心理科学进展, 2019, 27(8): 1439-1450 doi: 10.3724/SP.J.1042.2019.01439

研究前沿

努力:成本还是奖赏?

易伟, 梅淑婷, 郑亚,

大连医科大学心理学系, 大连 116044

Effort: Cost or reward?

YI Wei, MEI Shuting, ZHENG Ya,

Department of Psychology, Dalian Medical University, Dalian 116044, China

通讯作者: 郑亚, E-mail: zhengya@dmu.edu.cn

收稿日期: 2018-10-17   网络出版日期: 2019-07-26

基金资助: * 国家自然科学基金项目.  31500872

Received: 2018-10-17   Online: 2019-07-26

摘要

努力(Effort)与奖赏系统关系密切。当前关于努力在奖赏加工中的作用存在两个截然相反的观点:努力是一种成本还是一种奖赏?理论模型包括:其一, 努力是一种成本, 会降低奖赏的价值, 相应的理论解释包括内部成本模型、机会成本模型及信号模型等; 其二, 努力能够提升奖赏的价值, 相应的理论解释包括认知失调和努力的合理化模型、习得性勤奋理论及认知需求理论等。这两种观点均得到了来自于动物学、行为学、电生理学以及神经影像学等证据的支持。未来研究需要对努力准确定义, 从时间进程角度对努力的理论进行整合, 进一步考察努力的相关影响因素。

关键词: 努力 ; 成本 ; 奖赏

Abstract

Effort plays a critical role in reward processing, which has been couched within two contradictory theories regarding effort as either a cost or a reward. On the one hand, effort is regarded as a cost whereby it reduces reward value, which has been articulated in the intrinsic cost model, the opportunity cost model, and the signal model. On the other hand, effort can boost the value of reward, which has been explained by the cognitive dissonance model, the learned industriousness model, and the need for cognition model. Both theories have been supported by converging evidence from animal studies, human behavioral studies, electrophysiological studies, and neuroimaging studies. Future research is needed to specify the definition of effort, integrate the competing theories in terms of the time course of effort expenditure, and explore potential factors that impact on effort.

Keywords: effort ; cost ; reward

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本文引用格式

易伟, 梅淑婷, 郑亚. (2019). 努力:成本还是奖赏? . 心理科学进展, 27(8), 1439-1450

YI Wei, MEI Shuting, ZHENG Ya. (2019). Effort: Cost or reward?. Advances in Psychological Science, 27(8), 1439-1450

1 引言

努力与人们的生活息息相关, 小到早起上班、锻炼身体、学习某项技能, 大到完成学业、实施某项工程、进行重大人生决策, 都需要努力的参与。社会心理学研究表明, 持续的努力不仅能够提高学生的学业水平(Duckworth, Peterson, Matthews, & Kelly, 2007; Duncan et al., 2007), 而且能够提升个体的社会交往能力和社会竞争力(Tangney, Baumeister, & Boone, 2004)。最近的研究表明, 个体付出努力的意愿的减退与快感缺失(Geaney et al., 2015; Treadway, Buckholtz, Schwartzman, Lambert, & Zald, 2009; Wang et al., 2015)、动机缺乏(Barch, Treadway, & Schoen, 2014; Fervaha et al., 2013)及情感淡漠(Bonnelle et al., 2015; Hartmann et al., 2015; Husain & Roiser, 2018)等精神疾病的核心症状有关, 这些精神疾病包括抑郁症(Culbreth et al., 2018; Rzepa, Fisk, & McCabe, 2017; Treadway, Bossaller, Shelton, & Zald, 2012; Yang et al., 2016)、精神分裂症(Gold et al., 2015; Gold et al., 2013)、神经性厌食症(Holsen & Goldstein, 2015)以及帕金森病(Chong et al., 2015; Tan et al., 2013)等。因此, 研究努力有助于加深我们对相关精神疾病的理解, 并且对这些疾病的预防和治疗具有积极的指导意义。

近年来, 研究者们对努力进行了大量的研究, 提出了许多有价值的理论模型。但是, 这些理论模型之间不仅相互矛盾, 也无法完全合理地解释生活中的现象, 并且常常与实验室研究结果相悖(Inzlicht, Shenhav, & Olivola, 2018)。我们认为, 导致这些理论模型的解释力度和预测效度无法令人满意的根本原因是:努力是一种成本(降低奖赏的价值), 还是一种奖赏(提高奖赏的价值) (Inzlicht et al., 2018; Kurzban, 2016; Shenhav et al., 2017)?本文将从这一问题出发, 分别从努力能够降低价值和努力能够增加价值这两个方面进行梳理和总结, 并对未来的研究提出展望。

2 努力的定义

努力是一种外显行为, 能够被个体自身和观察者觉察到(de Morree & Marcora, 2010, 2015)。尽管研究者们对努力进行了大量的研究, 但是到目前为止, 努力的定义尚未统一。Hayakawa (1987)将努力定义为“为了达到某种目的而付出的体力或心理活动”。Kahneman (1973)强调努力与动机的关系, 认为努力是一种与个体的主动行为有关的特殊唤醒状态, 这种状态有别于吸食毒品或外界压力导致的被动唤醒。而最近的研究者们倾向于将努力定义为, 介于(1)个体完成任务的潜力和任务本身的特性和(2)个体实际完成任务的程度之间的一种调节过程(Inzlicht et al., 2018; Shenhav et al., 2017)。虽然努力的定义存在差异, 但是这些定义均强调两点:(1)努力是一种主动的、需要意志参与的过程; (2)努力与个体的能力(或状态)及目标任务的属性有关。

另外, 努力与其他诸多心理因素存在密切的关系, 包括动机、注意、难度和无聊等, 明确这些关系有助于理解努力结构的复杂性(Westbrook & Braver, 2015)。

2.1 努力与动机

研究表明, 个体的动机唤醒程度总是与努力程度相匹配(Heckhausen, Schmalt, & Schneider, 1985)。例如, Kahneman (1973)认为努力的本质是一种特殊的动机状态。事实上, 尽管努力与动机关系密切, 但是二者存在明显的差异。动机强度理论认为, 个体的动机唤醒水平随着努力的提高而上升, 但是, 当努力的效用低于努力的成本, 或者完成任务所需要的努力超过个体的能力时, 个体的动机随着努力的增加而呈现下降趋势(Brehm & Self, 1989)。另外, 动机一般指向特定的目标, 而努力没有特定的指向(Inzlicht et al., 2018; Westbrook & Braver, 2015)。

