价值计算决定何时与如何努力

doi:10.3724/SP.J.1042.2022.00877

摘要/Abstract

摘要：

优化努力的分配, 最小化努力成本和最大化收益是各个领域的关键问题。本文梳理了基于努力的决策(effort-based decision-making)的理论与实证研究, 讨论了努力的两面性：固有成本和潜在价值。通过拓展控制期望价值理论(Expected Value of Control, EVC), 本研究探讨了影响努力的非社会与社会因素。探索人们何时以及如何付出努力的计算神经机制, 有利于理解与促进社会互动中的努力行为, 以及为干预精神疾病中动机缺失症状提供参考。

关键词: 努力, 控制期望价值理论, 成本-收益权衡

Abstract:

The optimization of effort investment, which minimizes the cost of effort and maximizes benefits, is a core issue in every field. “What factors influence how much effort we invest?” is gaining more and more attention. This study aims to review previous theoretical and empirical studies on effort. Based on the Paradox of Effort theory, this study expounds on the two sides of effort: inherent cost and potential value. Even though there are intrinsic costs associated with effort, the concept of effort solely in terms of costs is inadequate. The Paradox of Effort theory indicates that analyzing the value of effort at different time stages is more in line with daily activities. The key to effort-based decision-making is weighing the rewards and effort required to accomplish a goal. On this basis, we discussed the non-social and social factors and the neural mechanisms involved in effort investment according to the Expected Value of Control (EVC) theory. EVC theory discusses models of effort optimization in terms of conflict monitoring, cost-benefit integration of cognitive control, and implementation of control, emphasizing the role of integrating the expected value in the dorsal anterior cingulate cortex. Both social and non-social factors have impacts on the adaptive control allocation during the integration, but few empirical studies have explored the two-level interaction. Therefore, we developed the topic of cost-benefit analysis in EVC theory and highlighted its application to motivational behavior in social circumstances, which is conducive to exploring the plasticity of social behavior. The cognitive and neural mechanisms of effort play an essential role in understanding the adaptive allocation of effort in social life and provide references for treating motivational disorders, shaping learned industriousness and prosocial behavior. Future research needs to explore the adaptive changes in the expected value of control during the dynamic process using methods of neurophysiology and combine computational modeling to complement and validate the EVC theory in social contexts.

Key words: effort, Expected Value of Control theory, cost-benefit trade-off

中图分类号:

曹思琪, 汤晨晨, 伍海燕, 刘勋. (2022). 价值计算决定何时与如何努力. 心理科学进展 , 30(4), 877-887.

CAO Si-Qi, TANG Chen-Chen, WU Hai-Yan, LIU Xun. (2022). Value Analysis determines when and how to strive. Advances in Psychological Science, 30(4), 877-887.

图/表 5

图1 努力与其它关联概念的图示注：动机具有方向性。基于动机人们朝着特定方向付出努力。努力是目标导向的中间过程。不同难度的任务要求人们付出相应的努力。但是, 努力区别于任务难度。理论上, 难度可以无限增加, 但是随着难度增加到一定程度, 努力水平呈现下降趋势。

图2 社会与非社会动机下努力成本-收益模型注：Marr的计算框架包括三个主要结构(Marr & Poggio, 1979)：计算(computation), 算法(algorithm)以及执行(implementation)。首先, 计算(computation)指行为决策的具体目标。在图1左(橘色框)中, 基于努力的决策受到社会(合作、竞争与亲社会等)与非社会(奖赏、惩罚, 风险与效力等)因素的影响。这些不同的激励因素影响着大脑优化努力投资的算法(algorithm)。算法具体指的是EVC理论中成本-收益权衡(cost-benefit tradeoff)的框架(图1中间, 蓝色框)。最后, 大脑执行(implementation)目标导向行为的算法, 并最终指导行为(Shenhav et al., 2013, 2017)。眶额皮层(orbitofrontal cortex, OFC); 腹内侧前额皮质(ventral medial prefrontal cortex, vmPFC); 背侧前扣带回(dorsal anterior cingulate cortex, dACC); 外侧前额皮质(lateral prefrontal cortex, LPFC)。

