Advances in Psychology
Vol. 12  No. 02 ( 2022 ), Article ID: 48500 , 9 pages
10.12677/AP.2022.122043

情绪对决策的影响及其神经机制

夏诗环

重庆师范大学教育科学学院,重庆

收稿日期:2021年12月23日;录用日期:2022年1月22日;发布日期:2022年1月29日

摘要

情绪对人类的认知过程、决策行为起到了重要的作用。关于情绪影响决策的研究已有许多有价值的成果,目前研究主要基于效价和ATF理论进行探索。但是大多数研究主要还停留于揭示情绪影响决策的认知机制,对其神经机制的探索还尚有不足。另外,尽管有研究开始逐步探讨如何降低情绪对决策的影响,但是这些研究还有待深入和全面探索。综合行为和神经机制的研究,将有助于更好地理解情绪与决策间的关系和控制情绪。未来研究应该增加情绪影响决策的深度和广度,更多地结合ERP和fMRI技术探讨其内在的神经机制,积极探索控制情绪对决策影响的因素。

关键词

情绪,决策,ATF理论,ERP,fMRI

The Influence of Emotion on Decision-Making and Its Neural Mechanism

Shihuan Xia

School of Educational Science, Chongqing Normal University, Chongqing

Received: Dec. 23rd, 2021; accepted: Jan. 22nd, 2022; published: Jan. 29th, 2022

ABSTRACT

Emotions play an important role in human cognitive process and decision-making behavior. There have been many valuable results in the research on emotion affecting decision-making, and the current research is mainly based on the valence and ATF theory. However, most of the studies still focus on revealing the cognitive mechanism of emotion affecting decision-making, and the exploration of its neural mechanism is still insufficient. In addition, although some studies have begun to gradually explore how to reduce the influence of emotions on decision-making, these studies need to be further and comprehensive. Comprehensive behavioral and neural mechanism research will help to better understand the relationship between emotion and decision-making and control emotion. Future research should increase the depth and breadth of emotional impact on decision-making, explore the underlying neural mechanisms by combining ERP and fMRI techniques, and actively explore the factors that control the impact of emotions on decision-making.

Keywords:Emotion, Decision-Making, ATF Theory, ERP, fMRI

Copyright © 2022 by author(s) and Hans Publishers Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

1. 引言

情绪在人类社会活动中具有重要的适应性功能,它帮助我们调节和适应当前环境的变化。人类情感研究一直是心理学领域研究的重点和热点,它对人类的认知过程、决策行为起到了重要的作用。情绪对决策的研究主要集中于两个方面,情绪效价和情绪核心评价(Lerner et al., 2015; Suo et al., 2021)对人类决策行为的影响。基于情绪效价理论的研究认为正性情绪和负性情绪会引发个体不同的判断和决策行为,积极情绪导致个体做出乐观判断,而消极情绪导致个体做出悲观判断(Han et al., 2007; Keltner & Lerner, 2010; Loewenstein & Lerner, 2003)。与基于效价的理论不同,评价倾向框架理论(appraisal-tendency framework, ATF, Lerner & Keltner, 2000, 2001; Lerner et al., 2015)认为情绪与具体的评价相关,情绪一旦被激活,就会触发一种认知倾向,并根据触发该情绪的核心评价维度(确定性、控制感)来评估未来事件,进而影响决策行为。根据ATF理论,情绪对决策判断的影响不应该简单地仅从效价维度来探讨,而应该聚焦于情绪触发的评价倾向,比如同为消极情绪的悲伤、愤怒和恐惧,愤怒具有高确定性和控制感,而悲伤和恐惧具有较低确定性和控制感(Smith & Ellsworth, 1985; Lerner & Keltner, 2001)。因此在跨期决策和风险决策中,研究者发现情绪核心评价维度影响了个体的决策行为,在愤怒情绪影响下,个体偏爱于延迟选择和做出风险博弈,在悲伤和恐惧情绪下,偏爱于即刻选择和规避风险(宋锡妍等,2021;Lerner & Keltner, 2001; Yang et al., 2020; Suo et al., 2021)。无论是基于效价或基于ATF理论,情绪对决策的研究成果都越来越丰富,越来越深入。但是这些研究目前还主要着重于揭示情绪影响决策的认知机制,对其内在的神经机制探讨还不够丰富。因此本文将首先梳理情绪对决策影响的认知机制,其次主要梳理在情绪影响决策过程中涉及的神经机制,以便于我们更好地理解情绪与决策间的关系及其内在机制,最后探讨了改变情绪影响决策的因素。