2.2 努力与注意

尽管注意过程往往需要更多的认知努力, 但并非所有类型的注意都需要努力参与。例如, 注意恢复理论将注意分为主动注意和非主动注意。主动注意需要努力参与, 同时为各种认知努力活动提供资源(Kaplan, 2016; Kaplan & Berman, 2010); 而非主动注意是自动化的加工, 不需要努力或只需要极少努力的参与(Kaplan, 2016)。Kahneman (1973)将努力的执行等同于主动注意的过程, 二者都是一种主动的、有意志的行为。

2.3 努力与难度

许多研究者将任务难度作为努力的操作定义(Hernandez Lallement et al., 2014; Ma, Meng, Wang, & Shen, 2014; Wang, Zheng, & Meng, 2017):任务的难度越大, 个体付出的努力程度也越高; 努力主要取决于任务执行中错误的可能性(Dunn, Inzlicht, & Risko, 2017; Norman & Bobrow, 1975)。事实上, 任务难度的加工分为两种类型:资源限制过程(resource-limited process)和材料限制过程(data-limited process) (Norman & Bobrow, 1975)。如果任务表现取决于资源限制过程, 那么难度越高, 个体的努力程度越高; 相反, 如果任务表现取决于材料限制过程, 由于任务信息有限, 即使增加努力也无法提高任务表现, 因此, 任务难度的增加并不会提高个体的努力程度。另外, 努力是个体的主动加工过程, 而难度是任务本身的属性。研究证据表明, 当奖赏诱因较低或者难度过高时, 个体的努力不会随着难度的增加而增加, 表现出二者的分离(Brehm & Self, 1989; Kahneman, 1973)。

2.4 努力与无聊

作为一种不愉快的体验, 无聊来源于个体内部强烈的心理需求与外部刺激缺乏或者不足之间的冲突(Fenichel, 1951)。当个体认为外部任务太过简单、无法满足其内部需求时, 个体就会产生无聊的体验。努力与无聊存在互为因果的关系。一方面, 个体更愿意执行高努力任务从而摆脱当前的无聊状态(Eastwood, Frischen, Fenske, & Smilek, 2012; Fisherl, 1993; Milyavskaya, Inzlicht, Johnson, & Larson, 2018)。无聊的认知理论强调, 当个体处于无聊状态时, 其注意集中性较差, 需要花费更多的努力控制他们的注意力(Fisherl, 1993; Todman, 2003), 从这一角度来讲, 无聊是努力的原因(或无聊增强了努力的动机); 另一方面, 随着努力任务的进行, 个体又会产生无聊、疲劳及其他负性情绪(Inzlicht, Schmeichel, & Macrae, 2014; Pattyn, Neyt, Henderickx, & Soetens, 2008), 因而无聊是努力的结果。

3 努力是一种成本

前人对努力的研究主要集中于将“努力是一种成本”作为前提假设。尽管某些需要付出努力的行为(例如健身、节食等)从长远来说具有适应性意义, 但这些行为仍然被个体认为是不愉快的(Eastwood et al., 2012; Kool & Botvinick, 2014)。

动物学证据表明, 当行为结果的奖赏价值相同时, 相对于高努力的选项, 动物倾向于选择低努力的选项。例如, 当食物数量恒定时, 随着获得食物需要按压杠杆的次数增加, 大鼠选择高努力选项的比例降低(Cocker, Hosking, Benoit, & Winstanley, 2012; Floresco, Tse, & Ghods-Sharifi, 2008; Hosking, Floresco, & Winstanley, 2014; Hull, 1943)。类似地, 人类行为学研究表明, 当两个选项(一个为高努力选项, 另一个为低努力选项)的奖赏价值相同时, 个体倾向于避免选择高努力选项(Klein-Flügge, Kennerley, Saraiva, Penny, & Bestmann, 2015); 当高努力选项的奖赏价值增加时, 个体选择该选项的比例也随之增加(Kool & Botvinick, 2014; Treadway et al., 2009; Wang et al., 2015; Zhang, Li, Wang, Liu, & Zheng, 2017)。从时间进程的角度来说, 随着任务的进行, 个体付出努力的意愿随之降低(Hagger et al., 2016; Kool & Botvinick, 2014; Zhang et al., 2017)。最近的研究发现, 采用类似于延迟折扣的范式, 当被要求在高努力、特定的高奖赏值(如20元)任务与低努力、不断变化的较低奖赏值(如1~5元)任务之间进行选择时, 个体宁愿放弃较高的奖赏从而避免高努力的任务(Hartmann, Hager, Tobler, & Kaiser, 2013; Nishiyama, 2014, 2016; Westbrook & Braver, 2015; Westbrook, Kester, & Braver, 2013)。这种高努力选项的主观值随着所要付出的努力增加而降低的现象被称之为努力折扣(effort discounting)。

生理学证据表明, 努力活动会引起交感神经系统兴奋, 如心跳加速、血压上升、呼吸急促和皱眉肌收缩等, 并且产生焦虑、疲劳、甚至沮丧等负性情绪(Elkins-Brown, Saunders, & Inzlicht, 2016; Silvestrini, 2017)。功能核磁共振成像(functional magnetic resonance imaging, fMRI)研究表明, 以纹状体为代表的奖赏网络编码了以努力为基础的成本-利益的评估(Croxson, Walton, O'Reilly, Behrens, & Rushworth, 2009; Massar, Libedinsky, Weiyan, Huettel, & Chee, 2015; Wallis & Rushworth, 2014)。相对于低努力条件, 高努力条件导致前扣带回的激活显著增强(Croxson et al., 2009; Hart et al., 2017; Kurniawan, Guitart-Masip, Dayan, & Dolan, 2013; Massar et al., 2015; Prévost, Pessiglione, Météreau, Cléry-Melin, & Dreher, 2010; Vassena et al., 2014), 并且被试对于高努力的预测同样会激活前扣带回(Vassena, Holroyd, & Alexander, 2017)。研究者们认为, 前扣带回的这种激活模式与被试对努力的厌恶有关。类似地, 高努力条件下, 前额叶皮质(McGuire & Botvinick, 2010)、顶内沟(Chong et al., 2017)、前脑岛(Hernandez Lallement et al., 2014; Prévost et al., 2010)、杏仁核(Chong et al., 2017)等区域的活动增强。另外, 腹侧纹状体和伏隔核的激活一方面随着奖赏的增加而增强, 另一方面却随着任务努力需求的增加而减弱(Botvinick, Huffstetler, & McGuire, 2009; Kurniawan et al., 2013)。药理学的证据表明, 大脑多巴胺水平会随着努力水平的上升而降低(Salamone, Correa, Farrar, & Mingote, 2007), 而给成年人类被试服用安非他命能够提高其付出努力的意愿(Wardle, Treadway, Mayo, Zald, & de Wit, 2011)。最近的一项脑电(Electroencephalogram, EEG)研究表明, 相对于没有期待, 避免努力任务的期待能够增大奖励正波(reward positivity, RewP)的幅值, 并且Deta和Beta-gamma频段的功率也相应提高(Gheza, de Raedt, Baeken, & Pourtois, 2018)。由于这些指标被认为与奖赏的敏感性有关, 因此上述结果提示, 降低努力的预期能够提高结果反馈的价值。类似地, Beta频段的功率会随着努力任务的进行而降低(Anzak et al., 2012; Tan et al., 2013), 也说明努力会降低奖赏的价值。综上所述, 来自各个方面的证据表明, 努力是一种成本, 与负性情感系统相关联, 而避免努力激活了正性情感系统。那么, 努力作为一种成本的心理机制是什么?研究者们提出了诸多理论模型, 主要包括以下三种:内部成本模型、机会成本模型以及信号模型。

