Front. Psychol. Frontiers in Psychology Front. Psychol. 1664-1078 Frontiers Media S.A. 10.3389/fpsyg.2017.01592 Psychology Review The Influence of Emotion on Fairness-Related Decision Making: A Critical Review of Theories and Evidence Zheng Ya 1 Yang Zhong 2 3 * Jin Chunlan 4 Qi Yue 2 3 Liu Xun 2 3 * 1Department of Psychology, Dalian Medical University Dalian, China 2CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences Beijing, China 3Department of Psychology, University of Chinese Academy of Sciences Beijing, China 4School of Foreign Languages, East China University of Science and Technology Shanghai, China

Edited by: Chao Liu, Beijing Normal University, China

Reviewed by: Xiuyan Guo, East China Normal University, China; Jing Luo, Capital Normal University, China

*Correspondence: Xun Liu, liux@psych.ac.cn Zhong Yang, yangzhong@psych.ac.cn

This article was submitted to Decision Neuroscience, a section of the journal Frontiers in Psychology

 19 09 2017 2017 8 1592 10 05 2017 30 08 2017 Copyright © 2017 Zheng, Yang, Jin, Qi and Liu. 2017 Zheng, Yang, Jin, Qi and Liu

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Fairness-related decision making is an important issue in the field of decision making. Traditional theories emphasize the roles of inequity aversion and reciprocity, whereas recent research increasingly shows that emotion plays a critical role in this type of decision making. In this review, we summarize the influences of three types of emotions (i.e., the integral emotion experienced at the time of decision making, the incidental emotion aroused by a task-unrelated dispositional or situational source, and the interaction of emotion and cognition) on fairness-related decision making. Specifically, we first introduce three dominant theories that describe how emotion may influence fairness-related decision making (i.e., the wounded pride/spite model, affect infusion model, and dual-process model). Next, we collect behavioral and neural evidence for and against these theories. Finally, we propose that future research on fairness-related decision making should focus on inducing incidental social emotion, avoiding irrelevant emotion when regulating, exploring the individual differences in emotional dispositions, and strengthening the ecological validity of the paradigm.

 emotion emotion regulation fairness-related decision making fairness theory neural mechanisms 31571161 31200782 31500872 31640039 National Natural Science Foundation of China10.13039/501100001809 China Scholarship Council10.13039/501100004543 Introduction

Researchers of decision-making typically regard emotion as impulsive and irrational and neglect its role in decision making (Kahneman and Tversky, 1979; Von Neumann and Morgenstern, 2007). In “normative decision theory,” economic decision making is based on “cold” mathematical calculation, and decision makers are idealized as perfect “rational machines.” However, studies increasingly show that emotion is one of the most important factors in the irrational decision-making process (Hastie, 2001; Sanfey et al., 2006). For example, emotion may guide people’s decision making under conditions of risk and uncertainty and with regard to intertemporal choices, social decisions, and moral decision making (Loewenstein and Lerner, 2003; Rilling and Sanfey, 2011).

Fairness-related decision making is an important issue in the field of psychological decision making (Güth and Kocher, 2014). Experiments on fairness-related decision making have usually been conducted using the classic “Ultimatum Game” (UG) paradigm (Güth et al., 1982). An increasing number of UG studies have revealed that responders tended to sacrifice their own payoffs to decline an unfair offer, especially when they receive an offer that is less than 20% of the total (Güth et al., 1982; Thaler, 1988; Camerer and Thaler, 1995). These irrational rejection behaviors cannot be captured by the economic rationality of utility, in which the responder should accept all offers since receiving at least some money is always preferable to receiving no money.

Some theories, such as “inequity aversion” theory (Fehr and Schmidt, 1999; Bolton and Ockenfels, 2000) and “reciprocity equilibrium” theory (Rabin, 1993; Falk and Fischbacher, 2006), have attempted to explain irrational behaviors in fairness-related decision making. “Inequity aversion” means that people prefer equitable outcomes: they are willing to forego a material payoff to work toward more equitable outcomes (Fehr and Schmidt, 1999; Bolton and Ockenfels, 2000). However, it is difficult to explain why unfair offers from computer partners were accepted at higher rates than human partners if people were pursuing only fairness in terms of their own material payoff relative to the payoff of others (Blount, 1995; Knoch et al., 2006). According to “reciprocity equilibrium” theory, the rejection in the UG with human partners is social punishment to promote fair offers in subsequent bargaining, establish a good reputation, or enforce fairness norms (Rabin, 1993; Falk and Fischbacher, 2006). Thus, people will reject unfair offers from human partners, but accept unfair offers from computer partners to maximize personal gains. One study found that players would reject unfair offers when rejection reduced only their own earning to 0, and even when they cannot communicate their anger to the proposers through rejection (Yamagishi et al., 2009). The rejection of unfair offers that increase inequity and fail to punish proposers cannot be explained by the “inequity aversion” and “reciprocity equilibrium” theories. Such studies have increased awareness of the fact that emotion may be an important reason for irrational behaviors in fairness-related decision making (Sanfey et al., 2003; Ferguson et al., 2014). They propose that rejection is used to express the negative emotions such as anger or disgust aroused by unfair offers (Xiao and Houser, 2005). Although the two classical theories do not deny the existence of emotion, they nevertheless do not clearly explain the role of emotion and its mechanism. A new perspective on emotion is required to explain behavior in fairness-related decision making. Many studies have explored the influence of emotion on fairness-related decision making using behavioral, electrophysiological and neuroimaging approaches and supported these theories.

The influence of emotion on decision making concerns integral emotions (i.e., task-driven) and incidental emotions (i.e., task-unrelated) (Loewenstein and Lerner, 2003). The Wounded Pride/Spite Model suggests that integral emotion, such as negative emotions provoked by unfair offers, prompt rejections (Straub and Murnighan, 1995; Pillutla and Murnighan, 1996). However, this model only focuses on the influence of emotional response aroused by fairness-related decision making; it does not consider the influence of emotion aroused by dispositional or situational sources objectively unrelated to the task. To address this gap, the Affect Infusion Model investigated how incidental emotion (emotion aroused by emotional videos or images) influence fairness-related decision making (Forgas et al., 2003; Bless et al., 2006). These two models emphasized the role of emotion in fairness-related decision making, but ignored the regulation of emotion by cognition in modulating behavior. The Dual-Process System claims that the rational system and the emotional system are dual subsystems in fairness-related decision making, with the former prompting an adaptive response to different situations by regulating the latter (Loewenstein and O’Donoghue, 2004; Sanfey and Chang, 2008; Feng et al., 2015). This review summarizes these models of the impact of emotions on fairness-related decision making and the corresponding behavioral and neural evidence.