图3 三种时间进程的努力

图4 参与努力行为的脑网络左图：腹内侧前额皮质(ventral medial prefrontal cortex, vmPFC); 前扣带回(anterior cingulate cortex, ACC); 背侧前扣带回(dorsal anterior cingulate cortex, dACC); 伏隔核(nucleus accumbens, NAcc); 杏仁核(amygdala)。右图：眶额皮层(orbitofrontal cortex, OFC); 外侧前额皮质(lateral prefrontal cortex, LPFC); 运动皮层(motor cortex)。

表1 基于努力的成本效益评估的神经机制

努力类型	研究发现	参考文献
体力	纹状体的前部区域编码奖赏信息纹状体的后部区域表征努力的行动启动(effortful action initiation)	(Gangopadhyay et al., 2020)
	腹内侧前额皮质、纹状体参与主观价值的表征	(Sidarus et al., 2019)
	腹内侧前额皮质编码主观价值, 而前扣带回皮质编码决策困难	(Hogan et al., 2019)
认知	哌醋甲酯通过调节纹状体多巴胺信号来提高认知努力任务中收益的敏感性	(Westbrook et al., 2020)
	背侧前扣带回和脑岛编码主观价值计算的努力成本信息	(Westbrook et al., 2019)
	前扣带回皮质的病变损害了涉及努力成本的决策	(Rudebeck et al., 2006)
	前扣带回皮质活动调节伏隔核对努力折扣的响应程度	(Botvinick et al., 2009)