3.1 内部成本模型

内部成本模型认为, 努力本身携带一种主观成本(Kool & Botvinick, 2013; Muraven & Baumeister, 2000), 这种成本是由于有机体内部的有限性造成的(Shenhav et al., 2017), 主要包括资源有限、工作记忆有限和表征能力有限。

首先, 有机体内部的资源有限。个体的内部资源会随着努力任务的强度和时间的增加成比例下降, 因此努力的付出会受到资源有限性的制约, 使得个体必须谨慎地付出努力以保存内部资源(Inzlicht & Schmeichel, 2012; Inzlicht et al., 2014)。有研究者认为努力消耗的内部资源是有机体中的血糖(Gailliot & Baumeister, 2007; Gailliot et al., 2007; Vadillo, Gold, & Osman, 2016)。例如, 当提供含葡萄糖的饮料时, 被试执行努力任务的疲劳程度会下降(Gailliot et al., 2007)。但该观点遭到了其他研究者的批评, 因为实验操作在提高被试的血糖浓度的同时, 也提高了被试的动机程度, 因而无法明确血糖在努力过程中的作用(Inzlicht et al., 2014; Vadillo et al., 2016)。另一种观点认为, 努力消耗的是有机体的星形胶质细胞糖原(Christie & Schrater, 2015), 但目前仍缺乏可靠的实验证据支持。另外, 最近的一项元分析表明, 努力并不依赖于资源的有限性(Carter, Kofler, Forster, & McCullough, 2015)。

其次, 努力活动一般都需要工作记忆的参与, 而工作记忆的容量是有限的(Oberauer, Farrell, Jarrold, & Lewandowsky, 2016)。因此, 个体在同一时间内执行任务的数量是有限的, 执行任务的成本包括执行该任务所需要的容量有限的工作记忆(Cowan, Rouder, Blume, & Saults, 2012)。

再次, 有机体的表征能力是有限的。执行努力任务需要调用不同的感觉通道, 但是有机体的感觉通道的数量是有限的, 从而导致个体在特定的时间内只能表征特定数量的信息(Musslick et al., 2016; Musslick, Shenhav, Botvinick, & Cohen, 2015)。研究表明, 信息加工通道之间的部分重叠会对同一时间内能够处理的信息的数量产生巨大的影响(Musslick et al., 2016; Zénon, Solopchuk, & Pezzulo, 2018)。因此, 有机体的表征能力的有限性也可能是努力成本的来源。

3.2 机会成本模型

相对于内部成本模型, 机会成本模型试图从收益与成本权衡的角度解释努力成本(Kurzban, Duckworth, Kable, & Myers, 2013)。该模型认为, 努力活动存在一个同时性的问题, 即并非所有的任务都能同时进行。个体在执行努力任务时会计算并比较不同任务的利益与成本, 使得特定时间内付出努力的预期效用最大化(Griffiths, Lieder, & Goodman, 2015; Musslick et al., 2015; Shenhav, Botvinick, & Cohen, 2013)。因此, 个体执行当前任务的机会成本是指在特定的时间内, 利用相同的心理过程执行另一效用最大的任务的潜在价值(Kurzban, 2016; Kurzban et al., 2013)。由于高努力任务往往需要花费更多的时间, 因此, 选择执行高努力任务意味着失去了完成其他任务的机会, 表现为一种机会成本。fMRI研究显示, 对努力任务的期待所激活的脑区与延迟折扣所激活的脑区存在重叠, 包括前扣带回与纹状体(Prévost et al., 2010), 提示努力折扣与更多的时间需求有关, 从而间接支持了机会成本模型。

机会成本模型本身存在两个主要问题(Kool & Botvinick, 2013)。首先, 该模型的充分性问题。尽管很多情境都存在显著的机会成本, 但是这些情境并未涉及到主观努力。其次, 机会成本模型无法合理地解释资源消耗效应, 即个体付出努力的意愿随着任务的进行而下降。根据机会成本模型, 在资源消耗效应中, 个体付出努力的意愿下降是由于执行其他可能任务的效用上升所致。 然而, 个体对于熟悉任务的效用的估计是一定的, 不太可能随着任务的进行而变化。 换言之, 资源消耗效应只可能发生在无法准确估计效用的新异任务中。事实上, 资源消耗效应不仅会发生在新异任务, 也会发生在熟悉任务中。

3.3 信号模型

信号模型认为, 随着任务的进行, 个体会产生疲劳、无聊等各种负性情绪, 而这些情绪反过来作为一种信号, 会促使个体将注意力从当前的任务转移到具有更高内部效用的任务(Inzlicht & Schmeichel, 2012; Inzlicht et al., 2014)。因此, 个体选择高努力任务的意愿取决于外部的奖赏是否足以抵消继续执行当前任务所付出的成本(Inzlicht, Bartholow, & Hirsh, 2015)。