 Wounded Pride/Spite Model and its Evidence Wounded Pride/Spite Model

The Wounded Pride/Spite Model proposes that the integral emotion aroused by a task itself may change fairness-related decision making. The model claims that if responders perceive that offers are unfair, feelings of wounded pride and anger may be aroused (Straub and Murnighan, 1995; Pillutla and Murnighan, 1996). When direct channels for expressing emotions are either impossible or undesirable, individuals are willing to incur the costs of rejection to retaliate against perceived unfairness (Gross and Levenson, 1993; Gross, 1999). Even when the responder has no way to punish the proposers, the responder still wants to reject the unfair offer (Yamagishi et al., 2009), suggesting that rejection may be not only a strategy to enlarge future potential payoffs but also an effective means of emotional release. However, if responders can convey their feelings of unfairness to proposers, the acceptance rates (ARs) of unfair offers could be increased substantially (Xiao and Houser, 2005).

 Evidence from Integral Emotion

According to a large number of recent studies, the integral negative emotions aroused by unfair offers can increase the punishment for violating fairness norms.

First, previous studies found that fairness-related decision making can evoke strong emotions, demonstrating the existence of integral emotion in fairness-related decision making. From the responders’ self-reports, the researchers found that when responders received an unfair offer, their negative affective responses, such as anger, contempt, irritation, envy and sadness, increased, whereas positive affective responses, such as pleasure and happiness, decreased (Pillutla and Murnighan, 1996; Bosman et al., 2001; Xiao and Houser, 2005; Osumi and Ohira, 2009; Voegele et al., 2010; Hewig et al., 2011; Bediou and Scherer, 2014; Gilam et al., 2015). Researchers used the UG to examine the affective correlates of decision making and found that the decision to reject is positively related to more negative emotional reactions, increased autonomic nervous system and skin conductance activity (van’t Wout et al., 2006; Hewig et al., 2011), and decelerated heart rate (Osumi and Ohira, 2009; Dunn et al., 2012). Furthermore, similar facial motor activities were evoked by unfair treatment, unpleasant tastes, and photographs of contaminants, suggesting that unfairness elicits the same disgust as bad tastes and disease vectors (Chapman et al., 2009).

Second, the affective response to unfairness offers is one possible reason for rejection in fairness-related decision making. Psychophysiological studies have shown that increased ARs of offers correlate with greater resting heart rate variability (Osumi and Ohira, 2009; Dunn et al., 2012). EEG studies found that feedback-related negativity (FRN) could predict the likelihood of rejection in the UG and that rejection was associated with negative emotion (van’t Wout et al., 2006; Hewig et al., 2011). By using the dipole localization method, EEG studies showed that unfair offers could arouse the activation of the insula, which is associated with negative emotion, and the anterior cingulate cortex (ACC), which is associated with conflict monitoring (Guclu et al., 2012). Neuroimaging studies also showed a negative correlation between the activation of the insula specifically involved in aversive emotion and the ARs of unfair offers (Sanfey et al., 2003; Takagishi et al., 2009). The above findings indicate that negative emotion aroused by perceptions of unfairness play an important role in rejection behaviors, supporting the Wounded Pride/Spite Model.

Although the Wounded Pride/Spite Model proposes that negative emotion in fairness-related decision making is an important factor in the rejection of an unfair offer (van’t Wout et al., 2006; Hewig et al., 2011) and can explain many behaviors in fairness-related decision making (Harle and Sanfey, 2007; Grecucci et al., 2013b), this model is only concerned with the responders’ emotional reaction that is aroused by fairness-related decision making. It ignores the impact of the responders’ emotional state and other contextual factors.

 Affect Infusion Model and Evidence Affect Infusion Model

The Affect Infusion Model proposes that incidental emotion aroused by task-unrelated sources can significantly influence fairness-related decision making by priming mood-congruent concepts and dispositions (Forgas et al., 1990; Forgas, 2002). For instance, in fairness-related decision making, people must integrate negative (unfair social signals) and positive (financial benefits) information. Positive incidental emotion makes responders more concerned about their own benefits, thus increasing ARs. By contrast, negative incidental emotion makes responders more concerned about unfair offers, thus decreasing ARs (Harle et al., 2012). That is, acceptance or rejection decisions represent the internal rewards and external fairness principles in fairness-related decision making. Positive emotion can enhance cooperation by recruiting a more assimilative, internally focused processing style that promotes selfishness (Forgas et al., 1990). Negative emotion is an alert signal that requires accommodative processing and increases monitoring of the external environment to process potential threats and hazardous stimulation, increasing concern with social norms (Forgas et al., 2003; Bless et al., 2006). For example, sadness provokes pessimistic framing and increases the processing of threatening information, making responders more concerned about the negative consequences of unfairness and the punishment of those who violate the fairness norm (Harle and Sanfey, 2007).

 Evidence of Incidental Emotion

To explore the influence of incidental emotion, many studies have manipulated the affective state by evoking different valences and arousal levels with images and videos. The results showed that participants in a negative emotional state will reject a greater number of unfair offers (Moretti and Di Pellegrino, 2010; Fabiansson and Denson, 2012; Harle et al., 2012; Liu et al., 2016; Riepl et al., 2016), whereas a positive emotional state may reduce or exert no influence on ARs (Harle and Sanfey, 2007; Andrade and Ariely, 2009; Forgas and Tan, 2013a,b; Liu et al., 2016).

Behavioral studies found that on the one hand, when the participants were responders, compared with a neutral group, sad participants reported more negative emotions, such as anger and disgust, when faced with unfair offers and subsequently made more rejections. However, participants who were induced to experience happy emotions accepted more unfair offers (Riepl et al., 2016), with no discernible impact on their decisions (Harle and Sanfey, 2007; Forgas and Tan, 2013a,b; Liu et al., 2016). On the other hand, when the participants were proposers, inducing amusement (compared with sadness) made them more selfish; they also allocated a greater number of points to themselves and had shorter response times (Forgas and Tan, 2013a,b). Neuroimaging studies indicate that incidental sad emotions are regulated by the three main brain regions for emotions, namely, the insula, ACC and striatum. First, compared with participant responses under neutral conditions, the ARs of unfair offers were associated with higher bilateral insula activations in participants who were sad. Insula is typically associated with negative emotions (Paulus et al., 2003; Knutson et al., 2007), suggesting that this region may indicate an aversive response, which may reduce ARs (Harle et al., 2012). Consequently, some researchers have speculated that insula activation can predict the influence of sadness on decision making (Sanfey et al., 2003). Increasing evidence suggests the important role of the anterior insula (AI) in detecting norm violations (Civai et al., 2012; Xiang et al., 2013). Researchers speculated that a sad participant with increased AI activity may experience high sensitivity to norm violation. Thus, sad incidental emotion could activate the insula involved in negative emotion (or detection of norm violation) and bias behavior accordingly. Second, receiving unfair offers in a sad vs. neutral mood resulted in greater activation in the ACC linked to error and decision conflict monitoring, suggesting that sad individuals may experience an enhanced perception of social norm violation (Harle et al., 2012). Furthermore, a moderating effect of mood was found in the left ventral striatum, which is associated with reward processing. Individuals who experienced a neutral mood showed stronger activation for fair offers relative to unfair offers, while individuals who were sad did not exhibit such a pattern of activation, implying decreased reward responsiveness to reward stimuli (Harle et al., 2012). Overall, both behavioral and neural studies have shown that negative emotions enhance participants’ negative responses to behaviors that violate fairness norms and reduce reward activation for fair offers, thus decreasing ARs. These studies demonstrate that emotion plays a role in changing participants’ decisions by altering their cognitive processing, supporting the Affect Infusion Model.