2. 情绪影响决策的认知机制

近年来,对情绪和决策科学相互结合的研究急剧增加。就直觉经验来说,情绪一定影响决策,比如前一天晚上经历分手的个体很难在第二天的文献报告中表现很好。在过去的研究中,研究者致力于探讨决策对情绪的影响及其内在机制(Carter & McBride, 2013; Kassam, Morewedge, Gilbert, & Wilson, 2011; Kermer, Driver-Linn, Wilson, & Gilbert, 2006; McGraw, Larsen, Kahneman, & Schkade, 2010; Mellers, Schwartz, Ho, & Ritov, 1997; Rutledge, Skandali, Dayan, & Dolan, 2014; Yechiam, Telpaz, & Hochman, 2014)。但是关于情绪对决策的影响以及情绪如何影响决策的研究还相对较少。事实上,许多心理学家都认为情绪是驱动个体做出生活中重要意义决定的驱动因素(e.g., Ekman, 2007; Frijda, 1988; Gilbert, 2006; Keltner et al., 2014; Keltner & Lerner, 2010; Lazarus, 1991; Loewenstein et al., 2001; Scherer & Ekman, 1984)。此外即使是无意识下的情绪信息也会影响决策行为,甚至提高决策判断的准确率和置信度(Lufityanto, Donkin, & Pearson, 2016)。近年来,尽管研究者探讨情绪与决策关系的角度各异,但是都有一个相同的基本观点,即情绪广泛地、有效地影响着人们的决策(Lerner et al., 2015)。情绪影响个体决策的理性和行为,如愤怒激发个体对不公平事件反应的动机(Solomon, 1993),对后悔的提前预期使个体做出规避风险的决策行为(Loomes & Sugden, 1982)。情绪对决策的影响主要基于两个方面,效价理论和评价倾向框架理论(ATF)。

2.1. 情绪效价对决策行为的影响

基于情绪效价的研究将情绪分为积极情绪和消极情绪,并假定相同效价的情绪对决策行为产生相同的效应,积极情绪使个体做出乐观的判断,而消极情绪使个体做出悲观的判断(Han et al., 2007; Keltner & Lerner, 2010; Loewenstein & Lerner, 2003)。根据情绪效价对决策影响的假设,Johnson和Tversky (1983)首次实证研究发现,与阅读积极故事的被试相比,阅读消极故事的被试做出更为悲观的判断。随后的研究也发现类似的效应,如在晴天时人们具有更高的生活满意度和幸福感(Schwarz & Clore, 1983);26个国家的股市表现与日照量呈正相关(Hirshleifer & Shumway, 2003; Kamstra et al., 2003);当输掉世界杯足球比赛时,该国的股票回报率就会下降(Edmans et al., 2007),最近的研究也表明,当天气或者运动赛事好于预期时,人们会更愿意进行赌博行为(Otto et al., 2016)。消极情绪状态下个体愿意接受较小且即时的奖励,而积极情绪状态下的参与者愿意接受较大且延迟的奖励(Wang & Liu, 2009; Guan et al., 2015)。因此情绪效价影响个体的决策行为获得了大量的证据支持。

2.2. 情绪核心评价对决策行为的影响

许多研究基于情绪效价探讨情绪对决策的影响,但是效价并不能解释所有情绪对决策的影响(Lerner et al., 2015)。关键点是这些研究没有考虑到同一效价的情绪在本质上存在的差异,比如预期评估(Smith & Ellsworth, 1985),加工的深度(Bodenhausen et al. 1994b),中枢神经系统的活动(Phelps et al., 2014)等。因此Lerner和Keltner (2000, 2001)提出了评价倾向框架理论(ATF),该理论认为情绪触发的认知核心评价倾向是驱动决策行为的原因,相同效价的情绪(如恐惧、愤怒)可能引发相反的决策行为,而不同效价的情绪(愤怒、快乐)可能会引发相似的决策行为。实证研究应该关注那些在情绪核心维度上高度分化的具体情绪,并比较不同核心维度情绪在决策上的差异(Lerner & Keltner, 2000)。为了验证该理论,Lerner和Keltner (2000)发现恐惧、愤怒倾向个体的风险认知各异,恐惧情绪倾向个体对未来事件做出悲观的判断,而愤怒情绪倾向个体对未来事件做出乐观的判断。Lerner和Keltner (2001)进一步发现诱发的情绪通过确定性和控制感评价维度调节了情绪对乐观判断的影响。另外,相同效价的悲伤和愤怒情绪对决策产生不同的影响(DeSteno et al., 2000)。ATF理论根据Smith和Ellsworth (1985)对情绪六种核心评价维度的描述来表征情绪,包括确定性、控制感、预期努力、注意活动、责任感和愉悦度。评价维度通过改变个体认知评价倾向来影响个体的决策。如情绪触发的确定性和控制感是一种认知倾向,确定性是指个体对事件觉察的预测性,而控制感是指事件被归因于个人或者情境(Lerner et al., 2015)。恐惧情绪具有低控制感和确定性,愤怒个体具有高控制感和确定性,这种核心评价上的差异导致了恐惧的个体看到更大的风险,选择低风险的选项;而愤怒的个体看到更小的风险,使他们选择高风险的选项(Lerner et al., 2015)。另外最近的研究同样为此提供了证据,通过实验诱发的具体情绪(快乐、愤怒和恐惧)对风险决策产生不同的影响,诱发恐惧情绪的个体选择更加安全、风险较小的选项,而诱发愤怒情绪的个体选择回报高、风险性高的选项(宋锡妍等,2021 ;Yang et al., 2020)。