信号模型过于强调努力产生的负性情绪对努力行为的影响, 忽略了努力带来的正性情感的作用。事实上, 个体付出努力的动机往往是获得正性奖赏(趋利)或者逃避负性刺激(避害)。 因此, 个体的努力虽然受到负性情感信号的影响, 但是努力过程中产生的正性情感, 例如愉悦、成就感等, 能够降低甚至抵消努力产生的固有的负性情感, 从而促进个体的努力行为。因此, 信号模型对努力带来的负性情感的强调存在一定的局限性。

3.4 小结

针对“努力作为一种成本”的实证性证据, 研究者们提出了不同的理论模型, 试图从不同的角度解释其内在机制。不难看出, 这些理论模型具有两个共同特点:(1)这些理论更多的是从努力本身的属性考虑, 强调努力本身对个体执行任务的意愿的影响; (2)从努力的时间进程来说, 这些理论更多地关注了任务执行前的个体的心理活动, 因此, “努力是一种成本”这一假设具有前瞻性的特点, 即个体执行任务前, 通过成本与收益的权衡, 决定是否执行高努力任务。

4 努力增加价值

与“努力是一种成本”的观点相悖, “努力是一种奖赏”近年来引起了研究者的关注, 同样得到大量实验证据的支持。

动物研究发现, 努力会提高动物对奖赏的偏好。例如, 大鼠在经过高努力和低努力任务训练后, 在随后的选择任务中表现出了对高努力结果的明显偏好(Armus, 1999; Johnson & Gallagher, 2011)。类似的现象也出现在鸽子(Clement, Feltus, Kaiser, & Zentall, 2000; Zentall, 2016)、椋鸟(Kacelnik & Marsh, 2002), 甚至是无脊椎动物(Czaczkes, Brandstetter, di Stefano, & Heinze, 2018; Pompilio, Kacelnik, & Behmer, 2006)当中。这些研究表明“努力增加价值”这种现象表现出了明显的跨物种性。

人类行为学实验表明, 相对于意外之财或付出较低努力获得的奖赏, 被试更不愿意消费通过较高努力获得的奖赏(Muehlbacher & Kirchler, 2009), 也不愿意以这些奖赏作为筹码, 去参与后续高风险的赌博任务(Arkes et al., 1994; Schmidta et al., 2017)。宜家效应(IKEA effect)表明, 相对于专家制作的产品, 个体更愿意花费较多的金钱去购买自己制作的产品(Mochon, Norton, & Ariely, 2012; Norton, Mochon, & Ariely, 2012; Sarstedt, Neubert, & Barth, 2017)。类似地, 习得性勤奋(learned industriousness)现象表明, 不仅先前付出的努力能够提高个体行为结果的价值, 而且努力本身就可以作为一种次级强化物(Eisenberger, 1992)。

fMRI证据表明, 相同的奖赏在通过高努力获得时, 与通过低努力获得时相比, 会引起伏隔核、纹状体等奖赏相关的脑区更强的激活(Hernandez Lallement et al., 2014; Vassena et al., 2014); 进一步的证据表明, 在个体主动选择的条件下, 高努力条件诱发了更强的腹侧纹状体的激活(Schouppe, Demanet, Boehler, Ridderinkhof, & Notebaert, 2014), 对于高努力任务的期待激活了背侧纹状体(Kurniawan et al., 2013); 个体的额叶活动越强, 其更愿意付出努力(Hughes, Yates, Morton, & Smillie, 2015)。类似地, 最近的一项EEG研究表明, 与低努力条件相比, 高努力条件诱发了更强的表征奖赏期待的刺激前负波(stimulus-preceding negativity, SPN)和表征奖赏结果的RewP的幅值(Ma et al., 2014; Wang et al., 2017)。

总之, 各个方面的证据均表明, 努力不仅仅是一种成本, 而且也是一种奖赏, 能够增加努力结果的价值。 在某些情境下, 努力本身甚至会演变成为一种次级强化物。同样地, 研究者们提出了许多理论模型来解释努力对奖赏的促进作用。

4.1 认知失调和努力的合理化模型

认知失调模型认为, 个体信念和行为的不一致会导致个体改变自己的信念, 从而降低由于这种不一致带来的心理冲突(Festinger, 1962)。作为认知失调的一种特殊形式, 努力的合理化是指, 个体倾向于认为需要更多努力获得的结果具有更高的价值, 从而使得先前付出的努力合理化(Aronson & Mills, 1959)。努力的合理化模型能够很好地解释生活中或实验研究中的某些现象。例如, 儿童更不愿意将自己通过高努力获得的奖赏分给陌生人, 是因为他们在获得奖赏后对自己付出的努力和奖赏的价值进行了重新评价, 赋予了高努力结果更高的价值(Benozio & Diesendruck, 2015)。高努力条件下获得的奖赏诱发了奖赏相关脑区的激活增强, 也表明高努力结果价值的增加(Hernandez Lallement et al., 2014; Vassena et al., 2014)。然而, 进一步的研究表明, 努力的合理化是有条件的。例如, 宜家效应在个体无法完成产品制作时消失(Mochon et al., 2012; Norton et al., 2012; Sarstedt et al., 2017)。因此, 只有在个体能力范围之内, 努力才能增加其行为结果的价值, 这种增值效应可能与完成任务诱发了更为积极的心理品质有关(Norton et al., 2012), 包括自豪感、心理所有权等(Sarstedt et al., 2017)。

努力的合理化模型的不足在于并未考虑努力本身的属性。试次内对比效应表明, 个体在执行高努力任务或延迟折扣任务之后, 均表现出对该任务结果的偏好(Alessandri, Darcheville, Delevoye-Turrell, & Zentall, 2008)。这说明努力与延迟折扣具有类似的属性, 即努力本身是一种成本, 努力导致的主观价值的增加可能是个体完成任务之后对高努力任务的一种合理化解释。

4.2 习得性勤奋理论

习得性勤奋理论认为, 在现实情境中, 高努力往往与更高的奖赏同时出现, 高努力通过强化作用与高奖赏不断匹配, 久而久之, 其本身成为一种次级强化物(Eisenberger, 1992)。该理论将现实情境进一步分为练习情境和转化情境。在练习情境中, 通过条件作用对高努力不断强化; 在转化情境中, 高努力成为次级奖赏使得个体更愿意付出努力。

