Human judgment is by nature comparative. When people make evaluations, they do so in relation to a pertinent norm or standard. To describe oneself as tall, for example, implies that one is taller than others. Even such a basic statement about physical properties is therefore inherently comparative 1. Comparisons constitute central mechanisms of social judgment and, as a result, stand at the core of a whole range of social cognitive processes. Person perception 2–5, stereotyping 6, attitudes 7, affect 8,9, decision making 10,11, theory of mind 12, and the concept of self 13,14 all rely on comparative processes. Over 50 years of psychological research has shown that social comparisons form one of the cornerstones of social cognition 15.
One of the reasons that could explain the ubiquity of social comparisons is that they provide efficient strategies to make judgments and decisions. By focusing on a subset of information rather than engaging in an exhaustive search of one’s knowledge base, social comparisons enable humans to save scarce cognitive resources 16. This cognitive benefit also shows at the brain level: during a judgment task, comparative information processing was associated with smaller changes in alpha-band activity, suggesting reduced mental effort 17.
In the last few years, neuroscientists have begun to study the neural correlates of social comparison using functional neuroimaging and noninvasive electrophysiological methods. The aim of the present article is to provide an integrative summary and discussion of this research. Our review is guided by the two main research lines that social neuroscientists have pursued so far. In the first part of this review, we will examine neural evidence suggesting that humans spontaneously rely on social comparison when processing information about themselves or other people. In the second part, we will consider the potential neural structures supporting this mechanism. Finally, we will address questions that entail challenges for future directions such as the connections between the different systems that play a role in social comparison.
Brain response to objective and relative outcomes
When looking for happiness and life satisfaction, people often pursue greater wealth. Reflecting this general tendency of humans to increase their own wealth, traditional economic models of decision-making posit that individual well-being is determined primarily by one’s absolute income. Real-life observation and experiments in social environments, however, offer another perspective. What seems to characterize people’s subjective well-being is not only how much they own in absolute terms but also how much they own in comparison with others. Social psychologists and anthropologists have indeed shown that social comparisons influence subjective well-being and behavior 18,19. Do they also influence brain processing of outcomes? Social neuroscience has addressed this question by investigating the influence of social comparison on two components of the brain reward system 20: the ventral striatum (VS) and the dorsal anterior cingulate cortex (dACC).
The VS constitutes one of the main structures of the reward system. It encompasses the nucleus accumbens, the ventromedial parts of the caudate nucleus and putamen, the olfactory tubercle, and the lateral olfactory tract 21. The VS reacts to both primary (e.g., pleasant tastes) and secondary rewards (e.g., monetary incentives) and seems to play a role in the formation of stimulus–reward association 22. Ventral striatal activity is influenced by different kinds of comparisons such as counterfactuals, temporal comparisons, or expectations 23. Recently, several fMRI studies have investigated whether the VS is also modulated by social comparisons.
These studies have shown that activity in the VS not only depends on absolute but also on relative rewards. For example, in Fliessbach et al.’s fMRI study 24, two participants were simultaneously scanned while performing a simple estimation task (Fig. 1a). Participants’ monetary reward for a given trial depended only on their own performance and was, thus, unrelated to that of the other player. At the end of a trial, participants would, nevertheless, receive a feedback providing information about both participants’ performance and payment. Interestingly, when reading this information, participants seemed to spontaneously engage in social comparison. Results, indeed, showed that ventral striatal activity following gains was not influenced by the absolute amount of money earned but by the relative payoff (Fig. 1b). In other terms, in this experiment, earning 30, 60, or 120 euros did not elicit any significant difference in ventral striatal activity. What caused VS activity to increase was to earn more than the other player. Similar results have been observed by other studies using slightly different paradigms 25–31 and were found in both female and male participants 26,28, suggesting that social comparison exerts a strong and reliable effect on the VS.
The relative information represented in the VS may be used to improve future decisions. To test this hypothesis, Bault et al. 25 ran a lottery experiment involving more or less risky decisions. They found that participants exposed to the performance of another player showed increased activity in the medial prefrontal cortex (mPFC) and other regions involved in the attribution of mental states to others. This effect was observed even though participants’ outcomes did not depend on the other player’s performance. This medial prefrontal activity seemed to be determined by the rewards obtained previously: striatal activation while learning about an outcome predicted mPFC activity when deciding, in the subsequent trial, which of the two lotteries to choose. This suggests that when deciding between two lotteries, participants engaged spontaneously in strategic competitive reasoning and adjusted their behavior to the other player’s to obtain higher payoffs. In line with this hypothesis, behavioral data showed that participants behaved in a more risk-seeking manner when they played in a bold environment in which their counterparts made risky choices. This research thus identifies a network composed of the VS and mPFC that would sustain the mechanism by which social comparison enables adjustment of one’s behavior to the behavior of others. The activity of this network seems, however, to depend on the possibilities for self-improvement.