However, some researchers have noted that the dimension of emotional motivation, rather than emotional valence, is the key factor that influences fairness decision making. Emotional valence refers to the intrinsic attractiveness (positive valence) or averseness (negative valence) of an event, an object, or a situation (Frijda, 1986). Emotional motivation refers to the aversive and appetitive apparatuses, which, respectively, promote withdrawal and approach behavior (Schneirla, 1959; Lang et al., 1997). Two emotions with similar valences may have different motivations, and vice versa. For instance, amusement and serenity are positive emotions, whereas anger and disgust are negative emotions. However, amusement and anger are classified as approach-based emotions, whereas serenity and disgust are withdraw-based emotions. Therefore, researchers have suggested that compared with a valence framework, partitioning affective states based on motivational tendency could more accurately explain the changes in ARs in fairness-related decision. The results of a study that explored the influence of positive emotions (amusement and serenity) and negative emotions (anger and disgust) on fairness-related decision making, indicate that emotional valence did not predict ARs. However, the approach-based emotional states (amusement, anger) increased ARs, whereas withdrawal-based emotional states (disgust, serenity) decreased ARs (Harle and Sanfey, 2010). Thus, emotional motivation may help explain fairness-related decision making. Many researchers have explored the emotional influence of fairness-related decision making in terms of approach-based states (anger) and withdrawal-based emotional states (disgust) (Andrade and Ariely, 2009; Moretti and Di Pellegrino, 2010; Liu et al., 2016; Riepl et al., 2016).

Studies have shown that anger influences fairness-related decision making and leads responders to reject more unfair offers. On the one hand, anger functions as a negative emotion after unfair treatment (Pillutla and Murnighan, 1996) and thus decreases the ARs of unfair offers. Prior to a decision, the responders’ anger elicited by watching the video clip made them reject more unfair offers compared with responders who watched a pleasant video clip (Andrade and Ariely, 2009; Riepl et al., 2016). When manipulating the facial expressions of the proposers, the same results were found: responders facing angry proposers provided the most rejections, whereas the least rejections were from those who faced pleasant proposers (Mussel et al., 2013; Liu et al., 2016). When the responder’s anger was provoked by the controlled proposer’s negative appraisal of the responder’s speech, decreased ARs resulted (Fabiansson and Denson, 2012). To the best of our knowledge, only one study used an EEG and explored the neural mechanism of the influence of incident emotion on fairness-related decision making. That study induced anger, fear and happiness via short movie clips. The results showed that responders with high trait negative affect in aversive mood states had increased FRN amplitudes when they were in an angry mood but not when they experienced fear or happiness (Riepl et al., 2016). On the other hand, whether the proposer or the responder is the angry party leads to different perceptions of fairness and judgments of the proposer’s offer. If the proposers are angry, more unfair offers are given. For example, if the proposer’s anger is aroused by the responder, the proposer is more likely to split unfair offers (Fabiansson and Denson, 2012). In contrast, if the responder feels angry, more fair offers are given. For example, proposers will make more fair offers when they know that the responders watched an angry video clip in contrast with the knowledge that the responders watched a happy clip (Andrade and Ho, 2007). The above results may relate to the proposers’ attribution of anger. Anger is a kind of high-arousal and approach-based negative emotion (Berkowitz and Harmon-Jones, 2004; Carver and Harmon-Jones, 2009), and it may cause antisocial behaviors related to revenge (Carnevale and Isen, 1986; Pillutla and Murnighan, 1996; Allred et al., 1997). Therefore, when the responder is the one to irritate the proposer, the proposer proposes more unfair offers in return. Second, anger may make people tougher and more dominant (Knutson, 1996; Tiedens, 2001). People know that angry people are impulsive and act irrationally (Bacharach and Lawler, 1981), so they may make more fair offers to reduce the possibility of being rejected instead of irritating the responder to maximize the profits in bargaining when they play as proposers (Andrade and Ho, 2007; Andrade and Ariely, 2009).

In addition, disgust aroused prior to a decision can increase the responder’s punishment for unfair offers, whereas the idea of misattributing the disgust induced by the unfair offer to incidental disgust will reduce the responder’s punishment. When responders have viewed emotional pictures or faces to arouse aversion prior to a decision, lower ARs to unfair offers are caused by the disgust (Moretti and Di Pellegrino, 2010; Liu et al., 2016). In a comparison of the influence of disgust and sadness on fairness decisions, disgust caused obviously lower ARs (Moretti and Di Pellegrino, 2010). However, another study using disgusting smells showed that participants misattributed the disgust induced by an unfair offer to the disgusting smell, which led to higher ARs (Bonini et al., 2011). These results indicate that the arousal of disgust prompts people’s maintenance of social norms because disgust is a type of withdrawal-based emotion (Harle and Sanfey, 2010) and may be extended to moral and social violations (Rozin et al., 2000). As an indicator of the judgment of others’ behavior as either right or wrong, feelings of disgust can function better than sadness as moral intuition (Haidt, 2001) to decrease the ARs of unfair offers. To an extent, disgust aroused prior to a task overlapped with disgust in the distribution, whereas the attribution of the latter to the former resulted in a subtraction of the emotion.

From the above, we may conclude that the valences of anger and aversion are the same; however, due to the different induction manipulations and attributions, they may have different impacts on fairness-related decision making. Consequently, the Affect Infusion Model takes the motivational direction of emotion as an important factor to interpret the emotional process of fairness-related decision making within a wider range.

 Dual-Process Systems and the Empirical Study Dual-Process Systems

The above two models focused on the function of emotional arousal and appraisal in fairness-related decision making but ignored the regulation of emotion by cognition to change decision making. The Dual-process System claims that there are dual subsystems in fairness-related decision making: one is automatic, with an immediate response and an emotional system with no cognitive effort, whereas the other is controlled and comparatively slow, with a rational system of cognitive effort. The emotional system represents the intuitive response; however, after learning and calculation, the rational system requires an adaptive response to different situations by regulating the emotional system (Loewenstein and O’Donoghue, 2004; Sanfey and Chang, 2008; Feng et al., 2015). Fairness-related decision making is influenced by systematically and effectively regulating responders’ fairness perceptions via rational cognitive control (Rilling and Sanfey, 2011). For example, the model suggests that all types of emotional regulation strategies can change fairness-related decision making through the interaction of cognition and emotion.

 The Empirical Study of Dual-Process Systems

Researchers have employed different emotion regulation strategies and compared their effectiveness. The results support the influence of emotion regulation on fairness-related decision making.