习得性勤奋理论能够解释许多现象。例如, 与受到低努力强化(通过平地获得食物)的小鼠相比, 受到高努力强化(通过斜坡获得食物)的小鼠在接下来的决策任务中更倾向于选择与高努力对应的奖赏(Armus, 1999); 完成认知需求任务而获得奖赏的学生, 在接下来的无关任务中能够坚持更长的时间(Eisenberger & Leonard, 1980)。换句话说, 个体所付出的努力在先前的任务中(练习情境)被强化, 从而在接下来的任务中(转化情境)成为一种次级强化物, 进而增加了高努力任务的价值。另外, 习得性勤奋理论表现出了一定的生态效度。Giammittorio (2017)将习得性勤奋理论运用到脑损伤病人的恢复中, 结果表明, 努力训练能够有效地提高脑损伤个体的适应性行为。Bustamante, Davis和Marquez (2014)等人招募了80名被试, 在练习情境中, 分别对高、低认知努力和高、低体力努力进行强化, 但被试在随后的心理持续任务中(转化情境)的表现只在高、低体力努力强化组中出现差异, 表明习得性勤奋理论在不同的努力类型之间存在差异。

4.3 认知需求理论

认知需求理论强调了认知需求特质与努力之间的关系。认知需求特质是指个体表现出来的一种参与和享受认知努力的、具有跨时间和情境的稳定倾向性(Cacioppo, Petty, Feinstein, & Jarvis, 1996; Hill & Aita, 2018)。认知需求越高的个体, 更愿意参与认知努力活动, 并且更加享受努力的过程和结果。同时, 该特质可以预测个体处理任务和社会信息的方式(Cacioppo et al., 1996; Cacioppo, Petty, & Kao, 1984)。

认知需求理论得到了实证性证据的支持。认知需求量表得分越高的个体, 更不愿意为了逃避高努力任务而放弃奖赏(Westbrook et al., 2013)、在具有挑战性的任务中更愿意付出较多的努力并能坚持更长的时间(Hill, Rohling, Boettcher, & Meyers, 2013)、在奖励任务中对外部金钱诱因的敏感性低于认知需求量表得分较低的个体(Sandra & Otto, 2018)。这些证据都表明, 高认知需求的个体赋予了认知努力更高的内部价值(Cacioppo et al., 1996; Sandra & Otto, 2018), 使得个体参与并享受、而非逃避努力。这也能够解释生活中为什么有些人喜欢爬山、数独以及围棋等需要付出较高努力的活动。认知需求理论强调努力本身具有更高的内部价值。事实上, 作为一种特质, 认知需求在不同的个体之间存在较大的差异, 因此该理论本身存在一定的缺陷, 难以推广到所有人群和状态性的实验室研究中。

4.4 小结

与“努力作为一种成本”的观点类似, “努力作为一种奖赏”同样得到大量的实证性证据支持。这些理论模型的共同特点包括:(1)努力增加的价值更多的是对努力的结果而言。尽管习得性勤奋理论认为努力本身可以作为一种次级强化物, 但这也是由于努力结果的强化所导致的; (2)从努力的时间进程来说, 努力增加价值更多的是在完成任务之后, 即努力回溯性地增加了行为结果的价值。

5 总结与展望

努力作为一种调节机制, 到底是一种成本还是一种奖赏呢?综上所述, 这两种观点均有相应的实证性证据和理论模型支持, 并表现出了稳定的跨物种性。一方面, 努力本身需要消耗资源, 个体倾向于避免付出努力, 只有增加奖赏值个体才会增加其努力的程度, 因而努力作为一种成本, 能够降低价值; 另一方面, 个体更加珍视通过努力获得的结果, 甚至努力本身会作为一种次级强化物, 因而努力能够增加价值。近年来, 尽管研究者对努力进行了大量的研究, 但对努力的心理机制和功能意义的了解还远远不够。在未来的研究中, 研究者们需要解决以下问题:

第一, 对努力进行准确的定义。如前所述, 尽管许多研究者试图对努力进行定义, 但是当前关于努力, 特别是认知努力的定义仍然很不明确。由于缺乏清晰的操作性定义, 往往导致努力相关的研究混淆了其他的心理因素。例如, 有研究将难度作为努力的操作定义, 考察努力对于SPN等EEG指标的影响(Wang et al., 2017)。由于高难度混淆了高不确定性, 而SPN波幅对信息的不确定性异常敏感, 因此无法确定努力条件下SPN成分的增大是由于个体的高努力造成的, 还是由于难度导致的不确定性造成。因此, 对努力进行统一而准确的定义, 是后续研究的前提条件。

第二, 整合现有的关于努力的理论模型。目前关于努力的两种主流观点虽然获得了多方面证据的支持, 但是二者均无法单独解释生活中的现象和实验室结果, 因此需要对现有的理论模型进行系统地整合。结合前文所述, 我们认为, 从努力的时间进程上对努力的理论进行整合可能是一条有效的途径。事实上, 两种理论模型关注的时间点并不一致, “努力是一种成本”更多的是从努力的期待阶段进行考虑, 相关证据大多来自于个体执行努力任务之前, 换而言之, “努力是一种成本”从时间进程上来说具有前瞻性的特点; 而“努力增加价值”, 更多的是从努力的评价阶段进行考虑, 相关证据大多来自于个体完成努力任务之后, 因此, “努力增加价值”从时间进程上来说具有回溯性的特点。现有的理论框架尚未从时间进程的角度对努力的理论模型进行整合。因此, 未来的研究可以尝试在同一实验研究中同时考察期待阶段和评价阶段努力的奖赏效应。

第三, 从认知控制系统与奖赏系统相互制衡的角度理解努力的价值。如前文所述, 一方面, 努力不是自动化的过程, 需要调用一定的认知资源, 进而激活与认知控制相关的脑区, 如前扣带回、背内侧前额叶等; 另一方面, 努力会激活与奖赏系统相关的脑区, 如腹侧纹状体、伏隔核等。由于认知控制系统与奖赏系统存在制衡关系(Heatherton & Wagner, 2011; Metcalfe & Mischel, 1999), 因此, 未来的研究有必要利用脑成像等技术手段从认知控制系统与奖赏系统相互制衡的角度进一步理解努力的价值。