情绪与决策的关系与信息加工深度有关(Lerner et al., 2015),情绪具有适应性功能,消极情绪发出信号,增加对危险环境的警惕和系统性的加工,而积极情绪发出安全信号,引发个体更多的启发性思考(Schwarz & Bless, 1991)。在积极情绪下,个体更多利用启发性线索(Bless et al., 1996; Bodenhausen et al., 1994a)。同时相较于中性情绪,被试在愤怒情绪下分配给福利接受者的钱更少,悲伤情绪下分配给福利接受者的钱更多,有趣的是这种差异在认知负荷情况下消失,由此可以发现愤怒与悲伤之间的分配差异受到认知加工深度的影响(Small & Lerner, 2008)。情绪对决策的影响是多方面的,同时情绪与决策之间的认知过程越来越受到重视。在ATF理论视角下,认知评价倾向在情绪与决策之间的因果关系中具有重要作用,其中核心评价维度(控制感和确定性)更是主导恐惧、愤怒情绪对决策的选择偏好。

3. 情绪影响决策的神经机制

风险决策通常包括了不确定性和风险性,而跨期决策需要权衡即时的利益得失与未来的利益得失。根据评价倾向框架理论(ATF, Lerner et al., 2015),恐惧和愤怒通过核心评价来影响个体的风险决策行为,由于恐惧情绪具有低确定性和预测性,因此个体倾向选择风险更小的选项,相反,愤怒情绪的核心评价具有高确定性和预测性,因此个体通常做出高风险选择。基于风险决策和跨期决策的角度,许多研究探讨了情绪对决策影响的神经机制。

事件相关电位技术(Event-related potentials, ERPs)具有较高的时间分辨率,它能够以毫秒为单位记录个体的神经活动。目前通过使用ERP技术,探讨情绪影响决策主要集中于P2、P3和FRN成分。P2成分是一种评价成分,主要反映了对客观事物属性的高级感知加工(Kranczioch et al., 2003; Boudreau et al., 2008),在跨期决策中,更大的奖赏和更长的延迟时间通常引发更大的P2振幅,这表明个体可以在早期阶段加工奖励和时间属性(Gui et al., 2016; Wu et al., 2016)。另外在愤怒情绪启动下,发现个体在额中区(fronto-central area)引发了更大的P2振幅(Suo et al., 2021),表明了个体对时间延迟和奖赏信息的加工,同时也促使个体在评估阶段投入了更多的注意力和动机。P3通常反映了个体的决策动机,即决策信息对动机水平的影响(Nieuwenhuis et al., 2005; Wu & Zhou, 2009)。在跨期任务中,个体对即时选项有更高的P3振幅,同时它也反映了对高风险选项的资源分配(Yang et al., 2020)。同样的,在愤怒情绪下,个体在做跨期决策时引发了更大的顶叶区(parietal area) P3振幅,由于P3振幅与即时奖赏相关,更大的即时奖赏引发更大的P3振幅(Li et al., 2012),因此这表明在愤怒情绪下,个体更加偏好于即时奖赏,对即时奖赏的动机更为强烈。同时在愤怒情绪下,也表现出更多的注意资源的投入和分配(Suo et al., 2021)。但是在风险决策中,恐惧情绪与愤怒情绪相比引发了更大的P3振幅,个体更偏好于规避风险(Yang et al., 2020)。根据ATF理论框架,恐惧情绪具有较高的不确定性和低控制感,因此个体在愤怒情境下时,对高风险选项更加警觉,投入更多的注意力,从而引发更大的P3振幅。FRN反映了个体对正在进行事件的动态修正,在这一阶段,个体会根据结果实时调整自己的动机状态(Holroyd, Baker, Kerns, & Müller, 2008)。在恐惧条件下,发现了更大的FRN振幅,相较于更小风险的选项结果,高风险的结果引发了更大的FRN振幅,于个体而言这种对高风险高回报选项的动机有更大的意义。尽管研究者探讨的具体情绪并不相同,但是都符合基于ATF框架下的理论解释。目前虽然已有许多研究从脑电技术角度探讨情绪影响决策中的神经机制,但是目前研究还不够丰富,如主要涉及到的是几种基本情绪,对更为复杂的情绪还较少有研究提供证据。另外依据ATF框架的具体机制仍然还相对模糊。