Zink et al. 32 have, indeed, observed mPFC activity for comparisons of social status with superior others, but they also noticed that the mPFC was only recruited if the hierarchy was unstable and offered promotion opportunities. In both stable and unstable social hierarchies, viewing a superior individual recruited perceptual–attentional, saliency, and cognitive systems. Yet, when participants had the possibility to improve their social status, additional regions were engaged related to social cognition (mPFC) and emotional processing (amygdala). Social comparison, thus, seems to stimulate self-improvement by the activity of interconnected motivational and social neural networks.
Dorsal anterior cingulate cortex
The dACC is another region that plays a key role in the processing of reward prediction and its errors. The dACC is an integrative hub connecting affective, cognitive, and motor brain regions. Its role is to monitor these functions in potentially conflicting situations, when, for example, an error has been committed or when outcomes do not follow expectancies. dACC activity therefore reflects the subjective evaluation of an outcome and can be used as a measure of the deviation from the desired outcome. This function made the dACC a potential target of social comparison.
In line with this idea, Takahashi et al. 33 suggested that perceiving a superior other triggers activity in the dACC and that this activity correlates with envy ratings. Participants in their study read scenarios describing more or less enviable persons. When this person was superior and self-relevant (e.g., a student studying the same major and having similar lifestyle and hobbies) participants reported stronger feelings of envy and showed increased activation in a cluster located at the border between the dACC and the supplementary motor area, a region known for its role in the resolution of cognitive conflict. Moreover, the activation of this area seemed to predict how participants would react to the misfortune of envied others. In a subsequent fMRI study involving the same participants, Takahashi et al. 33 presented descriptions of misfortunes happening to the protagonists of the first study (e.g., ‘he was falsely accused of cheating in an exam’). Learning about the misfortune of envied individuals triggered a feeling of satisfaction, or schadenfreude, accompanied by an increased activity of the ventral striatum. This ventral striatal activity was, in addition, correlated with the activity observed in the first study around the dACC and supplementary motor area: the stronger the dACC activity while thinking about envied others, the greater the activation of the VS while imagining them in difficult situations. [A recently published fMRI experiment failed to replicate the results of Takahashi et al. 33. Chester et al. 34 used a similar paradigm as Takahashi et al.’s 33, but in their study, misfortunes of envied others did not induce any ventral striatal activation. Instead of the VS, they found a lack of dorsomedial Prefrontal Cortex (DMPFC) activation for misfortunes of envied individuals, suggesting that envy reduces participants’ empathic reactions. The discrepancy between these two fMRI studies is in line with behavioral studies that found conflicting evidence on the role of envy in predicting schadenfreude (for a review on this issue, see Powell et al.35).]
The error signal produced by the dACC can be measured as a negative event-related potential on the scalp. This feedback-related negativity (FRN) peaks around 300 ms and is maximal at frontocentral scalp electrode sites 36 (Fig. 2). The FRN is observed following losses or error feedback compared with wins or positive feedback, and can also be induced by positive prediction errors such as that produced by unexpected omissions of pain 38. Several event-related potential (ERP) experiments tested whether the FRN is modulated by social comparison.
ERP experiments investigating the effect of social comparison on reward processing reported discrepant results. In all of these studies, participants performed a simple task (e.g., an estimation of the number of dots on the screen) and received a feedback about their performance and the performance of another player whose reward was independent from the participant’s reward. Yet, although these studies rely on similar experimental designs, they all report different results. Boksem et al. 39 found enhanced FRN when participants’ own outcomes were worse than those of others, but neither Wu et al. 40 nor Qiu et al. 41 replicated these results. What seemed to matter in these two other experiments was not so much whether the participant received a higher payoff than the other player, but rather whether the two players were equitably rewarded. Surprisingly, however, results of Wu et al. 40 and Qiu et al. 41 went in opposite directions. Wu et al. 40 found an equity effect, that is, increased FRN for equal payoffs compared with unequal ones, whereas Qiu et al. 41 observed inequity effects, an enhanced negative component between 350 and 550 ms and located near the ACC in the inequity conditions. The explanation for these apparently inconsistent results may reside in the very nature of the FRN.