First, responders may spontaneously regulate the negative emotions induced by unfair offers in the UG. After decision making, responders are requested to report their own opinions on the offer and to write down the shift of their decisions as follows: “At the very beginning, I thought of…, then I considered.…” Some responders may remain angry, reject the unfair offer and refuse to report, whereas others may spontaneously employ cognitive reappraisal to reduce their own negative emotions and then accept more unfair offers (Voegele et al., 2010; Gilam et al., 2015). In physiological arousal, responders who employed reappraisal showed higher vagal activation and attenuated heart rate deceleration after accepting unfair offers (Voegele et al., 2010). Neuroimaging studies have revealed that increased ARs of unfair offers are associated with increased activity in the ventrolateral prefrontal cortex (vlPFC), a region involved in emotion regulation, and decreased activity in the AI, which is linked to negative affect (Tabibnia et al., 2008). Individuals with high monetary gains showed increased ventromedial prefrontal cortex (vmPFC) activity but also decreased AI activity (Tabibnia et al., 2008; Gilam et al., 2015). Furthermore, patients with vmPFC damage had lower ARs than control groups (Koenigs and Tranel, 2007). The studies suggested that brain areas associated with emotion regulation, such as vlPFC and vmPFC, may be engaged to diminish the aversion-related AI’s response (Tabibnia et al., 2008; Gilam et al., 2015) and increase the ARs of unfair offers.

Second, multiple emotion regulation strategies can change decisions by regulating emotions. Researchers have employed two strategies for emotion regulation in fairness-related decision making: reappraisal and expressive suppression. The results showed that although the two strategies could reduce the negative emotions of responders to unfair offers, though compared with expressive suppression, the reappraisal strategy was more effective in changing responders’ emotions and making them accept more unfair offers (Kirk et al., 2006; van’t Wout et al., 2010; Fabiansson and Denson, 2012). In addition, reappraisal strategies may continue to reduce participants’ negative emotions and make them propose more fair offers during a second interaction with partners who treated them unfairly in a previous interaction, whereas the expressive suppression strategy may reduce participants’ previous negative emotions with no effect of ridding themselves of negative treatment, resulting in the proposal of unfair offers (van’t Wout et al., 2010; Fabiansson and Denson, 2012). The results showed that to change emotions and behaviors using an emotion regulation strategy and to avoid previous negative impact, the reappraisal strategy is considerably more effective than expressive suppression and can extend beyond a single encounter to influence future interaction. Grecucci furthered the study of reappraisal strategies by discussing up- and down-regulation (Grecucci et al., 2013b). The former refers to the interpretation of intentions and behaviors of unfair offers as more negative (i.e., the player is a selfish person and wants to keep all the monetary gains), whereas the latter refers to these as less negative (i.e., the proposers’ debt problems leading them to gain more). The results showed that responders with an up-regulation strategy rejected more unfair offers in contrast with down-regulation, demonstrating that reappraisal strategies may change the way responders understand others’ intentions and affect their emotional reaction, resulting in changed decisions. Overall, the reappraisal strategy can modulate the impact of emotional stimuli, contributing to our decisions flexibly (Grecucci et al., 2013b). Neuroimaging studies revealed that the dorsolateral prefrontal cortex (DLPFC) and bilateral ACC play vital roles in the reappraisal process. The DLPFC is associated with cognitive control and inhibition (Miller and Cohen, 2001) as the basis of the generation and maintenance of reappraisal strategies (Ochsner et al., 2002; Ochsner and Gross, 2005). Additionally, Buckholtz et al. (2008, 2015), Buckholtz and Marois (2012) proposed the integrative model of DLPFC function, which suggested the role of DLPFC in the representational integration of the distinct information streams used to make punishment decisions. When applying cognition reappraisal in fairness-related decision making, the evaluation of fairness and the information concerning harm and blame changed. Therefore, the DLPFC activated to integrate the information from emotional response, regulation strategy, fairness evaluation and other sources to make punishment decisions. Furthermore, the ACC monitors and evaluates conflicting responses or motives (Yeung and Sanfey, 2004; Ochsner and Gross, 2005).

In addition to reappraisal and expressive suppression, expected emotion is an effective way of regulating fairness-related decision making. With regard to changing a decision, some studies have investigated the regulation of individuals’ expected emotion induced by the decision outcome. In the decision stage, responders will attempt to predict the probabilities of different outcomes and the emotional consequences associated with alternative actions. To minimize negative emotion and maximize positive emotion, responders will adjust their decisions (Loewenstein and Lerner, 2003; Rick and Loewenstein, 2007). If they predict they will be proud of their fair offers, more fair offers will be given, whereas if they predict that they will feel regretful, less fair offers will be chosen. The expected emotion helps them to anticipate future outcomes and modify their behaviors to evoke desirable emotions and avoid undesirable results. When an individual can expect a positive outcome, it is likely that a current offer will be supported. In contrast, an expected negative outcome will lead to modification of the current activities (Baumeister et al., 2007). Some researchers have manipulated the expected emotion using the autobiographical recall task and found that anticipated pride about fair behavior increased levels of fairness, whereas anticipated pride about unfair behavior decreased levels of fairness. Similarly, anticipated regret about fair behavior reduced levels of fairness, whereas anticipated regret about unfairness increased levels of fairness (van der Schalk et al., 2012). If the proposers were required to observe pride or regret after making fair or unfair offers in the UG, they made fewer fair offers if they had seen the responder’s regret about a fair offer, whereas they made more fair offers if they had seen the responder’s regret about unfair offers (van der Schalk et al., 2014). The results showed that past emotional experience make people reflect on and modify the outcome of their behavior because they pursue not only maximized benefits but also positive emotional experiences (Mellers et al., 1999; Loewenstein and Lerner, 2003). Other studies on regulating strategies of delay or distraction revealed that the delay of a decision did not change the emotional experience or behavior (Bosman et al., 2001), whereas distraction only decreased anger but did not change fairness-related or other decisions when anger was induced again by the same stimulus (Gross and Levenson, 1993; Gross, 1999; Xiao and Houser, 2005; Fabiansson and Denson, 2012).

Neural mechanism studies on the emotion regulation of fairness-related decision making have supported Dual-process Systems. The interaction of the automatic processing emotional system and the controlled cognitive system affects people’s behavior. The emotional system includes the insula, which is associated with aversion to violating norms (Sanfey et al., 2003; Guo et al., 2013); the amygdala, which is associated with negative emotions (Haruno and Frith, 2010; Haruno et al., 2014); and the vmPFC, which is associated with encoding subjective values of perceived offers and emotion regulation (Tabibnia et al., 2008; Baumgartner et al., 2011; Gilam et al., 2015). In addition, the controlled cognitive system involves the dorsal ACC, which regulates the conflict of norm enforcement and self-interest and DLPFC (Knoch et al., 2006, 2008; Baumgartner et al., 2011) related to executive control.

Dual-process Systems focus on the function of emotions and involve the interaction of emotion and cognition for fairness-related decision making. This model has been supported by many behavioral and neuroimaging studies (Sanfey et al., 2003; Baumgartner et al., 2011). This model also proposes strategies for regulating emotion that provide a new way of changing fairness-related decision making (Knoch et al., 2006, 2008). However, current evidence is limited to the regulation of negative emotion induced by an offer (Grecucci et al., 2013a,b). Little is known about the regulation of incidental emotion in fairness-related decision making.