第四, 当前理论需要负性情境下的实验证据的支持。当前关于努力的研究大多以获得奖赏为前提, 即大都是在正性情境中进行的。然而, 在现实生活中, 努力的目的不仅仅是获得奖赏, 还具有逃避危险的功能。例如, 人类努力避免惩罚, 动物努力逃避捕食者的追捕等。在经典的延迟折扣和概率折扣任务中, 正性条件下的折扣率往往高于负性条件(Benzion, Rapoport, & Yagil, 1989; Thaler, 1981)。因此, 有理由相信, 负性情境中的努力效应可能会表现出与正性情境中不同的模式。考察不同情境中的努力效应对现有的理论将是一个有力的补充。

第五, 开发更为全面和可靠的努力测量工具。近年来, 研究者们开发了努力耗费奖赏任务(The Effort Expenditure for Rewards Task)、认知努力折扣范式(The Cognitive Effort Discounting Paradigm)等客观的努力测量工具(Treadway et al., 2009; Westbrook & Braver, 2015; Westbrook et al., 2013)。这些工具虽然都获得了较大的成功, 但是其理论前提并未跳出“努力作为一种成本”的框架, 因此使得测量结果不可避免地产生了偏向性。另一方面, 尽管主观测量工具如认知需求量表(Need for Cognition Scale)、美国航空航天局任务负荷指数(NASA Task Load Index)等量表已经在努力的研究中被大量使用, 但由于这些工具的初衷并非测量努力本身, 因此其信效度仍然有待检验。例如, 有研究发现, 美国航空航天局任务负荷指数得分并非努力的主观价值的稳定预测因子(Westbrook et al., 2013)。

第六, 考察努力的个体差异。最近的研究表明, 与低认知需求个体相比, 高认知需求个体赋予了努力更高的内部价值、表现出了更高的奖赏敏感性以及更强的付出努力的动机(Sandra & Otto, 2018); 老年个体付出努力的意愿和对努力结果的评价与年轻个体相比存在显著差异(Hess & Ennis, 2012; Westbrook et al., 2013); 不同年龄段的儿童对努力结果的评价也有明显的不同(Benozio & Diesendruck, 2015); 个体付出努力的意愿与个体的能力存在密切的关系(Sandra & Otto, 2018)。也就说是, 努力效应可能受到个体差异的影响, 如人格特质、年龄、能力, 甚至是病理特征。因此, 从个体差异的角度开展研究, 将有助于我们更为深入地理解努力的心理结构和功能意义。

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Amotivational states and insufficient recruitment of mental effort have been observed in a variety of clinical populations, including depression, traumatic brain injury, post-traumatic stress disorder, and attention deficit hyperactivity disorder. Previous rodent models of effort-based decision making have utilized physical costs whereas human studies of effort are primarily cognitive in nature, and it is unclear whether the two types of effortful decision making are underpinned by the same neurobiological processes. We therefore designed a novel rat cognitive effort task (rCET) based on the 5-choice serial reaction time task, a well-validated measure of attention and impulsivity. Within each trial of the rCET, rats are given the choice between an easy or hard visuospatial discrimination, and successful hard trials are rewarded with double the number of sugar pellets. Similar to previous human studies, stable individual variation in choice behavior was observed, with 'workers' choosing hard trials significantly more than their 'slacker' counterparts. Whereas workers 'slacked off in response to administration of amphetamine and caffeine, slackers 'worked harder' under amphetamine, but not caffeine. Conversely, these stimulants increased motor impulsivity in all animals. Ethanol did not affect animals' choice but invigorated behavior. In sum, we have shown for the first time that rats are differentially sensitive to cognitive effort when making decisions, independent of other processes such as impulsivity, and these baseline differences can influence the cognitive response to psychostimulants. Such findings could inform our understanding of impairments in effort-based decision making and contribute to treatment development. Neuropsychopharmacology (2012) 37, 1825-1837; doi:10.1038/npp.2012.30; published online 28 March 2012

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Our central goal is to provide a definition of boredom in terms of the underlying mental processes that occur during an instance of boredom. Through the synthesis of psychodynamic, existential, arousal, and cognitive theories of boredom, we argue that boredom is universally conceptualized as "the aversive experience of wanting, but being unable, to engage in satisfying activity." We propose to map this conceptualization onto underlying mental processes. Specifically, we propose that boredom be defined in terms of attention. That is, boredom is the aversive state that occurs when we (a) are not able to successfully engage attention with internal (e.g., thoughts or feelings) or external (e.g., environmental stimuli) information required for participating in satisfying activity, (b) are focused on the fact that we are not able to engage attention and participate in satisfying activity, and (c) attribute the cause of our aversive state to the environment. We believe that our definition of boredom fully accounts for the phenomenal experience of boredom, brings existing theories of boredom into dialogue with one another, and suggests specific directions for future research on boredom and attention.

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Background: Decision-making studies show that response selection is influenced by the "effort cost" associated with response alternatives. These effort-cost calculations seem to be mediated by a distributed neural circuit including the anterior cingulate cortex and subcortical targets of dopamine neurons. On the basis of evidence of dysfunction in these systems in schizophrenia (SZ), we examined whether effort-cost computations were impaired in SZ patients and whether these deficits were associated with negative symptoms.
Methods: Effort-cost decision-making performance was evaluated in 44 patients with SZ and 36 demographically matched control subjects. Subjects performed a computerized task where they were presented with a series of 30 trials in which they could choose between making 20 button presses for $1 or 100 button presses for higher amounts (varying from $3 to $7 across trials). Probability of reward receipt was also manipulated to determine whether certain (100%) or uncertain (50%) reward affected effort-based decision-making.
Results: Patients were less likely than control subjects to select the high-effort response alternative during the 100% probability condition, particularly when the value payoff was highest (i.e., $6 and $7). Patients were also less likely to select the high-effort option on trials after reward in the 50% probability condition. Furthermore, these impairments in effort-cost computations were greatest among patients with elevated negative symptoms. There was no association with haloperidol equivalent dosage.
Conclusions: The motivational impairments of SZ might be associated with abnormalities in estimating the "cost" of effortful behavior. This increased effort cost might undermine volition.

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Self-regulatory failure is a core feature of many social and mental health problems. Self-regulation can be undermined by failures to transcend overwhelming temptations, negative moods and resource depletion, and when minor lapses in self-control snowball into self-regulatory collapse. Cognitive neuroscience research suggests that successful self-regulation is dependent on top-down control from the prefrontal cortex over subcortical regions involved in reward and emotion. We highlight recent neuroimaging research on self-regulatory failure, the findings of which support a balance model of self-regulation whereby self-regulatory failure occurs whenever the balance is tipped in favor of subcortical areas, either due to particularly strong impulses or when prefrontal function itself is impaired. Such a model is consistent with recent findings in the cognitive neuroscience of addictive behavior, emotion regulation and decision-making.