The FRN is modulated by several factors that can vary with slight paradigm changes 37. For example, the FRN is sensitive to outcome probability 36. In Wu et al.’s experiment 40, equal payoffs had the lowest probability: the majority of the trials led to unequal payoffs either because the answer of one of the two players was incorrect or because two correct trials were differently rewarded. This may explain why the researchers observed an enhanced FRN for equity conditions. The FRN is also sensitive to expectations 42,43. Qiu et al. 41 reported that their participants expected their rewards to be the same as the other player’s when they were both correct, which may explain why they found a stronger FRN in the inequity conditions as compared with the equity conditions. Finally, the FRN decreases with perceived task difficulty 44,45. Thus, it is possible that when the participant was incorrect, but the other player was correct, the participant assumed that the task must have been rather easy and found their error less forgivable, which in return leads to an enhanced FRN as reported by Boksem et al. 39. The sensitivity of the FRN to these slight paradigm differences makes it difficult to draw clear conclusions on the influence of social comparison. It is thus still unclear whether the FRN and more generally ACC activity are influenced by social comparisons in the same way as the VS is.
Conclusion and future research on the brain response to relative outcomes
Neuroimaging studies provide evidence that the brain relies on social comparison when processing rewarding information. Convergent findings indicate that the VS reacts to relative rewards. This research shows that the VS is modulated by social comparison even when participants’ outcomes do not depend on the other player. This suggests that the brain assesses one’s personal winnings or achievements in comparison with those of others even when this information is irrelevant to the task and reward at hand. These results are consistent with the hypothesis that social comparisons are ‘spontaneous, effortless, and unintentional reactions to the performance of others’ (46, p. 227).
Representation of relative values in the VS influences subsequent decisions through a connection between the VS and the mPFC, an area essential for decision making in social situations. Whether other areas of the reward system are also modulated by social comparison is, however, still unclear. The modulation of the dACC by social comparison still remains to be proven. Experiments testing the influence of social comparison on the FRN are inconsistent and their results may be produced by parameters of the specific experimental paradigms rather than by an actual effect of social comparison.
To our knowledge, the effect of social comparison on the processing of negative outcomes has not been investigated so far. Yet, it has been shown that people rely on social comparisons to cope with difficult situations. Cancer patients, for example, spontaneously engage in comparisons with other patients 47: comparisons with less fortunate others (i.e., downward comparisons) may help minimize the severity of one’s situation and can be used as a strategy to maintain a flattering self-image and positive feelings 48. Previous neuroimaging experiments have found that negative outcomes, such as punishments, involve the lateral orbitofrontal cortex. Future studies could thus investigate whether the lateral orbitofrontal cortex is modulated by social comparison.
To date, neuroimaging studies have mainly used monetary paradigms to test the influence of social comparison on the reward system (for exception see Zink et al. 32). However, people rely on social comparison to evaluate a much broader set of situations and qualities than just money. People do compare their belongings with those of others, but also their personalities, physical characteristics, performances, aptitudes, achievements, statuses, social groups, relationships, emotions, opinions, and behaviors 49–58. It is thus essential to also investigate how comparisons along these different dimensions influence motivational brain systems.
Mechanisms of social comparisons
Neuroimaging research suggests that reward processing is highly relative, which is in agreement with social psychological findings that make comparison one of the central mechanisms of social cognition. Yet, what are the cerebral processes that enable us to compare ourselves to other people? Does social comparison rely on the same brain network as other kinds of comparative judgments or do they engage specific systems?
Extensive research in cognitive neuroscience has identified a network that may be responsible for the representation and comparison of a wide range of nonsocial magnitudes. This network encompasses the intraparietal sulcus (IPS) as well as areas of the prefrontal cortex 59. The activity of this network is modulated by a distance effect: the closer two magnitudes (e.g., two numbers), the more difficult the comparison and the greater the activity of this frontoparietal network 60,61. This network, and in particular the IPS, is recruited by comparisons of numbers presented in different formats (e.g., digits, words), size, dot patterns, line lengths, magnitudes of angles, luminance, and money rewards 60–67. Social neuroscientists have recently begun to investigate its role in social and person comparisons.