与ERP技术相比,功能磁共振成像技术(fMRI)具有更高的空间分辨率。无论是情绪研究或者是决策研究,这项技术都得到广泛的应用。但是还较少有研究直接通过fMRI技术探讨情绪对决策影响的神经机制。在收益损失的决策任务中,研究发现在跨期收益和跨期损失领域,都发现外侧前额叶和顶叶区的激活,其中在损失框架下,这些脑区激活更强。同时其岛叶、丘脑也被激活, 而丘脑、岛叶通常被认为与负面情绪有关。这些发现表明个体在涉及损失的跨期决策时有更强的负性情绪激活。另外在情绪状态下,个体的杏仁核激活水平会更高(Fusar-Poli et al., 2009)。杏仁核在情绪加工中扮演着重要的作用,但是杏仁核的激活是否影响我们的决策过程还是未知的。另外在决策的评价过程中涉及到大脑的前额叶区域,杏仁核与前额叶之间的功能连接也还不清楚。

4. 影响情绪决策关系的因素

对情绪刺激的偏好是情绪具有适应性功能的重要体现,因为这有助于个体对外部的威胁或者奖励进行反应(Yiend, 2010; Okon-Singer et al., 2013; Pourtois et al., 2013)。但是在某些情况下,情绪可能导致个体做出不利或者次优的决策判断。在情绪对决策或者判断的不利影响下,许多的策略被应用于减弱情绪对决策的不利影响。这些策略包含两个方面,一是减弱情绪反应,比如时间延迟、认知重评和诱发一种相对抗的情绪;二是隔断情绪影响决策的过程,比如改变决策选择、引发错误归因的意识和通过认知努力排出情绪(Lerner et al., 2015)。

4.1. 情绪调节策略减弱情绪对决策的影响

认知重评是一种有效的情绪调节策略,研究发现认知重评减弱负面事件引起的消极情绪,降低消极情绪引发的生理神经反应(Jamieson et al., 2012)。采用认知重评策略的个体也有更多积极情绪体验,更不容易患精神疾病(Aldao et al., 2010)。另外,使用情绪调节策略的个体倾向于选择更低风险的选项,同时它调节与奖赏处理相关的纹状体活动,促使个体选择更优的决策选项(Martin & Delgado, 2011)。在这些直接或间接地把认知重评应用于情绪与决策中的研究发现认知上的调节策略可以帮助个体做出风险更低的决策,即通过有效认知策略的使用来降低情绪对决策的不利影响,帮助决策者做出更优的抉择。

4.2. 认知努力阻断情绪对决策的影响

认知努力与情绪决策间的关系体现在隔断情绪对决策的不利影响过程。如在被试做决策或判断时,排除情绪干扰,阻断情绪对决策的作用(Lerner et al., 2015)。一定的认知努力可以有效排除情绪信息干扰,通过增加对目标干扰刺激的预测性,使个体保持对目标任务的注意,排除情绪信息的干扰。因此,认知努力可以有效地隔断情绪对决策的作用,降低不利情绪对风险决策的影响(Lerner et al., 2015)。另外,通过奖励机制提高的认知努力,也减弱情绪对目标任务的不利影响(Lerner et al., 2015)。外部奖励激活个体的认知控制能力,使个体更加专注的将注意活动集中于目标任务,进而排除情绪刺激对目标任务的干扰(Jin, Auyeung, & Chevalier, 2020)。

当情绪成为干扰因素时,认知努力可以增加对目标任务的注意力并有效地减弱情绪信息对目标任务的干扰(Murphy et al., 2020; Grimshaw et al., 2018; Walsh et al., 2018; Troller-Renfree et al., 2019; Micucci et al., 2020; Jin, Auyeung, & Chevalier, 2020)。金钱奖励激发个体动机,在外部奖励条件下,无论是积极或消极的情绪分心,与没有奖励相比,其对目标判断任务的分心作用都减小了(Walsh et al., 2018; Jin, Auyeung, & Chevalier, 2020)。因此,阻断情绪对决策的影响可以通过提高个体的认知努力。