参考文献 83

[1]	曹思琪, 刘勋, 伍海燕. (2021). 共情可控? 以自上而下视角考察共情的可调节性. 心理科学进展, 29(8), 1420-1429.
[2]	高娟, 王鹏, 王晓田, 孙倩, 刘永芳. (2020). 得失情境下他人参照点及心理距离对自我-他人利益权衡的影响. 心理学报, 52(5), 633-644.
[3]	易伟, 梅淑婷, 郑亚. (2019). 努力:成本还是奖赏?. 心理科学进展, 27(08), 1439-1450.
[4]	Angus, D. J., Latham, A. J., Harmon-Jones, E., Deliano, M., Balleine, B., & Braddon-Mitchell, D. (2017). Electrocortical components of anticipation and consumption in a monetary incentive delay task. Psychophysiology, 54(11), 1686-1705. doi: 10.1111/psyp.2017.54.issue-11 URL
[5]	Apps, M. A. J., Grima, L. L., Manohar, S., & Husain, M. (2015). The role of cognitive effort in subjective reward devaluation and risky decision-making. Scientific Reports, 5, 16880. doi: 10.1038/srep16880 URL
[6]	Aridan, N., Malecek, N. J., Poldrack, R. A., & Schonberg, T. (2019). Neural correlates of effort-based valuation with prospective choices. NeuroImage, 185, 446-454. doi: S1053-8119(18)32023-8 pmid: 30347281
[7]	Arulpragasam, A. R., Cooper, J. A., Nuutinen, M. R., & Treadway, M. T. (2018). Corticoinsular circuits encode subjective value expectation and violation for effortful goal-directed behavior. Proceedings of the National Academy of Sciences, 115(22), E5233-E5242.
[8]	Bear, A., & Rand, D. G. (2016). Intuition, deliberation, and the evolution of cooperation. Proceedings of the National Academy of Sciences, 113(4), 936-941. doi: 10.1073/pnas.1517780113 URL
[9]	Białaszek, W., Marcowski, P., & Ostaszewski, P. (2017). Physical and cognitive effort discounting across different reward magnitudes: Tests of discounting models. PLoS ONE, 12(7), e0182353. doi: 10.1371/journal.pone.0182353 URL
[10]	Botvinick, M., & Braver, T. (2015). Motivation and cognitive control: From behavior to neural mechanism. Annual Review of Psychology, 66, 83-113. doi: 10.1146/annurev-psych-010814-015044 pmid: 25251491
[11]	Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. Trends in Cognitive Sciences, 8(12), 539-546. pmid: 15556023
[12]	Botvinick, M. M., Huffstetler, S., & McGuire, J. T. (2009). Effort discounting in human nucleus accumbens. Cognitive, Affective and Behavioral Neuroscience, 9(1), 16-27. doi: 10.3758/CABN.9.1.16 pmid: 19246324
[13]	Caraco, T. (1981). Energy budgets, risk and foraging preferences in dark-eyed juncos (Junco hyemalis). Behavioral Ecology and Sociobiology, 8(3), 213-217. doi: 10.1007/BF00299833 URL
[14]	Charness, G., & Gneezy, U. (2000). What’s in a name? Anonymity and social distance in dictator and ultimatum games. Journal of Economic Behavior & Organization, 68(1), 29-35. doi: 10.1016/j.jebo.2008.03.001 URL
[15]	Chennells, M., & Michael, J. (2018). Effort and performance in a cooperative activity are boosted by perception of a partner’s effort. Scientific Reports, 8(1), 15692. doi: 10.1038/s41598-018-34096-1 pmid: 30356160
[16]	Chong, T. T.-J., Apps, M. A. J., Giehl, K., Hall, S., Clifton, C. H., & Husain, M. (2018). Computational modelling reveals distinct patterns of cognitive and physical motivation in elite athletes. Scientific Reports, 8(1), 11888. doi: 10.1038/s41598-018-30220-3 URL
[17]	Chong, T. T.-J., Apps, M., Giehl, K., Sillence, A., Grima, L. L., & Husain, M. (2017). Neurocomputational mechanisms underlying subjective valuation of effort costs. PLOS Biology, 15(2), e1002598. doi: 10.1371/journal.pbio.1002598 URL
[18]	Contreras-Huerta, L. S., Pisauro, M. A., & Apps, M. A. J. (2020). Effort shapes social cognition and behaviour: A neuro-cognitive framework. Neuroscience and Biobehavioral Reviews, 118, 426-439. doi: S0149-7634(20)30521-2 pmid: 32818580