So far, the cerebral mechanisms that enable us to compare ourselves to others have received the attention of only one study 68. In this fMRI experiment, participants were asked to compare their own height or intelligence with that of individuals they personally know. Results showed a greater engagement of the IPS in height comparisons than intelligence comparisons. Conversely, intelligence comparisons recruited to a larger extent the mPFC and other areas dedicated to the attribution of mental states to others. These results can be explained in two ways. They may reflect differences in the nature of the information retrieved in memory for the comparison (physical vs. psychological information) or they may result from differences in the comparative process itself (for a discussion of this issue, see Kedia et al. 68). To decide between these alternative explanations, one would need to focus on the comparative process and exclude other perceptual or inferential mechanisms. To date, this approach has not been adopted for self–other comparisons, but it has been applied to other–other comparisons.
One strategy to focus on the comparative process consists of using noncomparative control conditions. Lindner et al. 69 relied on this method to investigate the neural networks recruited by the comparison of two celebrities’ height (Who is taller: Elvis or Bush?) and intelligence (Who is more intelligent: Hanks or Einstein?). In addition to these comparative conditions, the researchers used two control conditions, in which participants had to indicate whether one of the two celebrities was a politician or a musician. This study did not find any activation in the IPS, but rather showed the activity of a network composed of the mPFC and other regions important for social information processing. This network was recruited by both intelligence and height comparisons compared with the control conditions, although activations were stronger for intelligence than height comparisons. This led the authors to conclude that person comparisons rely on different neural comparative systems than comparisons of other categories of objects. This study does, however, entail confounds that would need to be controlled to interpret these results. First, there was no check to assess whether participants knew the celebrities’ height and intelligence and thus had all necessary information to perform the comparisons. Second, the challenge of using a control condition approach is the choice of an appropriate control condition. A good control condition should notably have the same level of difficulty as the conditions of interest, which was not the case in Lindner et al.’s 69 study, in which response times were shorter in the control condition than in the comparative ones. Moreover, the control condition should not involve any kind of comparison, which is difficult, given that comparisons are ubiquitous (categorizing a person as a politician or a musician does involve a comparison between the target to categorize and the musician and politician group categories 70,71). Some have thus suggested another approach that would enable researchers to overcome these limitations.
This other approach makes use of the distance effect, as commonly done to study magnitude comparison and numerical cognition. Some social neuroscientists have indeed reflected that if personal characteristics are similarly represented and compared in the brain as nonsocial magnitudes, they should elicit similar effects and these effects should engage the same neural networks. For example, if person comparisons were to follow a distance effect, one would expect comparisons of persons close on a certain characteristic (e.g., of similar attractiveness) to be more difficult and engage to a greater extent the frontoparietal network associated with nonsocial comparisons. Two articles have already tested this hypothesis for comparisons of height, attractiveness 72, and social status 73. Both studies found behavioral distance effects and, in both studies, these distance effects engaged the IPS (Fig. 3). These results suggest that social and nonsocial comparisons overlap in the parietal cortex.
The finding that comparisons of personal characteristics recruit the same comparative network as nonsocial comparisons does not, however, imply that different kinds of judgments engage strictly identical brain regions. The studies using the distance effect also showed differences between the compared dimensions. For example, height comparisons elicited overall more IPS activity than attractiveness comparisons and attractiveness comparisons elicited overall greater activity in the fusiform gyrus, a region of the occipital cortex dedicated to face perception and recognition 72. However, the distance effects remained unaffected by the compared dimension, which suggests that the comparative process was the same.
A putative model could explain both these similarities and differences. This model assumes that perceptual and evaluative processes vary depending on the compared dimension: facial characteristics such as attractiveness, for example, would recruit the fusiform gyrus whereas body dimensions, such as height, may involve the parietal cortex. This model also assumes that the actual comparison of the extracted magnitudes relies on a common frontoparietal comparative system (Fig. 4).
This model could be tested by investigating the time course of comparison processing using ERPs. The model would then predict differences in early perceptual processes (reflected for example by differences in the N170, the face-sensitive ERP component), but no distance effect of these neural markers. Previous ERP studies have observed that the distance effect for numbers – whether presented in words or Arabic digits – emerges at around 200 ms after stimulus onset 74. One could thus also use electroencephalography to assess whether person comparisons, which involve more complex stimuli than numbers, follow a similar time course as numbers or whether they occur at a later latency.