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It is ecologically adaptive that the amount of effort invested to achieve a reward increases the relevance of the resulting outcome. Here, we investigated the effect of effort on activity in reward and loss processing brain areas by using functional magnetic resonance imaging. In total, 28 subjects were endowed with monetary rewards of randomly varying magnitude after performing arithmetic calculations that were either difficult (high effort), easy (low effort) or already solved (no effort). Subsequently, a forced donation took place, where a varying part of the endowment was transferred to a charity organization, causing a loss for the subject. Results show that reward magnitude positively modulates activity in reward-processing brain areas (subgenual anterior cingulate cortex and nucleus accumbens) only in the high effort condition. Furthermore, anterior insular activity was positively modulated by loss magnitude only after high effort. The results strongly suggest an increasing relevance of outcomes with increasing previous effort.

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This study examined intra-individual variability in a large sample (n 629) of individuals with a history of mild traumatic brain injury (mTBI) or TBI referred for neuropsychological evaluation. Variability was assessed using the overall test battery mean standard deviation (OTBM SD). We found a negative linear relation between OTBM and OTBM SD (r .672) in this sample with a history of neurologic pathology, indicating that the variability is inversely related to cognitive performance and contrary to what is observed in most normative data. Analyses revealed main effects for OTBM and OTBM SD across three TBI severity groups: loss of consciousness (LOC) 1 h, LOC 1 h6 days, and LOC 6 days. These effects were found for both a valid performance group (no failed embedded validity measures; n 504) and an invalid performance group (failed one or more embedded validity measures; n 125). These findings support that cognitive intra-individual variability is increased uniquely by both neuropathology and suboptimal effort, there is a doseresponse relationship between neuropathology and cognitive variability, and intra-individual variability may have utility as a clinical index of both.

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According to the resource model of self-control, overriding one's predominant response tendencies consumes and temporarily depletes a limited inner resource. Over 100 experiments have lent support to this model of ego depletion by observing that acts of self-control at Time 1 reduce performance on subsequent, seemingly unrelated self-control tasks at Time 2. The time is now ripe, therefore, not only to broaden the scope of the model but to start gaining a precise, mechanistic account of it. Accordingly, in the current article, the authors probe the particular cognitive, affective, and motivational mechanics of self-control and its depletion, asking, "What is ego depletion?" This study proposes a process model of depletion, suggesting that exerting self-control at Time 1 causes temporary shifts in both motivation and attention that undermine self-control at Time 2. The article highlights evidence in support of this model but also highlights where evidence is lacking, thus providing a blueprint for future research. Though the process model of depletion may sacrifice the elegance of the resource metaphor, it paints a more precise picture of ego depletion and suggests several nuanced predictions for future research.

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Self-control refers to the mental processes that allow people to override thoughts and emotions, thus enabling behavior to vary adaptively from moment to moment. Dominating contemporary research on this topic is the viewpoint that self-control relies upon a limited resource, such that engaging in acts of restraint depletes this inner capacity and undermines subsequent attempts at control (i.e., ego depletion). Noting theoretical and empirical problems with this view, here we advance a competing model that develops a non-resource-based account of self-control. We suggest that apparent regulatory failures reflect the motivated switching of task priorities as people strive to strike an optimal balance between engaging cognitive labor to pursue 'have-to' goals versus preferring cognitive leisure in the pursuit of 'want-to' goals.

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Kurzban and colleagues carry forward an important contemporary movement in cognitive control research, tending away from resource-based models and toward a framework focusing on motivation or value. However, their specific proposal, centering on opportunity costs, appears problematic. We favor a simpler view, according to which the exertion of cognitive control carries intrinsic subjective costs.

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Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries an opportunity cost-that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished.

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We examine the underlying process behind the IKEA effect, which is defined as consumers' willingness to pay more for self-created products than for identical products made by others, and explore the factors that influence both consumers' willingness to engage in self-creation and the utility that they derive from such activities. We propose that creating products fulfills consumers' psychological need to signal competence to themselves and to others, and that feelings of competence associated with self-created products lead to their increased valuation. We demonstrate that the feelings of competence that arise from assembling products mediate their increased value (Experiment 1), that affirming consumers' sense of self decreases the value they derive from their creations (Experiment 2), and that threatening consumers' sense of self increases their propensity to Make things themselves (Experiments 3A and 3B). (C) 2012 Elsevier B.V. All rights reserved.

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Magsci     [本文引用: 3]

In four studies in which consumers assembled IKEA boxes, folded origami, and built sets of Legos, we demonstrate and investigate boundary conditions for the IKEA effect-the increase in valuation of self-made products. Participants saw their amateurish creations as similar in value to experts' creations, and expected others to share their opinions. We show that labor leads to love only when labor results in successful completion of tasks; when participants built and then destroyed their creations, or failed to complete them, the IKEA effect dissipated. Finally, we show that labor increases valuation for both "do-it-yourselfers" and novices. (C) 2011 Society for Consumer Psychology. Published by Elsevier Inc. All rights reserved.

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Magsci     [本文引用: 1]

Decision-making involves weighing costs against benefits, for instance, in terms of the effort it takes to obtain a reward of a given magnitude. This evaluation process has been linked to the dorsal anterior cingulate cortex (dACC) and the striatum, with activation in these brain structures reflecting the discounting effect of effort on reward. Here, we investigate how cognitive effort influences neural choice processes in the absence of an extrinsic reward. Using functional magnetic resonance imaging in humans, we used an effort-based decision-making task in which participants were required to choose between two options for a subsequent flanker task that differed in the amount of cognitive effort. Cognitive effort was manipulated by varying the proportion of incongruent trials associated with each choice option. Choice-locked activation in the striatum was higher when participants chose voluntarily for the more effortful alternative but displayed the opposite trend on forced-choice trials. The dACC revealed a similar, yet only trend-level significant, activation pattern. Our results imply that activation levels in the striatum reflect a cost-benefit analysis, in which a balance is made between effort discounting and the intrinsic motivation to choose a cognitively challenging task. Moreover, our findings indicate that it matters whether this challenge is voluntarily chosen or externally imposed. As such, the present findings contrast with classical findings on effort discounting that found reductions in striatum activation for higher effort by finding enhancements of the same neural circuits when a cognitively challenging task is voluntarily selected and does not entail the danger of losing reward.