 A Schematic Illustration of the Influence of Emotion on Fairness-Related Decision Making

In complex social environments, both the emotion and cognition systems are involved in processing the fairness perception of resource distribution (see Figure 1). The Wounded Pride/Spite Model and the Affect Infusion Model describe the influence of integral emotion aroused by task and incidental emotion aroused by task-unrelated resources, respectively. For instance, compared with fair offers, unfair offers have been associated with greater activation of the insula, which is involved in aversion emotion (Sanfey et al., 2003; Takagishi et al., 2009; ?), whereas fair offers have been linked to the activation of reward regions, such as the ventral striatum (Tabibnia et al., 2008). Additionally, individuals in sad or angry moods showed an enhanced perception of unfairness, with a greater activation of the insula and amygdala (Harle et al., 2012). The Dual-process Systems perspective proposes that the rational system could regulate emotion to both up- and down-regulate fairness-related decision making. For example, the ACC monitors and evaluates conflicts between norm enforcement and financial benefit (Yeung and Sanfey, 2004; Ochsner and Gross, 2005). The vlPFC and vmPFC associated with emotion regulation could decrease the activation of AI to diminish conflicts (Tabibnia et al., 2008; Gilam et al., 2015). The DLPFC is associated with cognitive control and inhibition (Miller and Cohen, 2001) and influences generation and maintenance reappraisal strategies (Ochsner et al., 2002; Ochsner and Gross, 2005). It can integrate the information from emotional response, regulation strategy, fairness evaluation and other sources to make punishment decisions (Buckholtz and Marois, 2012).

A schematic illustration of the influence of emotion on fairness-related decision making. The Wounded Pride/Spite Model and the Affect Infusion Model describe the influence of emotion, whereas the Dual-Process Systems Model proposes that cognition could regulate emotion to regulate fairness-related decision making. The related brain regions include the insula, amygdala (Amy), striatum (Str), ventrolateral prefrontal cortex (vlPFC), ventromedial prefrontal cortex (vmPFC), dorsolateral prefrontal cortex (DLPFC), and anterior cingulate cortex (ACC).

 Summary and Prospects

In the history of studies on fairness-related decision making, the hypothesis has changed from viewing responders as completely rational with no influence from emotion to regarding both emotion and cognition as important factors in Dual-process Systems. Many studies have revealed that emotion plays an important role in fairness-related decision making. Based on the review of the theoretical and empirical studies, we conclude that the future research scope of the influence of emotion in fairness-related decision making can be furthered in the following ways.

First, recent studies that have induced incidental emotions are limited to several basic emotions, such as happiness, sadness, anger or disgust. However, as a social animal, humans have complicated, delicate and vast social structures and interpersonal relations. Among these, social emotions are one of the important motivations for human behavior. Since fairness is one of the basic norms in human society, it is influenced by many social emotions (Takahashi et al., 2009). As a result, future research should explore the impact of social emotions, including both positive social emotions (empathy, gratitude) and negative social emotions (envy, indignation), on fairness-related decision making.

Second, reappraisal is a common strategy to regulate emotional response, but this strategy involves reinterpreting the meaning of a stimulus. In studies on fairness-related decision making, responders can adopt an up-regulation strategy or a down-regulation strategy. Responders must evaluate the motivations and behaviors of proposers to decrease the anger or disgust caused by unfair offers (Grecucci et al., 2013b). However, reappraisal may induce other emotions, such as empathy from down-regulation (Gross, 2013). Future studies should aim to identify the irrelevant emotions aroused by the regulation strategy that may influence fairness-related decision making.

Third, some personal traits, such as emotional dispositions (Dunn et al., 2010), social value orientation (Karagonlar and Kuhlman, 2013; Haruno et al., 2014), and personality characteristics (Spitzer et al., 2007; Osumi et al., 2012), may influence personal emotional response and regulation, thus affecting fairness-related decision making. For this reason, we suggest that future studies should explore the possible interaction of personality traits, emotion and unfair offers.

Finally, the standard UG paradigm has been widely used in studies on the influence of emotions on fairness-related decision making. Some complex, modified versions of the UG may complicate the context of fairness-related decision making, but may nevertheless be accurate models of real-world situations. For instance, we can put fairness-related decision making in the more complex background of social comparison (Wu et al., 2011; Alexopoulos et al., 2012; McDonald et al., 2013), the loss context (Buchan et al., 2005; Zhou and Wu, 2011; Guo et al., 2013), or making responders perceive the intentions of the proposer (Radke et al., 2012; Ma et al., 2015). As a result, future studies on the influence of emotions on fairness-related decision making should consider ecological validity to make the studies more realistic.

 Author Contributions

Conceived and designed the study: ZY, YZ, and XL. Literature search and synthesis: CJ and YQ. Wrote the paper: ZY and YZ.

 Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. This research was supported by the National Natural Science Foundation of China (Grants 31571161, 31200782, 31500872, and 31640039), the China Scholarship Council, and the National Social Science Foundation of China (Grant 14ZDB161).