Conclusion and future research on the underlying mechanisms
Research on the underlying mechanisms of social comparison points to a frontoparietal network also recruited by nonsocial comparisons. The studies that have identified this network relied on comparisons of attractiveness, height, and social status 72,73. Further investigation is needed to test whether this frontoparietal system is also involved in comparisons of complex mental states such as trustworthiness or intelligence. Future research should also investigate whether this network is recruited by spontaneous comparisons, that is, by situations in which participants compare themselves to others even though they were not explicitly instructed to do so (see paradigms described in the first section and Fig. 1a).
On this note, a recent fMRI experiment 75 suggests that the IPS may be recruited by spontaneous comparisons of financial status. Participants of this study were asked to form an impression of targets with high or low annual salaries. Results showed that the IPS was modulated by the financial status of the targets even though participants were not explicitly instructed to evaluate it. This higher IPS activity for low than for high financial statuses can be interpreted as a distance effect: participants may have spontaneously used their own financial status as a comparison standard to judge those of the targets, and the fact that participants’ incomes were closer to the low than to the high financial statuses may have created an effect of distance. This interpretation is, however, speculative, given that the study did not actually measure the distance between participants’ and targets’ financial situations and its effect on the IPS. The role of the IPS in spontaneous social comparisons thus still remains to be determined by more direct investigations.
In general, the involvement of the comparative frontoparietal network should be tested for a broader range of self–other comparisons: it is still unclear whether self–other comparisons involve a distance effect and whether this distance effect relies on the activity of the same frontoparietal network as other–other comparisons. When comparing themselves with others, people show biases that may influence comparative brain processes. For example, people have a tendency to overestimate their qualities and to consider themselves as better than average 76. At the brain level, this biased evaluation occurs with decreased activation of the medial orbitofrontal cortex (mOFC; see Fig. 5 and Beer and Hughes 77). In this context, the mOFC may enable one to correct one’s initial biased evaluation and shift from one’s natural response tendency 78–80. So far, the question of whether (and how) self-related biases influence comparison processes has not received much attention. Do self–other comparisons rely on the same frontoparietal network as other–other and nonsocial comparisons? If so, is this network modulated by self-related brain regions, such as the mOFC? Or do self–other comparisons rather engage brain networks that are distinct from those supporting other kinds of comparisons? Future research should identify the different networks involved in self–other comparisons and analyze how they interact with each other.
Social comparison constitutes a fundamental social cognitive process and is the focus of one of the major theories in social psychology. This research field has recently begun to spread out to neuroscience, but many questions still remain to be explored.
So far, neuroimaging studies on social comparison have either focused on the influence of social comparison on the reward system in gaming situations or on the cognitive and neural mechanisms supporting explicit comparisons. These two research areas have not yet, however, been linked to each other and the question of the connection between the comparative and reward systems still remains to be elucidated. Functional connectivity analyses would be well suited to address this question 81. These analyses rely on fMRI data to characterize the interactions between spatially remote brain regions and could, thus, be used to explore the correlation between the comparative and reward brain systems. This question could also be addressed in the context of the selective accessibility model 15. This social cognitive model posits two ways of comparing oneself with others. On the one hand, one can seek similarities between oneself and the comparison standard and assimilate to this person; on the other hand, one can focus on the dissimilarities and contrast away from the standard. These two comparative processes have opposing consequences. Assimilation to an upward standard (e.g., former race car driver Niki Lauda) leads to a positive self-evaluation (I have high athletic abilities), whereas contrast leads to a negative self-evaluation (I have poor athletic abilities). At the brain level, assimilation and contrast comparison mindsets may reverse the effect of social comparison on the reward system and change the sign of social prediction errors. For example, participants engaging in similarity testing may show higher levels of ventral striatal activity when exposed to a more rewarded co-player. This hypothesis remains to be tested and the effects of similarity and dissimilarity testing on the comparative and affective systems should be explored.
The social psychology literature suggests that the mechanisms underlying social comparison and their connection to the reward system are likely to be modulated by several factors. The standard chosen for the comparison is of primary importance 82,83. In experimental settings, comparison standards have usually been external persons (e.g., a familiar other, a celebrity, a confederate, or another participant) but it would also be interesting to consider internal standards (e.g., ideal, past, or future selves, societal norms). Comparisons with internal standards are frequently used in everyday life to evaluate or motivate oneself and improve one’s performance 84,85. For example, people with chronic medical problems tend to engage in comparisons with their past selves and to consider their present condition as better than it used to be at the beginning of their disease 86. It is, however, still unclear whether comparisons with internal standards recruit the same brain networks as comparisons with external ones.