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.

[本文引用: 1]

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.

[本文引用: 3]

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Psychological and neural mechanisms associated with effort-related cardiovascular reactivity and cognitive control: An integrative approach

International Journal of Psychophysiology,119 11-18.

[本文引用: 1]

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Complementary roles of different oscillatory activities in the subthalamic nucleus in coding motor effort in Parkinsonism

Experimental Neurology,248 187-195.

[本文引用: 2]

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High self-control predicts good adjustment, less pathology, better grades, and interpersonal success

Journal of Personality,72(2), 271-324.

[本文引用: 1]

Thaler R. (1981).

Some empirical evidence on dynamic inconsistency

Economics Letters,8(3), 201-207.

[本文引用: 1]

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Boredom and psychotic disorders: Cognitive and motivational issues

Psychiatry,66(2), 146-167.

[本文引用: 1]

Treadway M. T., Bossaller N. A., Shelton R. C., & Zald D. H . (2012).

Effort-based decision-making in major depressive disorder: A translational model of motivational anhedonia

Journal of Abnormal Psychology,121(3), 553-558.

Magsci     [本文引用: 1]

Anhedonia is a core feature of major depressive disorder (MDD), but the precise nature of anhedonic symptoms is unknown. Whereas anhedonia has traditionally been viewed as a deficit in the experience of pleasure, more recent evidence suggests that reduced anticipation and motivation may also be a core feature of this symptom. Here, we provide data from a study in MDD patients and healthy controls using a translational measure of reward motivation, the Effort Expenditure for Rewards Task (EEfRT or "effort"). This task offers subjects a series of trials where they may choose to expend more or less effort for the opportunity to win varying amounts of monetary rewards. We found that MDD patients were less willing to expend effort for rewards than controls. Additionally, we observed that patients were less able to effectively use information about magnitude and probability of rewards to guide their choice behavior. Finally, within the MDD patient group, duration of the current episode was a significant negative predictor of EEfRT task performance. These findings offer novel support for theoretical models proposing that anhedonia in MDD may reflect specific impairments in motivation and reward-based decision-making.

Treadway M. T., Buckholtz J. W., Schwartzman A. N., Lambert W. E., & Zald D. H . (2009).

Worth the 'EEfRT'? The effort expenditure for rewards task as an objective measure of motivation and anhedonia

PLoS One,4(8), e6598.

[本文引用: 3]

Vadillo M. A., Gold N., & Osman M . (2016).

The bitter truth about sugar and willpower: The limited evidential value of the glucose model of ego depletion

Psychological Science,27(9), 1207-1214.

[本文引用: 2]

Vassena E., Holroyd C. B., & Alexander W. H . (2017).

Computational models of anterior cingulate cortex: At the crossroads between prediction and effort

Frontiers in Neuroscience,11(316), 316.

[本文引用: 1]

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Overlapping neural systems represent cognitive effort and reward anticipation

PLoS One,9(3), e91008.

[本文引用: 3]

Wallis J. D., &Rushworth M. F. S. ,(2014) .Integrating benefits and costs in decision making. In P. W. Glimcher & E. Fehr (Eds.), Neuroeconomics (Second Edition) (pp. 411-433). San Diego: Academic Press.

[本文引用: 1]

Wang J., Huang J., Yang X-H., Lui S. S. Y Cheung E. F. C., &Chan R. C. K ., (2015).

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Schizophrenia Research,168(1-2), 465-474.

[本文引用: 2]

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Effort provides its own reward: Endeavors reinforce subjective expectation and evaluation of task performance

Experimental Brain Research,235(4), 1107-1118.

[本文引用: 3]

Wardle M. C., Treadway M. T., Mayo L. M., Zald D. H., & de Wit H . (2011).

Amping up effort: Effects of d-amphetamine on human effort-based decision-making

Journal of Neuroscience,31(46), 16597-16602.

Magsci     [本文引用: 1]

Animal studies suggest the neurotransmitter dopamine (DA) plays an important role in decision-making. In rats, DA depletion decreases tolerance for effort and probability costs, while drugs enhancing DA increase tolerance for these costs. However, data regarding the effect of DA manipulations on effort and probability costs in humans remain scarce. The current study examined acute effects of d-amphetamine, an indirect DA agonist, on willingness of healthy human volunteers to exert effort for monetary rewards at varying levels of reward value and reward probability. Based on preclinical research, we predicted amphetamine would increase exertion of effort, particularly when reward probability was low. Over three sessions, 17 healthy normal adults received placebo, d-amphetamine 10 mg, and 20 mg under counterbalanced double-blind conditions and completed the Effort Expenditure for Rewards Task. Consistent with predictions, amphetamine enhanced willingness to exert effort, particularly when reward probability was lower. Amphetamine did not alter effects of reward magnitude on willingness to exert effort. Amphetamine sped task performance, but its psychomotor effects were not strongly related to its effects on decision-making. This is the first demonstration in humans that dopaminergic manipulations alter willingness to exert effort for rewards. These findings help elucidate neurochemical substrates of choice, with implications for neuropsychiatric diseases characterized by dopaminergic dysfunction and motivational deficits.

Westbrook A. &Braver T.S . (2015).

Cognitive effort: A neuroeconomic approach

Cognitive,Affective, & Behavioral Neuroscience, 15(2), 395-415.

[本文引用: 4]

Westbrook A., Kester D., & Braver T. S . (2013).

What is the subjective cost of cognitive effort? Load, trait, and aging effects revealed by economic preference

PLoS One,8(7), e68210.

[本文引用: 5]

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Diminished caudate and superior temporal gyrus responses to effort-based decision making in patients with first-episode major depressive disorder

Progress in Neuro-Psychopharmacology and Biological Psychiatry,64 52-59.

[本文引用: 1]

Zénon A., Solopchuk O., & Pezzulo G . (2019).

An information-theoretic perspective on the costs of cognition

Neuropsychologia,123 5-18.

[本文引用: 1]

Zentall T. . (2016).

Cognitive dissonance or contrast?

Animal Sentience: An Interdisciplinary Journal on Animal Feeling,12(1), 1.

[本文引用: 1]

Zhang Y., Li Q., Wang Z., Liu X., & Zheng Y . (2017).

Temporal dynamics of reward anticipation in the human brain

Biological Psychology,128 89-97.

[本文引用: 2]

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