 References Alexopoulos J. Pfabigan D. M. Lamm C. Bauer H. Fischmeister F. P. (2012). Do we care about the powerless third? An ERP study of the three-person ultimatum game. Front. Hum. Neurosci. 6:59. 10.3389/fnhum.2012.00059 Allred K. G. Mallozzi J. S. Matsui F. Raia C. P. (1997). The influence of anger and compassion on negotiation performance. Organ. Behav. Hum. Decis. Process. 70 175–187. 10.1006/obhd.1997.2705 Andrade E. B. Ariely D. (2009). The enduring impact of transient emotions on decision making. Organ. Behav. Hum. Decis. Process. 109 1–8. 10.1016/j.obhdp.2009.02.003 Andrade E. B. Ho T. H. (2007). How is the boss’s mood today? I want a raise. Psychol. Sci. 18 668–671. 10.1111/j.1467-9280.2007.01956.x Bacharach S. B. Lawler E. J. (1981). Bargaining: Power, Tactics and Outcomes. San Francisco, CA: Jossey-Bass Inc. Baumeister R. F. Vohs K. D. DeWall C. N. Zhang L. (2007). How emotion shapes behavior: feedback, anticipation, and reflection, rather than direct causation. Pers. Soc. Psychol. Rev. 11 167–203. 10.1177/1088868307301033 Baumgartner T. Knoch D. Hotz P. Eisenegger C. Fehr E. (2011). Dorsolateral and ventromedial prefrontal cortex orchestrate normative choice. Nat. Neurosci. 14 1468–1474. 10.1038/nn.2933 Bediou B. Scherer K. R. (2014). Egocentric fairness perception: emotional reactions and individual differences in overt responses. PLOS ONE 9:e88432. 10.1371/journal.pone.0088432 Berkowitz L. Harmon-Jones E. (2004). Toward an understanding of the determinants of anger. Emotion. 4 107–130. 10.1037/1528-3542.4.2.107 Bless H. Fiedler K. Forgas J. (2006). “Mood and the regulation of information processing and behavior,” in Hearts and Minds: Affective Influences on Social Cognition and Behavior, ed. Forgas J. P. (New York, NY: Psychology Press), 65–84. Blount S. (1995). When social outcomes aren’t fair: the effect of causal attributions on preferences. Organ. Behav. Hum. Decis. Process. 63 131–144. 10.1006/obhd.1995.1068 Bolton G. E. Ockenfels A. (2000). ERC: a theory of equity, reciprocity, and competition. Am. Econ. Rev. 90 166–193. 10.1257/aer.90.1.166 Bonini N. Hadjichristidis C. Mazzocco K. Dematte M. L. Zampini M. Sbarbati A. (2011). Pecunia olet: the role of incidental disgust in the ultimatum game. Emotion 11 965–969. 10.1037/a0022820 Bosman R. Sonnemans J. Zeelenberg M. (2001). Emotions, Rejections, and Cooling off in the Ultimatum Game. Working Paper. Amsterdam: University of Amsterdam. Buchan N. Croson R. Johnson E. Wu G. (2005). “Gain and loss ultimatums,” in Experimental and Behavioral Economics, ed. Morgan J. (Bingley: Emerald Group Publishing Limited), 1–23. Buckholtz J. W. Asplund C. L. Dux P. E. Zald D. H. Gore J. C. Jones O. D. (2008). The neural correlates of third-party punishment. Neuron 60 930–940. 10.1016/j.neuron.2008.10.016 Buckholtz J. W. Marois R. (2012). The roots of modern justice: cognitive and neural foundations of social norms and their enforcement. Nat. Neurosci. 15 655–661. 10.1038/nn.3087 Buckholtz J. W. Martin J. W. Treadway M. T. Jan K. Zald D. H. Jones O. (2015). From blame to punishment: disrupting prefrontal cortex activity reveals norm enforcement mechanisms. Neuron 87 1369–1380. 10.1016/j.neuron.2015.08.023 Camerer C. Thaler R. H. (1995). Anomalies: ultimatums, dictators and manners. J. Econ. Perspect. 9 209–219. 10.1257/jep.9.2.209 Carnevale P. J. D. Isen A. M. (1986). The influence of positive affect and visual access on the discovery of integrative solutions in bilateral negotiation. Organ. Behav. Hum. Decis. Process. 37 1–13. 10.1016/0749-5978(86)90041-5 Carver C. S. Harmon-Jones E. (2009). Anger is an approach-related affect: evidence and implications. Psychol. Bull. 135 183–204. 10.1037/a0013965 Chapman H. A. Kim D. A. Susskind J. M. Anderson A. K. (2009). In bad taste: evidence for the oral origins of moral disgust. Science 323 1222–1226. 10.2307/25471595 Civai C. Crescentini C. Rustichini A. Rumiati R. I. (2012). Equality versus self-interest in the brain: differential roles of anterior insula and medial prefrontal cortex. Neuroimage 62 102–112. 10.1016/j.neuroimage.2012.04.037 Dunn B. D. Evans D. Makarova D. White J. Clark L. (2012). Gut feelings and the reaction to perceived inequity: the interplay between bodily responses, regulation, and perception shapes the rejection of unfair offers on the ultimatum game. Cogn. Affect. Behav. Neurosci. 12 419–429. 10.3758/s13415-012-0092-z Dunn B. D. Makarova D. Evans D. Clark L. (2010). “I’m worth more than that”: trait positivity predicts increased rejection of unfair financial offers. PLOS ONE 5:e15095. 10.1371/journal.pone.0015095 Fabiansson E. C. Denson T. F. (2012). The effects of intrapersonal anger and its regulation in economic bargaining. PLOS ONE 7:e51595. 10.1371/journal.pone.0051595 Falk A. Fischbacher U. (2006). A theory of reciprocity. Games Econ. Behav. 54 293–315. 10.1016/j.geb.2005.03.001 Fehr E. Schmidt K. M. (1999). A theory of fairness, competition, and cooperation. Q. J. Econ. 114 817–868. 10.1162/003355399556151 Feng C. Luo Y.-J. Krueger F. (2015). Neural signatures of fairness-related normative decision making in the ultimatum game: a coordinate-based meta-analysis. Hum. Brain Mapp. 36 591–602. 10.1002/hbm.22649 Ferguson E. Maltby J. Bibby P. A. Lawrence C. (2014). Fast to forgive, slow to retaliate: intuitive responses in the ultimatum game depend on the degree of unfairness. PLOS ONE 9:e96344. 10.1371/journal.pone.0096344 Forgas J. P. (2002). Feeling and doing: affective influences on interpersonal behavior. Psychol. Inq. 13 1–28. 10.1207/S15327965PLI1301-01 Forgas J. P. Bower G. H. Moylan S. J. (1990). Praise or blame? Affective influences on attributions for achievement. J. Pers. Soc. Psychol. 59 809–819. 10.1037/0022-3514.59.4.809 Forgas J. P. Davidson R. Scherer K. Goldsmith H. (2003). “Affective influences on attitudes and judgments,” in Handbook of Affective Sciences, eds Davidson R. J. Scherer K. R. Goldsmith H. H. (New York, NY: Oxford University Press), 596–618. Forgas J. P. Tan H. B. (2013a). Mood effects on selfishness versus fairness: affective influences on social decisions in the ultimatum game. Soc. Cogn. 31 504–517. 10.1521/soco-2012-1006 Forgas J. P. Tan H. B. (2013b). To give or to keep? Affective influences on selfishness and fairness in computer-mediated interactions in the dictator game and the ultimatum game. Comput. Hum. Behav. 29 64–74. 