Previous research in social psychology has also shown how the characteristics of the standard influence the comparison process: people tend to assimilate – rather than contrast away – to similar, familiar, moderate, and psychologically close standards as well as to members of their ingroup 15,87,88. How these characteristics influence the comparative and emotional brain systems would be a question of great interest.
Besides the comparison standard, social comparisons also depend on personality and cultural influences. Although the desire to compare oneself to others is universal, some people are more prone to engage in social comparisons than others. Individuals high in social comparison orientation (SCO) engage in social comparison more often and they are also more affected by it 89. SCO has been shown to correlate with several other personality dimensions. People high in SCO tend to be more self-conscious and show lower self-esteem and higher neuroticism 90. In a similar vein, depressed patients report an increased proneness to compare oneself with others 91,92. Individuals who are prone to social comparisons are more interested in what others feel and need and show higher levels of empathy 90. This suggests that SCO does not merely reflect a competitive mindset but rather an interdependent self. It is therefore not surprising that higher SCO has been observed in women compared with men and in cultures high on interdependence and power distance belief 93. In accordance with these observations, a recent fMRI experiment reports that Korean participants (representing an interdependent culture in the study) show a stronger modulation of the VS by social comparisons than American participants (representing an independent culture 31). On the basis of the general differences in SCO between men and women, one might also expect a modulation by sex. However, neuroimaging studies investigating the neural correlates of social comparison have not observed any significant difference in VS activity between men and women 26–28. It is, however, important to note that all these studies are limited in that they relied on small samples of participants (between eight and 38 of each sex) and may lack the statistical power to show significant differences. Future experiments involving larger samples should thus clarify whether sex differences in social comparison behavior are associated with identifiable neural differences.
All judgments and evaluations are relative in nature and hence rely on comparisons. Social comparisons are involved in a wide range of social cognitive processes spanning from person perception to attitudes and stereotyping. The discovery of the neural correlates of social comparison would enable researchers to evaluate the role played by comparison in social cognitive processes and as a consequence to further elucidate the neural mechanisms of social cognition.
G.K., T.M., and D.L. are supported by a grant from the bilateral program between the Economic and Social Research Council of the UK (ESRC) and the German Research Foundation (DFG) (RES-062-23-0946: The Neural Substrates of Social Comparison).
Conflicts of interest
There are no conflicts of interest.
1. Huttenlocher J, Higgins ET. Adjectives, comparatives, and syllogisms. Psychol Rev 1971; 78:487–504.
2. Corcoran K, Mussweiler T. Comparative thinking styles in group and person perception
: one mechanism – many effects. Soc Personal Psychol Compass 2009; 3:244–259.
3. Herr PM. Consequences of priming: judgment and behavior. J Pers Soc Psychol 1986; 51:1106–1115.
4. Higgins ET, Lurie L. Context, categorization, and recall: the ‘change-of-standard’ effect. Cogn Psychol 1983; 15:525–547.
5. Mussweiler T, Ruter K, Epstude K. The man who wasn’t there: subliminal social comparison
standards influence self-evaluation. J Exp Soc Psychol 2004; 40:689–696.
6. Corcoran K, Hundhammer T, Mussweiler T. A tool for thought! When comparative thinking reduces stereotyping effects. J Exp Soc Psychol 2009; 45:1008–1011.
7. Sherif M, Hovland CI. Social judgment: assimilation and contrast effects in communication and attitude change 1961.New Haven, CT: Yale University Press.
8. Higgins ET. Self-discrepancy: a theory relating self and affect. Psychol Rev 1987; 94:319–340.
9. Crusius J, Mussweiler T. When people want what others have: the impulsive side of envious desire. Emotion 2012; 12:142–153.
10. Kahneman D, Miller DT. Norm theory: comparing reality to its alternatives. Psychol Rev 1986; 93:136–153.
11. Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science 1974; 185:1124–1131.
12. Todd AR, Hanko K, Galinsky AD, Mussweiler T. When focusing on differences leads to similar perspectives. Psychol Sci 2011; 22:134–141.
13. Festinger L. A theory of social comparison
processes. Hum Relations 1954; 7:117–140.
