermer DA, Driver-Linn E, Wilson TD, Gilbert DT. Loss aversion is an affective forecasting error. Psychol Sci. 2006;17(8): 649–653. doi: 10.1111/j.1467-9280.2006.01760.x 16913944

36. Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica. 1979;47(2): 263–292.

37. Kistemaker DA, Wong JD, Gribble PL. The central nervous system does not minimize energy costs in arm movements. J Neurophysiol. 2010;104(6): 2985–2994. doi: 10.1152/jn.00483.2010 20884757

38. Harris CM, Wolpert DM. Signal-dependent noise determines motor planning. Nature. 2008;394(6695): 780–784.

39. Wicker FW, Hamman D, Hagen AS, Reed JL, Wiehe JA. Studies of loss aversion and perceived necessity. J Psychol. 1995;129(1): 75–189.

40. Gätcher S, Johnson EJ, Herrmann A. Individual-level loss aversion in riskless and risky choices. CeDEx Discussion Paper Series. 2010; no. 2961: ISSN 1749–3293.

41. Harinck F, Van Dijk E, Van Beest I, Mersmann P. When gains loom larger than losses: reversed loss aversion for small amounts of money. Psychol Sci. 2007;18(12): 1099–1105. doi: 10.1111/j.1467-9280.2007.02031.x 18031418

42. Ert E, Erev I. On the descriptive value of loss aversion in decisions under risk: six clarifications. Judgm Decis Mak. 2013;8(3): 214–235.

43. Levy DJ, Glimcher PW. Comparing apples and oranges: using reward-specific and reward-general subjective value representation in the brain. J Neurosci. 2011;31(41):14693–14707. doi: 10.1523/JNEUROSCI.2218-11.2011 21994386

44. Wu S-W, Delgado MR, Maloney LT. Economic decision-making compared with an equivalent motor task. Proc Natl Acad Sci. 2009; 06:6088–6093.

45. O’Brien MK, Ahmed AA. Does risk-sensitivity transfer across movements? J Neurophys. 2013;109:1866–1875.

46. O’Brien MK, Ahmed AA. Threat affects risk preferences in movement decision making. Front Behav Neurosci. 2015;9:150. doi: 10.3389/fnbeh.2015.00150 26106311

47. O’Brien MK, Ahmed AA. Rationality in human movement. Exerc Sport Sci Rev. 2016;44(1): 20–28. doi: 10.1249/JES.0000000000000066 26509481

48. Weber EU, Blais A-R, Betz NE. A domain-specific risk-attitude scale: measuring risk perceptions and risk behaviors. J Behav Dec Making. 2002;15:263–290.

49. Kool W, Botvinick MM. A labor/leisure tradeoff in cognitive control. J Exp Psychol Gen. 2012;143: 131–141. doi: 10.1037/a0031048 23230991

50. Tom SM, Fox CR, Trepel C, Poldrack RA. The neural basis of loss aversion in decision-making under risk. Science. 2007;315(5811): 515–518. doi: 10.1126/science.1134239 17255512

51. Borg GAV. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982; 14(5): 377–381. 7154893

52. Stephan KE, Penny WD, Daunizeau J, Moran RJ, Friston KJ. Bayesian model selection for group studies. Neuroimage. 2009; 46(4): 1004–1017. doi: 10.1016/j.neuroimage.2009.03.025 19306932

53. Rigoux L, Stephan KE, Friston KJ, Daunizeau J. Bayesian model selection for group studies–Revisited. Neuroimage. 2014; 84(1): 971–985.

54. Devaine M, Hollard G, Daunizeau J. The Social Bayesian Brain: Does Mentalizing Make a Difference When We Learn? PLoS Comput Biol. 2014; 10(12): e1003992. doi: 10.1371/journal.pcbi.1003992 25474637

Článek vyšel v časopise


2019 Číslo 10
Nejčtenější tento týden