[19]	Crockett, M. J., Kurth-Nelson, Z., Siegel, J. Z., Dayan, P., & Dolan, R. J. (2014). Harm to others outweighs harm to self in moral decision making. Proceedings of the National Academy of Sciences, 111(48), 17320-17325. doi: 10.1073/pnas.1408988111 URL
[20]	Croxson, P. L., Walton, M. E., O;Reilly, J. X., Behrens, T. E. J., & Rushworth, M. F. S. (2009). Effort-based cost-benefit valuation and the human brain. The Journal of Neuroscience, 29(14), 4531 -4541. doi: 10.1523/JNEUROSCI.4515-08.2009 URL
[21]	Cudo, A., Francuz, P., Augustynowicz, P., & Stróżak, P. (2018). The effects of arousal and approach motivated positive affect on cognitive control. An ERP study. Frontiers in Human Neuroscience, 12, 320. doi: 10.3389/fnhum.2018.00320 URL
[22]	Decety, J., & Yoder, K. J. (2016). Empathy and motivation for justice: Cognitive empathy and concern, but not emotional empathy, predict sensitivity to injustice for others. Social Neuroscience, 11(1),1-14. doi: 10.1080/17470919.2015.1029593 pmid: 25768232
[23]	Duckworth, A. L., Tsukayama, E., & Kirby, T. A. (2013). Is it really self-control? Examining the predictive power of the delay of gratification task. Personality and Social Psychology Bulletin, 39(7), 843-855. doi: 10.1177/0146167213482589 pmid: 23813422
[24]	Eisenberger, R. (1992). Learned industriousness. Psychological Review, 99(2), 248-267. pmid: 1594725
[25]	Egner, T. (2017). The Wiley handbook of cognitive control. New Jersey: John Wiley & Sons.
[26]	Festinger, L. (1957). A theory of cognitive dissonance (Vol. 2). Redwood City: Stanford university press.
[27]	Freund, M. C., Etzel, J. A., & Braver, T. S. (2021). Neural coding of cognitive control: The representational similarity analysis approach. Trends in Cognitive Sciences, 25(7), 622-638. doi: 10.1016/j.tics.2021.03.011 URL
[28]	Frömer, R., Lin, H., Dean Wolf, C. K., Inzlicht, M., & Shenhav, A. (2021). Expectations of reward and efficacy guide cognitive control allocation. Nature Communications, 12(1), 1-11. doi: 10.1038/s41467-020-20314-w URL
[29]	Gangopadhyay, P., Chawla, M., Dal Monte, O., & Chang, S. W. C. (2020). Prefrontal-amygdala circuits in social decision-making. Nature Neuroscience, 24(1), 5-18. doi: 10.1038/s41593-020-00738-9 URL
[30]	Garvert, M. M., Moutoussis, M., Kurth-Nelson, Z., Behrens, T. E. J., & Dolan, R. J. (2015). Learning-induced plasticity in medial prefrontal cortex predicts preference malleability. Neuron, 85(2), 418-428. doi: 10.1016/j.neuron.2014.12.033 URL
[31]	Grahek, I., Frömer, R., & Shenhav, A. (2021). Learning when effort matters: Neural dynamics underlying updating and adaptation to changes in performance efficacy. BioRxiv, 2020.10.09.333310.
[32]	Hart, E. E., & Izquierdo, A. (2019). Quantity versus quality: Convergent findings in effort-based choice tasks. Behavioural Processes, 164, 178-185. doi: 10.1016/j.beproc.2019.05.009 URL
[33]	Heilbronner, S. R., & Hayden, B. Y. (2016). Dorsal anterior cingulate cortex: A bottom-up view. Annual Review of Neuroscience, 39(1), 149-170. doi: 10.1146/neuro.2016.39.issue-1 URL
[34]	Hogan, P. S., Galaro, J. K., & Chib, V. (2019). Roles of ventromedial prefrontal cortex and anterior cingulate in subjective valuation of prospective effort. Cerebral Cortex, 29(10), 4277-4290. doi: 10.1093/cercor/bhy310 URL
[35]	Holroyd, C. B., & Yeung, N. (2012). Motivation of extended behaviors by anterior cingulate cortex. Trends in Cognitive Sciences, 16(2), 122-128. doi: 10.1016/j.tics.2011.12.008 pmid: 22226543
[36]	Inzlicht, M., Shenhav, A., & Olivola, C. Y. (2018). The effort paradox: Effort is both costly and valued. Trends in Cognitive Sciences, 22(4), 337-349. doi: S1364-6613(18)30020-2 pmid: 29477776