5. 研究展望

首先,尽管目前情绪对决策影响的研究已有很多有价值的成果,但在研究的深度、广度及神经机制方面还尚有不足,未来研究还需要积极探索。其次,由于情绪影响决策可能存在不利影响,因此探讨改变情绪影响决策的因素也不可忽视,未来还应在这方面进行探索。

5.1. 情绪影响决策的深度、广度

目前,在情绪影响决策行为的深度方面主要探讨的多为基本情绪中的恐惧、愤怒、快乐和悲伤,但是对于较为复杂的复合情绪还较少有人关注,比如自豪、愧疚等。另外,虽然基于ATF框架理论,我们进一步理解了情绪影响决策的内在机制,但是这种机制还没有完全将其六种核心评价分离开,未来研究应该进一步剥离确定性和控制感,以探讨是否是确定性和控制感对决策的唯一影响。最后,还应该探讨实验诱发的情绪与情绪特质之间的差异是否会引发不同的决策行为,这有助于更好地理解情绪对决策的影响。

5.2. 情绪影响决策的神经机制

随着现代科技的发展,已经有越来越多的研究通过时间精度高的ERP技术、空间精度高的fMRI技术来探索心理现象的神经机制。目前通过跨期或风险决策任务已有一定的基于时间的ERP结果,但是基于空间分辨率高fMRI成果还较少,未来应该通过这项技术进一步探讨其在脑区激活上的差异和功能连接,这有助于我们更好地理解情绪影响决策的神经机制。

5.3. 探索影响情绪决策关系的因素

关于情绪调节策略的研究很多,但是对于情绪决策研究的涉及还不足,因此未来研究应该更多关注情绪调节策略在情绪决策研究中的作用。另外,目前关于认知重评调节策略在情绪决策研究中已有一些令人振奋的结果(Martin & Delgado, 2011),但是其他的调节策略还较少被关注到,如情绪抑制等。另外,阻断情绪对决策的影响还有很多策略,但是这些策略大部分限于理论意义,还没有足够的实证证据,因此未来应该增加这方面的探索。

文章引用

夏诗环. 情绪对决策的影响及其神经机制
The Influence of Emotion on Decision-Making and Its Neural Mechanism[J]. 心理学进展, 2022, 12(02): 381-389. https://doi.org/10.12677/AP.2022.122043

参考文献

  1. 1. 宋锡妍, 程亚华, 谢周秀甜, 龚楠焰, 刘雷(2021). 愤怒情绪对延迟折扣的影响: 确定感和控制感的中介作用. 心理学报, 53(5), 456-468.

  2. 2. Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-Regulation Strategies across Psychopathology: A Meta-Analytic Review. Clinical Psychology Review, 30, 217-237. https://doi.org/10.1016/j.cpr.2009.11.004

  3. 3. Bless, H., Schwarz, N., Clore, G. L., Golisano, V., Rabe, C., & Wölk, M. (1996). Mood and the Use of Scripts: Does a Happy Mood Really Lead to Mindlessness? Journal of Personality and Social Psychology, 71, 665-679. https://doi.org/10.1037/0022-3514.71.4.665

  4. 4. Bodenhausen, G. V., Kramer, G. P., & Süsser, K. (1994a). Happiness and Stereotypic Thinking in Social Judgment. Journal of Personality and Social Psychology, 66, 621-632. https://doi.org/10.1037/0022-3514.66.4.621

  5. 5. Bodenhausen, G. V., Sheppard, L. A., & Kramer, G. P. (1994b). Negative Affect and Social Judgment: The Differential Impact of Anger and Sadness. European Journal of Social Psychology, 24, 45-62. https://doi.org/10.1002/ejsp.2420240104

  6. 6. Boudreau, C., McCubbins, M. D., & Coulson, S. (2008). Knowing When to Trust Others: An ERP Study of Decision Making after Receiving Information from Unknown People. Social Cognitive and Affective Neuroscience, 4, 23-34. https://doi.org/10.1093/scan/nsn034

  7. 7. Carter, S., & McBride, M. (2013). Experienced Utility versus Decision Utility: Putting the “S” in Satisfaction. Journal of Socio-Economics, 42, 13-23. https://doi.org/10.1016/j.socec.2012.11.009

  8. 8. DeSteno, D., Petty, R. E., Wegener, D. T., & Rucker, D. D. (2000). Beyond Valence in the Perception of Likelihood: The Role of Emotion Specificity. Journal of Personality and Social Psychology, 78, 397-416. https://doi.org/10.1037/0022-3514.78.3.397

  9. 9. Edmans, A., García, D., & Norli, Ø. (2007). Sports Sentiment and Stock Returns. The Journal of Finance, 62, 1967-1998. https://doi.org/10.1111/j.1540-6261.2007.01262.x

  10. 10. Ekman, P. (2007). Emotions Revealed: Recognizing Faces and Feelings to Improve Communication and Emotional Life. Holt.