10.1016/j.chb.2012.07.017 Frijda N. H. (1986). The Emotions. Cambridge: Cambridge University Press. Gilam G. Lin T. Raz G. Azrielant S. Fruchter E. Ariely D. (2015). Neural substrates underlying the tendency to accept anger-infused ultimatum offers during dynamic social interactions. Neuroimage 120 400–411. 10.1016/j.neuroimage.2015.07.003 Grecucci A. Giorgetta C. Bonini N. Sanfey A. G. (2013a). Reappraising social emotions: the role of inferior frontal gyrus, temporo- parietal junction and insula in interpersonal emotion regulation. Front. Hum. Neurosci. 7:523. 10.3389/fnhum.2013.00523 Grecucci A. Giorgetta C. van’t Wout M. Bonini N. Sanfey A. G. (2013b). Reappraising the ultimatum: an fMRI study of emotion regulation and decision making. Cereb. Cortex 23 399–410. 10.1093/cercor/bhs028 Gross J. J. (1999). Emotion regulation: past, present, future. Cogn. Emot. 13 551–573. 10.1080/026999399379186 Gross J. J. (2013). Handbook of Emotion Regulation. New York City, NY: Guilford publications. Gross J. J. Levenson R. W. (1993). Emotional suppression: physiology, self-report, and expressive behavior. J. Pers. Soc. Psychol. 64:970. 10.1037//0022-3514.64.6.970 Guclu B. Ertac S. Hortacsu A. List J. A. (2012). Mental attributes and temporal brain dynamics during bargaining: EEG source localization and neuroinformatic mapping. Soc. Neurosci. 7 159–177. 10.1080/17470919.2011.586902 Guo X. Zheng L. Zhu L. Li J. Wang Q. Dienes Z. (2013). Increased neural responses to unfairness in a loss context. Neuroimage 77 246–253. 10.1016/j.neuroimage.2013.03.048 Güth W. Kocher M. G. (2014). More than thirty years of ultimatum bargaining experiments: motives, variations, and a survey of the recent literature. J. Econ. Behav. Organ. 108 396–409. 10.1016/j.jebo.2014.06.006 Güth W. Schmittberger R. Schwarze B. (1982). An experimental-analysis of ultimatum bargaining. J. Econ. Behav. Organ. 3 367–388. 10.1016/0167-2681(82)90011-7 Haidt J. (2001). The emotional dog and its rational tail: a social intuitionist approach to moral judgment. Psychol. Rev. 108 814–834. 10.1037/0033-295X.108.4.814 Harle K. M. Chang L. J. van ’t Wout M. Sanfey A. G. (2012). The neural mechanisms of affect infusion in social economic decision-making: a mediating role of the anterior insula. Neuroimage 61 32–40. 10.1016/j.neuroimage.2012.02.027 Harle K. M. Sanfey A. G. (2007). Incidental sadness biases social economic decisions in the ultimatum game. Emotion 7 876–881. 10.1037/1528-3542.7.4.876 Harle K. M. Sanfey A. G. (2010). Effects of approach and withdrawal motivation on interactive economic decisions. Cogn. Emot. 24 1456–1465. 10.1080/02699930903510220 Haruno M. Frith C. D. (2010). Activity in the amygdala elicited by unfair divisions predicts social value orientation. Nat. Neurosci. 13 160–161. 10.1038/nn.2468 Haruno M. Kimura M. Frith C. D. (2014). Activity in the nucleus accumbens and amygdala underlies individual differences in prosocial and individualistic economic choices. J. Cogn. Neurosci. 26 1861–1870. 10.1162/jocn_a_00589 Hastie R. (2001). Problems for judgment and decision making. Annu. Rev. Psychol. 52 653–683. 10.1146/annurev.psych.52.1.653 Hewig J. Kretschmer N. Trippe R. H. Hecht H. Coles M. G. Holroyd C. B. (2011). Why humans deviate from rational choice. Psychophysiology 48 507–514. 10.1111/j.1469-8986.2010.01081.x Kahneman D. Tversky A. (1979). Prospect theory: an analysis of decision under risk. Econometrica 47 263–291. 10.2307/1914185 Karagonlar G. Kuhlman D. M. (2013). The role of social value orientation in response to an unfair offer in the ultimatum game. Organ. Behav. Hum. Decis. Process. 120 228–239. 10.1016/j.obhdp.2012.07.006 Kirk D. Carnevale P. J. Gollwitzer P. M. (2006). Self-Regulation in Ultimatum Bargaining: Controlling Emotion with Binding Goals. Available at SSRN: https://ssrn.com/abstract=539843. 10.2139/ssrn.913732 Knoch D. Nitsche M. A. Fischbacher U. Eisenegger C. Pascual-Leone A. Fehr E. (2008). Studying the neurobiology of social interaction with transcranial direct current stimulation - The example of punishing unfairness. Cereb. Cortex 18 1987–1990. 10.1093/cercor/bhm237 Knoch D. Pascual-Leone A. Meyer K. Treyer V. Fehr E. (2006). Diminishing reciprocal fairness by disrupting the right prefrontal cortex. Science 314 829–832. 10.1126/science.1129156 Knutson B. (1996). Facial expressions of emotion influence interpersonal trait inferences. J. Nonverbal Behav. 20 165–182. 10.1007/bf02281954 Knutson B. Rick S. Wimmer G. E. Prelec D. Loewenstein G. (2007). Neural predictors of purchases. Neuron 53 147–156. 10.1016/j.neuron.2006.11.010 Koenigs M. Tranel D. (2007). Irrational economic decision-making after ventromedial prefrontal damage: evidence from the ultimatum game. J. Neurosci. 27 951–956. 10.1523/jneurosci.4606-06.2007 Lang P. J. Bradley M. M. Cuthbert B. N. (1997). “Motivated attention: affect, activation and action,” in Attention and Orienting: Sensory and Motivational Processes, eds Lang P. J. Simons R. F. Balaban M. T. (Hillsdale, NJ: Lawrence Erlbaum Associates, Inc), 97–135. Liu C. Chai J. W. Yu R. (2016). Negative incidental emotions augment fairness sensitivity. Sci. Rep. 6:24892. 10.1038/srep24892 Loewenstein G. Lerner J. S. (2003). “The role of affect in decision making,” in Handbook of Affective Science, eds Davidson R. J. Scherer K. R. Goldsmith H. H. (New York, NY: Oxford University Press), 3. Loewenstein G. O’Donoghue T. (2004). Animal Spirits: Affective and Deliberative Processes in Economic Behavior. Available at SSRN: https://ssrn.com/abstract=539843. 10.2139/ssrn.539843 Ma Q. Meng L. Zhang Z. Xu Q. Wang Y. Shen Q. (2015). You did not mean it: perceived good intentions alleviate sense of unfairness. Int. J. Psychophysiol. 96 183–190. 10.1016/j.ijpsycho.2015.03.011 McDonald I. M. Nikiforakis N. Olekalns N. Sibly H. (2013). Social comparisons and reference group formation: Some experimental evidence. Games Econ. Behav. 79 75–89. 10.1016/j.geb.2012.12.003 Mellers B. Schwartz A. Ritov I. (1999). Emotion-based choice. J. Exp. Psychol. 128 332–345. 10.1037/0096-3445.128.3.332 Miller E. K. Cohen J. D. (2001). An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24 167–202. 10.1146/annurev.neuro.24.1.167 Moretti L. Di Pellegrino G. (2010). Disgust selectively modulates reciprocal fairness in economic interactions. Emotion 10 169–180. 10.1037/a0017826 Mussel P. Goritz A. S. Hewig J. (2013). The value of a smile: facial expression affects ultimatum-game responses. Judgm. Decis. Mak. 8 381–385. Ochsner K. N. Bunge S. A. Gross J. J. Gabrieli J. D. E. (2002). Rethinking feelings: an fMRI study of the cognitive regulation of emotion. J. Cogn. Neurosci. 