[37]	Kang, G., Chang, W., Wang, L., & Zhou, X. (2019). Reward expectation modulates multiple stages of auditory conflict control. International Journal of Psychophysiology, 146, 148-156. doi: 10.1016/j.ijpsycho.2019.09.009 URL
[38]	Klein-Flügge, M. C., Kennerley, S. W., Friston, K., & Bestmann, S. (2016). Neural signatures of value comparison in human cingulate cortex during decisions requiring an effort-reward trade-off. Journal of Neuroscience, 36(39), 10002-10015. doi: 10.1523/JNEUROSCI.0292-16.2016 pmid: 27683898
[39]	Klein-Flügge, M. C., Kennerley, S. W., Saraiva, A. C., Penny, W. D., & Bestmann, S. (2015). Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation. PLOS Computational Biology, 11(3), e1004116. doi: 10.1371/journal.pcbi.1004116 URL
[40]	Kostandyan, M., Bombeke, K., Carsten, T., Krebs, R. M., Notebaert, W., & Boehler, C. N. (2019). Differential effects of sustained and transient effort triggered by reward-A combined EEG and pupillometry study. Neuropsychologia, 123, 116-130. doi: S0028-3932(18)30173-8 pmid: 29709582
[41]	Kührt, C., Pannasch, S., Kiebel, S. J., & Strobel, A. (2021). Dispositional individual differences in cognitive effort investment: Establishing the core construct. BMC Psychology, 9(1), 1-14. doi: 10.1186/s40359-020-00492-4 URL
[42]	Leng, X., Yee, D., Ritz, H., & Shenhav, A. (2020). Dissociable influences of reward and punishment on adaptive cognitive control. BioRxiv, 2020.09.11.294157
[43]	Leonard, J. A., Lee, Y., & Schulz, L. E. (2017). Infants make more attempts to achieve a goal when they see adults persist. Science, 357(6357), 1290-1294. doi: 10.1126/science.aan2317 pmid: 28935806
[44]	Lockwood, P. L., Hamonet, M., Zhang, S. H., Ratnavel, A., Salmony, F. U., Husain, M., & Apps, M. A. J. (2017). Prosocial apathy for helping others when effort is required. Nature Human Behaviour, 1(7), 1-10. doi: 10.1038/s41562-016-0001 URL
[45]	Manohar, S. G., Finzi, R. D., Drew, D., & Husain, M. (2017). Distinct motivational effects of contingent and noncontingent rewards. Psychological Science, 28(7), 1016-1026. doi: 10.1177/0956797617693326 pmid: 28488927
[46]	Marr, D., & Poggio, T. (1979). A computational theory of human stereo vision. Proceedings of the Royal Society of London. Series B. Biological Sciences, 204(1156), 301-328.
[47]	Millet, K., & Dewitte, S. (2007). Altruistic behavior as a costly signal of general intelligence. Journal of Research in Personality, 41(2), 316-326. doi: 10.1016/j.jrp.2006.04.002 URL
[48]	Miller, M. A., Thomé, A., & Cowen, S. L. (2013). Intersection of effort and risk: Ethological and neurobiological perspectives. Frontiers in Neuroscience, 7, 208. doi: 10.3389/fnins.2013.00208 pmid: 24223535
[49]	Morsella, E., Feinberg, G. H., Cigarchi, S., Newton, J. W., & Williams, L. E. (2011). Sources of avoidance motivation: Valence effects from physical effort and mental rotation. Motivation and Emotion, 35(3), 296-305. doi: 10.1007/s11031-010-9172-y URL
[50]	Nagengast, A. J., Braun, D. A., & Wolpert, D. M. (2011). Risk-sensitivity and the mean-variance trade-off: Decision making in sensorimotor control. Proceedings of the Royal Society B: Biological Sciences, 278(1716), 2325-2332. doi: 10.1098/rspb.2010.2518 URL
[51]	Norton, M. I., Mochon, D., & Ariely, D. (2012). The IKEA effect: When labor leads to love. Journal of Consumer Psychology, 22(3), 453-460. doi: 10.1016/j.jcps.2011.08.002 URL
[52]	O’Doherty, J. P., Cockburn, J., & Pauli, W. M. (2017). Learning, reward, and decision making. Annual Review of Psychology, 68, 73-100. doi: 10.1146/psych.2017.68.issue-1 URL