  11. 11. Frijda, N. H. (1988). The Laws of Emotion. American Psychologist, 43, 349-358. https://doi.org/10.1037/0003-066X.43.5.349

  12. 12. Fusar-Poli, P., Placentino, A., Carletti, F., Landi, P., & Politi, P. (2009). Functional Atlas of Emotional Faces Processing: A Voxel-Based Meta-Analysis of105 Functional Magnetic Resonance Imaging Studies. Journal of Psychiatry & Neuroscience, 34, 418-432.

  13. 13. Gilbert, D. T. (2006). Stumbling on Happiness. Knopf.

  14. 14. Grimshaw, G. M., Kranz, L. S., Carmel, D., Moody, R. E., & Devue, C. (2018). Contrasting Reactive and Proactive Control of Emotional Distraction. Emotion, 18, 26-38. https://doi.org/10.1037/emo0000337

  15. 15. Guan, S., Cheng, L., Fan, Y., & Li, X. (2015). Myopic Decisions under Negative Emotions Correlate with Altered Time Perception. Frontiers in Psychology, 6, Article 468. https://doi.org/10.3389/fpsyg.2015.00468

  16. 16. Gui, D. Y., Li, J. Z., Li, X., & Luo, Y. J. (2016). Temporal Dynamics of the Interaction between Reward and Time Delay during Intertemporal Choice. Frontiers in Psychology, 7, Article 1526. https://doi.org/10.3389/fpsyg.2016.01526

  17. 17. Han, S., Lerner, J. S., & Keltner, D. (2007). Feelings and Consumer Decision Making: The Appraisal-Tendency Framework. Journal of Consumer Psychology, 17, 158-168. https://doi.org/10.1016/S1057-7408(07)70023-2

  18. 18. Hirshleifer, D., & Shumway, T. (2003). Good Day Sunshine: Stock Returns and the Weather. J. Finance, 58, 1009-1032. https://doi.org/10.1111/1540-6261.00556

  19. 19. Holroyd, C. B., Baker, T. E., Kerns, K. A., & Müller, U. (2008). Electrophysiological Evidence of Atypical Motivation and Reward Processing in Children with Attention-Deficit Hyperactivity Disorder. Neuropsychologia, 46, 2234-2242. https://doi.org/10.1016/j.neuropsychologia.2008.02.011

  20. 20. Jamieson, J. P., Nock, M. K., & Mendes, W. B. (2012). Mind over Matter: Reappraising Arousal Improves Cardiovascular and Cognitive Responses to Stress. Journal of Experimental Psychology: General, 141, 417-422. https://doi.org/10.1037/a0025719

  21. 21. Jin, X., Auyeung, B., & Chevalier, N. (2020). External Rewards and Positive Stimuli Promote Different Cognitive Control Engagement Strategies in Children. Developmental Cognitive Neuroscience, 44, Article ID: 100806. https://doi.org/10.1016/j.dcn.2020.100806

  22. 22. Johnson, E. J., & Tversky, A. (1983). Affect, Generalization, and the Perception Of Risk. Journal of Personality and Social Psychology, 45, 20-31. https://doi.org/10.1037/0022-3514.45.1.20

  23. 23. Kamstra, M. J., Kramer, L. A., & Levi, M. D. (2003). Winter Blues: A SAD Stock Market Cycle. American Economic Review, 93, 324-343. https://doi.org/10.1257/000282803321455322

  24. 24. Kassam, K. S., Morewedge, C. K., Gilbert, D. T., & Wilson, T. D. (2011). Winners Love Winning and Losers Love Money. Psychological Science, 22, 602-606. https://doi.org/10.1177/0956797611405681

  25. 25. Keltner, D. T., & Lerner, J. S. (2010). Emotion. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The Handbook of Social Psychology (Vol. 1, pp. 317-352). Wiley. https://doi.org/10.1002/9780470561119.socpsy001009

  26. 26. Keltner, D., Oatley, K., & Jenkins, J. M. (2014). Understanding Emotions. Wiley.