14 1215–1229. 10.1162/089892902760807212 Ochsner K. N. Gross J. J. (2005). The cognitive control of emotion. Trends Cogn. Sci. 9 242–249. 10.1016/j.tics.2005.03.010 Osumi T. Nakao T. Kasuya Y. Shinoda J. Yamada J. Ohira H. (2012). Amygdala dysfunction attenuates frustration-induced aggression in psychopathic individuals in a non-criminal population. J. Affect. Disord. 142 331–338. 10.1016/j.jad.2012.05.012 Osumi T. Ohira H. (2009). Cardiac responses predict decisions: an investigation of the relation between orienting response and decisions in the ultimatum game. Int. J. Psychophysiol. 74 74–79. 10.1016/j.ijpsycho.2009.07.007 Paulus M. P. Rogalsky C. Simmons A. Feinstein J. S. Stein M. B. (2003). Increased activation in the right insula during risk-taking decision making is related to harm avoidance and neuroticism. Neuroimage 19 1439–1448. 10.1016/S1053-8119(03)00251-9 Pillutla M. M. Murnighan J. K. (1996). Unfairness, anger, and spite: emotional rejections of ultimatum offers. Organ. Behav. Hum. Decis. Process. 68 208–224. 10.1006/obhd.1996.0100 Rabin M. (1993). Incorporating fairness into game theory and economics. Am. Econ. Rev. 83 1281–1302. 10.2307/2117561 Radke S. Guroglu B. de Bruijn E. R. (2012). There’s something about a fair split: intentionality moderates context-based fairness considerations in social decision-making. PLOS ONE 7:e31491. 10.1371/journal.pone.0031491 Rick S. Loewenstein G. (2007). “The role of emotion in economic behavior,” in Handbook of Emotions, eds Lewis M. Haviland-Jones J. M. Feldman Barrett L. (New York, NY: Oxford University Press). Riepl K. Mussel P. Osinsky R. Hewig J. (2016). Influences of state and trait affect on behavior, feedback-related negativity, and P3b in the ultimatum game. PLOS ONE 11:e0146358. 10.1371/journal.pone.0146358 Rilling J. K. Sanfey A. G. (2011). The neuroscience of social decision-making. Annu. Rev. Psychol. 62 23–48. 10.1146/annurev.psych.121208.131647 Rozin P. Haidt J. McCauley C. R. (2000). “Disgust,” in Handbook of Emotions, eds Lewise M. Haviland J. M. (New York, NY: Guilford Press), 637–653. Sanfey A. G. Chang L. J. (2008). Multiple systems in decision making. Ann. N. Y. Acad. Sci. 1128 53–62. 10.1196/annals.1399.007 Sanfey A. G. Loewenstein G. McClure S. M. Cohen J. D. (2006). Neuroeconomics: cross-currents in research on decision-making. Trends Cogn. Sci. 10 108–116. 10.1016/j.tics.2006.01.009 Sanfey A. G. Rilling J. K. Aronson J. A. Nystrom L. E. Cohen J. D. (2003). The neural basis of economic decision-making in the ultimatum game. Science 300 1755–1758. 10.1126/science.1082976 Schneirla T. C. (1959). “An evolutionary and developmental theory of biphasic processes underlying approach and withdrawal,” in Nebraska Symposium on Motivation, ed. Jones M. R. (Lincoln, NE: University of Nebraska Press), 1–42. Spitzer M. Fischbacher U. Herrnberger B. Grön G. Fehr E. (2007). The neural signature of social norm compliance. Neuron 56 185–196. 10.1016/j.neuron.2007.09.011 Straub P. G. Murnighan J. K. (1995). An experimental investigation of ultimatum games: information, fairness, expectations, and lowest acceptable offers. J. Econ. Behav. Organ. 27 345–364. 10.1016/0167-2681(94)00072-M Tabibnia G. Satpute A. B. Lieberman M. D. (2008). The sunny side of fairness - Preference for fairness activates reward circuitry (and disregarding unfairness activates self-control circuitry). Psychol. Sci. 19 339–347. 10.1111/j.1467-9280.2008.02091.x Takagishi H. Takahashi T. Toyomura A. Takashino N. Koizumi M. Yamagishi T. (2009). Neural correlates of the rejection of unfair offers in the impunity game. Neuroendocrinol. Lett. 30 496–500. Takahashi H. Kato M. Matsuura M. Mobbs D. Suhara T. Okubo Y. (2009). When your gain is my pain and your pain is my gain: neural correlates of envy and schadenfreude. Science 323 937–939. 10.1126/science.1165604 Thaler R. H. (1988). Anomalies: the ultimatum game. J. Econ. Perspect. 2 195–206. 10.1257/jep.2.4.195 Tiedens L. Z. (2001). Anger and advancement versus sadness and subjugation: the effect of negative emotion expressions on social status conferral. J. Pers. Soc. Psychol. 80 86–94. 10.1037/0022-3514.80.1.86 van der Schalk J. Bruder M. Manstead A. (2012). Regulating emotion in the context of interpersonal decisions: the role of anticipated pride and regret. Front. Psychol. 3:513. 10.3389/fpsyg.2012.00513 van der Schalk J. Kuppens T. Bruder M. Manstead A. S. (2014). The social power of regret: the effect of social appraisal and anticipated emotions on fair and unfair allocations in resource dilemmas. J. Exp. Psychol. 144 151–157. 10.1037/xge0000036 van’t Wout M. Chang L. J. Sanfey A. G. (2010). The influence of emotion regulation on social interactive decision-making. Emotion 10 815–821. 10.1037/a0020069 van’t Wout M. Kahn R. S. Sanfey A. G. Aleman A. (2006). Affective state and decision-making in the ultimatum game. Exp. Brain Res. 169 564–568. 10.1007/s00221-006-0346-5 Voegele C. Sorg S. Studtmann M. Weber H. (2010). Cardiac autonomic regulation and anger coping in adolescents. Biol. Psychol. 85 465–471. 10.1016/j.biopsycho.2010.09.010 Von Neumann J. Morgenstern O. (2007). Theory of Games and Economic Behavior. Princeton, NJ: Princeton university press. Wu Y. Zhou Y. van Dijk E. Leliveld M. C. Zhou X. (2011). Social comparison affects brain responses to fairness in asset division: an ERP study with the ultimatum game. Front. Hum. Neurosci. 5:131. 10.3389/fnhum.2011.00131 Xiang T. Lohrenz T. Montague P. R. (2013). Computational substrates of norms and their violations during social exchange. J. Neurosci. 33 1099–1108. 10.1523/jneurosci.1642-12.2013 Xiao E. Houser D. (2005). Emotion expression in human punishment behavior. Proc. Natl. Acad. Sci. U.S.A. 102 7398–7401. 10.1073/pnas.0502399102 Yamagishi T. Horita Y. Takagishi H. Shinada M. Tanida S. Cook K. S. (2009). The private rejection of unfair offers and emotional commitment. Proc. Natl. Acad. Sci. U.S.A. 106 11520–11523. 10.1073/pnas.0900636106 Yeung N. Sanfey A. G. (2004). Independent coding of reward magnitude and valence in the human brain. J. Neurosci. 24 6258–6264. 10.1523/jneurosci.4537-03.2004 Zhou X. Wu Y. (2011). Sharing losses and sharing gains: increased demand for fairness under adversity. J. Exp. Soc. Psychol. 47 582–588. 10.1016/j.jesp.2010.12.017