[53]	Olivola, C. Y., & Shafir, E. (2013). The martyrdom effect: When pain and effort increase prosocial contributions. Journal of Behavioral Decision Making, 26(1), 91-105. doi: 10.1002/bdm.v26.1 URL
[54]	Olivola, C. Y., & Shafir, E. (2018). Blood, sweat, and cheers: The martyrdom effect increases willingness to sponsor others’ painful and effortful prosocial acts. Available at SSRN 3101447.
[55]	Parro, C., Dixon, M. L., & Christoff, K. (2018). The neural basis of motivational influences on cognitive control. Human brain mapping, 39(12), 5097-5111. doi: 10.1002/hbm.v39.12 URL
[56]	Prévost, C., Pessiglione, M., Météreau, E., Cléry-Melin, M. L., & Dreher, J. C. (2010). Separate valuation subsystems for delay and effort decision costs. Journal of Neuroscience, 30(42), 14080-14090. doi: 10.1523/JNEUROSCI.2752-10.2010 URL
[57]	Rangel, A., Camerer, C., & Montague, P. R. (2008). A framework for studying the neurobiology of value-based decision making. Nature Reviews Neuroscience, 9(7), 545-556. doi: 10.1038/nrn2357 URL
[58]	Reyes-Aguilar, A., Fernandez-Ruiz, J., Pasaye, E. H., & Barrios, F. A. (2017). Executive mechanisms for thinking about negative situations in both cooperative and non-cooperative contexts. Frontiers in Human Neuroscience, 11, 275. doi: 10.3389/fnhum.2017.00275 pmid: 28596727
[59]	Rudebeck, P. H., Walton, M. E., Smyth, A. N., Bannerman, D. M., & Rushworth, M. F. S. (2006). Separate neural pathways process different decision costs. Nature Neuroscience, 9(9), 1161-1168. pmid: 16921368
[60]	Sandra, D. A., & Otto, A. R. (2018). Cognitive capacity limitations and need for cognition differentially predict reward-induced cognitive effort expenditure. Cognition, 172, 101-106. doi: S0010-0277(17)30306-2 pmid: 29247878
[61]	Seaman, K. L., Brooks, N., Karrer, T. M., Castrellon, J. J., Perkins, S. F., Dang, L. C., Hsu, M., Zald, D. H., & Samanez-Larkin, G. R. (2018). Subjective value representations during effort, probability and time discounting across adulthood. Social Cognitive and Affective Neuroscience, 13(5), 449-459. doi: 10.1093/scan/nsy021 URL
[62]	Shenhav, A., Botvinick, M. M., & Cohen, J. D. (2013). The expected value of control: An integrative theory of anterior cingulate cortex function. Neuron, 79(2), 217-240. doi: 10.1016/j.neuron.2013.07.007 pmid: 23889930
[63]	Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual Review of Neuroscience, 40, 99-124. doi: 10.1146/annurev-neuro-072116-031526 pmid: 28375769
[64]	Shenhav, A., Prater Fahey, M., & Grahek, I. (2021). Decomposing the motivation to exert mental effort. Current Directions in Psychological Science, 30(4), 307-314. doi: 10.1177/09637214211009510 pmid: 34675454
[65]	Sidarus, N., Palminteri, S., & Chambon, V. (2019). Cost-benefit trade-offs in decision-making and learning. PLoS Computational Biology, 15(9), e1007326. doi: 10.1371/journal.pcbi.1007326 URL
[66]	Sullivan-Toole, H., DePasque, S., Holt-Gosselin, B., & Galván, A. (2019). Worth working for: The influence of effort costs on teens' choices during a novel decision making game. Developmental Cognitive Neuroscience, 37, 100652. doi: 10.1016/j.dcn.2019.100652 URL
[67]	Tran, T., Hagen, A. E. F., Hollenstein, T., & Bowie, C. R. (2020). Physical- and cognitive-effort-based decision-making in depression: Relationships to symptoms and functioning. Clinical Psychological Science. 9(1), 53-67. doi: 10.1177/2167702620949236 URL