  27. 27. Kermer, D. A., Driver-Linn, E., Wilson, T. D., & Gilbert, D. T. (2006). Loss Aversion Is an Affective Forecasting Error. Psychological Science, 17, 649-653. https://doi.org/10.1111/j.1467-9280.2006.01760.x

  28. 28. Kranczioch, C., Debener, S., & Engel, A. K. (2003). Event-Related Potential Correlates of the Attentional Blink Phenomenon. Cognitive Brain Research, 17, 177-187. https://doi.org/10.1016/S0926-6410(03)00092-2

  29. 29. Lazarus, R. S. (1991). Emotion and Adaptation. Oxford University Press.

  30. 30. Lerner, J. S., & Keltner, D. (2000). Beyond Valence: Toward a Model of Emotion-Specific Influences on Judgement and Choice. Cognition and Emotion, 14, 473-493. https://doi.org/10.1080/026999300402763

  31. 31. Lerner, J. S., & Keltner, D. (2001). Fear, Anger, and Risk. Journal of Personality and Social Psychology, 81, 146-159. https://doi.org/10.1037/0022-3514.81.1.146

  32. 32. Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and Decision Making. Annual Review of Psychology, 66, 799-823. https://doi.org/10.1146/annurev-psych-010213-115043

  33. 33. Li, J. Z., Gui, D. Y., Feng, C. L., Wang, W. Z., Du, B. Q., Gan, T. et al. (2012). Victims’ Time Discounting 2.5 Years after the Wenchuan Earthquake: An ERP Study. PLoS ONE, 7, e40316. https://doi.org/10.1371/journal.pone.0040316

  34. 34. Loewenstein, G., & Lerner, J. S. (2003). The Role of Affect in Decision Making. In R. Davidson, H. Goldsmith, & K. Scherer (Eds.), Handbook of Affective Science (pp. 619-642). Oxford University Press.

  35. 35. Loewenstein, G., Weber, E. U., Hsee, C. K., & Welch, N. (2001). Risk as Feelings. Psychological Bulletin, 127, 267-286. https://doi.org/10.1037/0033-2909.127.2.267

  36. 36. Loomes, G., & Sugden, R. (1982). Regret Theory: An Alternative Theory of Rational Choice under Uncertainty. The Economic Journal, 92, 805-824. https://doi.org/10.2307/2232669

  37. 37. Lufityanto, G., Donkin, C., & Pearson, J. (2016). Measuring Intuition: Nonconscious Emotional Information Boosts Decision Accuracy and Confidence. Psychological Science, 27, 622-634. https://doi.org/10.1177/0956797616629403

  38. 38. Martin, L. N., & Delgado, M. R. (2011). The Influence of Emotion Regulation on Decision-Making under Risk. Journal of Cognitive Neuroscience, 23, 2569-2581. https://doi.org/10.1162/jocn.2011.21618

  39. 39. McGraw, A. P., Larsen, J. T., Kahneman, D., & Schkade, D. (2010). Comparing Gains and Losses. Psychological Science, 21, 1438-1445. https://doi.org/10.1177/0956797610381504

  40. 40. Mellers, B. A., Schwartz, A., Ho, K., & Ritov, I. (1997). Decision Affect Theory: Emotional Reactions to the Outcomes of Risky Options. Psychological Science, 8, 423-429. https://doi.org/10.1111/j.1467-9280.1997.tb00455.x

  41. 41. Micucci, A., Ferrari, V., De Cesarei, A., & Codispoti, M. (2020). Contextual Modulation of Emotional Distraction: Attentional Capture and Motivational Significance. Journal of Cognitive Neuroscience, 32, 621-633. https://doi.org/10.1162/jocn_a_01505

  42. 42. Murphy, J., Devue, C., Corballis, P. M., & Grimshaw, G. M. (2020). Proactive Control of Emotional Distraction: Evidence from EEG Alpha Suppression. Frontiers in Human Neuroscience, 14, Article 318. https://doi.org/10.3389/fnhum.2020.00318

  43. 43. Nieuwenhuis, S., Aston-Jones, G., & Cohen, J. D. (2005). Decision Making, the P3, and the Locus Coeruleus—Norepinephrine System. Psychological Bulletin, 131, 510-532. https://doi.org/10.1037/0033-2909.131.4.510

  44. 44. Okon-Singer, H., Lichtenstein-Vidne, L., & Cohen, N. (2013). Dynamic Modulation of Emotional Processing. Biological Psychology, 92, 480-491. https://doi.org/10.1016/j.biopsycho.2012.05.010

  45. 45. Otto, A. R., Fleming, S. M., & Glimcher, P. W. (2016). Unexpected but Incidental Positive Outcomes Predict Real-World Gambling. Psychological Science, 27, 299-311. https://doi.org/10.1177/0956797615618366

  46. 46. Phelps, E. A., Lempert, K. M., & Sokol-Hessner, P. (2014). Emotion and Decision Making: Multiple Modulatory Neural Circuits. Annual Review of Neuroscience, 37, 263-288. https://doi.org/10.1146/annurev-neuro-071013-014119

  47. 47. Pourtois, G., Schettino, A., & Vuilleumier, P. (2013). Brain Mechanisms for Emotional Influences on Perception and Attention: What Is Magic and What Is Not. Biological Psychology, 92, 492-512. https://doi.org/10.1016/j.biopsycho.2012.02.007

  48. 48. Rutledge, R. B., Skandali, N., Dayan, P., & Dolan, R. J. (2014). A Computational and Neural Model of Momentary Subjective Well-Being. Proceedings of the National Academy of Sciences of the United States of America, 111, 12252-12257. https://doi.org/10.1073/pnas.1407535111

  49. 49. Scherer, K. R., & Ekman, P. (Eds.) (1984). Approaches to Emotion. Erlbaum.

  50. 50. Schwarz, N., & Bless, H. (1991). Happy and Mindless, but Sad and Smart? The Impact of Affective States on Analytic Reasoning. In J. P. Forgas (Ed.), Emotion and Social Judgments (pp. 55-71). Pergamon. https://doi.org/10.4324/9781003058731-4

  51. 51. Schwarz, N., & Clore, G. L. (1983). Mood, Misattribution, and Judgments of Well-Being: Informative and Directive Functions of Affective States. Journal of Personality and Social Psychology, 45, 513-523. https://doi.org/10.1037/0022-3514.45.3.513

  52. 52. Small, D. A., & Lerner, J. S. (2008). Emotional Policy: Personal Sadness and Anger Shape Judgments about a Welfare Case. Political Psychology, 29, 149-168. https://doi.org/10.1111/j.1467-9221.2008.00621.x

  53. 53. Smith, C. A., & Ellsworth, P. C. (1985). Patterns of Cognitive Appraisal in Emotion. Journal of Personality and Social Psychology, 48, 813-838. https://doi.org/10.1037/0022-3514.48.4.813

  54. 54. Solomon, R. C. (1993). The Passions: Emotions and the Meaning of Life. Hackett.

  55. 55. Suo, T., Jia, X., Song, X., & Liu, L. (2021). The Differential Effects of Anger and Sadness on Intertemporal Choice: An ERP Study. Frontiers in Neuroscience, 15, Article 638989. https://doi.org/10.3389/fnins.2021.638989

  56. 56. Troller-Renfree, S. V., Buzzell, G. A., Pine, D. S., Henderson, H. A., & Fox, N. A. (2019). Consequences of Not Planning Ahead: Reduced Proactive Control Moderates Longitudinal Relations between Behavioral Inhibition and Anxiety. Journal of the American Academy of Child & Adolescent Psychiatry, 58, 768-775.e1. https://doi.org/10.1016/j.jaac.2018.06.040

  57. 57. Walsh, A. T., Carmel, D., Harper, D., & Grimshaw, G. M. (2018). Motivation Enhances Control of Positive and Negative Emotional Distractions. Psychonomic Bulletin & Review, 25, 1556-1562. https://doi.org/10.3758/s13423-017-1414-5

  58. 58. Wang, P., & Liu, Y. F. (2009). The Effect of Mood on Intertemporal Choice. Psychological Science, 32, 1318-1320.

  59. 59. Wu, H., Gui, D., Lin, W., Gu, R., Zhu, X., & Liu, X. (2016). The Procrastinators Want It Now: Behavioral and Event-Related Potential Evidence of the Procrastination of Intertemporal Choices. Brain and Cognition, 107, 16-23. https://doi.org/10.1016/j.bandc.2016.06.005

  60. 60. Wu, Y., & Zhou, X. L. (2009). The P300 and Reward Valence, Magnitude, and Expectancy in Outcome Evaluation. Brain Research, 1286, 114-122. https://doi.org/10.1016/j.brainres.2009.06.032

  61. 61. Yang, Q., Zhou, S., Gu, R., & Wu, Y. (2020). How Do Different Kinds of Incidental Emotions Influence Risk Decision Making? Biological Psychology, 154, Article ID: 107920. https://doi.org/10.1016/j.biopsycho.2020.107920

  62. 62. Yechiam, E., Telpaz, A., & Hochman, G. (2014). The Complaint Bias in Subjective Evaluations of Incentives. Decision, 1, 147-160. https://doi.org/10.1037/dec0000008

  63. 63. Yiend, J. (2010). The Effects of Emotion on Attention: A Review of Attentional Processing of Emotional Information. Cognition and Emotion, 24, 3-47. https://doi.org/10.1080/02699930903205698

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