[68]	Tusche, A., Böckler, A., Kanske, P., Trautwein, F. M., & Singer, T. (2016). Decoding the charitable brain: Empathy, perspective taking, and attention shifts differentially predict altruistic giving. Journal of Neuroscience, 36(17), 4719-4732. doi: 10.1523/JNEUROSCI.3392-15.2016 pmid: 27122031
[69]	Vekaria, K. M., Brethel-Haurwitz, K. M., Cardinale, E. M., Stoycos, S. A., & Marsh, A. A. (2017). Social discounting and distance perceptions in costly altruism. Nature Human Behaviour, 1(5), 112474.
[70]	Verguts, T., Vassena, E., & Silvetti, M. (2015). Adaptive effort investment in cognitive and physical tasks: A neurocomputational model. Frontiers in Behavioral Neuroscience, 9, 57. doi: 10.3389/fnbeh.2015.00057 pmid: 25805978
[71]	Vogel, T. A., Savelson, Z. M., Otto, A. R., & Roy, M. (2020). Forced choices reveal a trade-off between cognitive effort and physical pain. ELife, 9, e59410. doi: 10.7554/eLife.59410 URL
[72]	Volz, L. J., Welborn, B. L., Gobel, M. S., Gazzaniga, M. S., & Grafton, S. T. (2017). Harm to self outweighs benefit to others in moral decision making. Proceedings of the National Academy of Sciences of the United States of America, 114(30), 7963-7968.
[73]	Westbrook, A., & Frank, M. (2018). Dopamine and proximity in motivation and cognitive control. Current Opinion in Behavioral Sciences, 22, 28-34. doi: 10.1016/j.cobeha.2017.12.011 pmid: 29713659
[74]	Westbrook, A., Frank, M. J., & Cools, R. (2021). A mosaic of cost-benefit control over cortico-striatal circuitry. Trends in Cognitive Sciences, 25(8), 710-721. doi: 10.1016/j.tics.2021.04.007 pmid: 34120845
[75]	Westbrook, A., Lamichhane, B., & Braver, T. (2019). The subjective value of cognitive effort is encoded by a domain-general valuation network. Journal of Neuroscience, 39(20), 3934-3947. doi: 10.1523/JNEUROSCI.3071-18.2019 pmid: 30850512
[76]	Westbrook, A., van den Bosch, R., Määttä, J. I., Hofmans, L., Papadopetraki, D., Cools, R., & Frank, M. J. (2020). Dopamine promotes cognitive effort by biasing the benefits versus costs of cognitive work. Science, 367(6484), 1362-1366. doi: 10.1126/science.aaz5891 pmid: 32193325
[77]	Will, G. J., Rutledge, R. B., Moutoussis, M., & Dolan, R. J. (2017). Neural and computational processes underlying dynamic changes in self-esteem. ELife, 6, e28098. doi: 10.7554/eLife.28098 URL
[78]	Williams, L., & Gill, D. L. (1995). The role of perceived competence in the motivation of physical activity. Journal of Sport and Exercise Psychology, 17(4), 363-378. doi: 10.1123/jsep.17.4.363 URL
[79]	Wittmann, M. K., Kolling, N., Faber, N. S., Scholl, J., Nelissen, N., & Rushworth, M. F. S. (2016). Self-Other mergence in the frontal cortex during cooperation and competition. Neuron, 91(2), 482-493. doi: 10.1016/j.neuron.2016.06.022 pmid: 27477020
[80]	Yee, D. M., & Braver, T. S. (2018). Interactions of motivation and cognitive control. Current Opinion in Behavioral Sciences, 19, 83-90. doi: 10.1016/j.cobeha.2017.11.009 URL
[81]	Yee, D. M., Crawford, J. L., Lamichhane, B., & Braver, T. S. (2021). Dorsal anterior cingulate cortex encodes the integrated incentive motivational value of cognitive task performance. Journal of Neuroscience, 41(16), 3707-3720. doi: 10.1523/JNEUROSCI.2550-20.2021 URL
[82]	Zaki, J., Wager, T. D., Singer, T., Keysers, C., & Gazzola, V. (2016). The anatomy of suffering: Understanding the relationship between nociceptive and empathic pain. Trends in Cognitive Sciences, 20(4), 249-259. doi: 10.1016/j.tics.2016.02.003 URL
[83]	Zénon, A., Devesse, S., & Olivier, E. (2016). Dopamine manipulation affects response vigor independently of opportunity cost. Journal of Neuroscience, 36(37), 9516-9525. doi: 10.1523/JNEUROSCI.4467-15.2016 URL