14. Higgins ET, Strauman T, Klein RSorrentino RM, Higgins ET. Standards and the process of self-evaluation: multiple affects from multiple stages. Handbook of motivation and cognition: foundations of social behavior 1986.New York: Guilford Press;23–63.
15. Mussweiler T. Comparison processes in social judgment: mechanisms and consequences. Psychol Rev 2003; 110:472–489.
16. Mussweiler T, Epstude K. Relatively fast! Efficiency advantages of comparative thinking. J Exp Psychol Gen 2009; 138:1–21.
17. Keil A, Mussweiler T, Epstude K. Alpha-band activity reflects reduction of mental effort in a comparison task: a source space analysis. Brain Res 2006; 1121:117–127.
18. Hagerty MR. Social comparisons of income in one's community: evidence from national surveys of income and happiness. J Pers Soc Psychol 2000; 78:764–771.
19. Smith RH, Diener E, Wedell DH. Intrapersonal and social comparison
determinants of happiness: a range-frequency analysis. J Pers Soc Psychol 1989; 56:317–325.
20. Swencionis JK, Fiske ST. How social neuroscience can inform theories of social comparison
. Neuropsychologia 2014; 56:140–146.
21. Haber SN, Knutson B. The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology 2010; 35:4–26.
22. McClure SM, York MK, Montague PR. The neural substrates of reward processing in humans: the modern role of FMRI. Neuroscientist 2004; 10:260–268.
23. Seymour B, McClure SM. Anchors, scales and the relative coding of value in the brain. Curr Opin Neurobiol 2008; 18:173–178.
24. Fliessbach K, Weber B, Trautner P, Dohmen T, Sunde U, Elger CE, Falk A. Social comparison
affects reward-related brain activity in the human ventral striatum
. Science 2007; 318:1305–1308.
25. Bault N, Joffily M, Rustichini A, Coricelli G. Medial prefrontal cortex
and striatum mediate the influence of social comparison
on the decision process. Proc Natl Acad Sci U S A 2011; 108:16044–16049.
26. Dohmen T, Falk A, Fliessbach K, Sunde U, Weber B. Relative versus absolute income, joy of winning, and gender: brain imaging evidence. J Public Econ 2011; 95:279–285.
27. Dvash J, Gilam G, Ben-Ze’ev A, Hendler T, Shamay-Tsoory SG. The envious brain: the neural basis of social comparison
. Hum Brain Mapp 2010; 31:1741–1750.
28. Fliessbach K, Phillipps CB, Trautner P, Schnabel M, Elger CE, Falk A, Weber B. Neural responses to advantageous and disadvantageous inequity. Front Hum Neurosci 2012; 6:165.
29. Grygolec J, Coricelli G, Rustichini A. Positive interaction of social comparison
and personal responsibility for outcomes. Front Psychol 2012; 3:25.
30. Du X, Zhang M, Wei D, Li W, Zhang Q, Qiu J. The neural circuitry of reward processing in complex social comparison
: evidence from an event-related FMRI study. PLoS One 2013; 8:e82534.
31. Kang P, Lee Y, Choi I, Kim H. Neural evidence for individual and cultural variability in the social comparison
effect. J Neurosci 2013; 33:16200–16208.
32. Zink CF, Tong Y, Chen Q, Bassett DS, Stein JL, Meyer-Lindenberg A. Know your place: neural processing of social hierarchy in humans. Neuron 2008; 58:273–283.
33. Takahashi H, Kato M, Matsuura M, Mobbs D, Suhara T, Okubo Y. When your gain is my pain and your pain is my gain: neural correlates of envy and schadenfreude. Science 2009; 323:937–939.
34. Chester DS, Powell CA, Smith RH, Joseph JE, Kedia G, Combs DJ, DeWall CN. Justice for the average Joe: the role of envy and the mentalizing
network in the deservingness of others’ misfortunes. Soc Neurosci 2013; 8:640–649.
35. Powell CAJ, Smith RH, Schurtz DRSmith RH. Schadenfreude caused by an envied person’s pain. Envy: theory and research 2008.New York: Oxford University Press;148–164.
36. Cohen MX, Elger CE, Ranganath C. Reward expectation modulates feedback-related negativity and EEG spectra. Neuroimage 2007; 35:968–978.
37. Walsh MM, Anderson JR. Learning from experience: event-related potential correlates of reward processing, neural adaptation, and behavioral choice. Neurosci Biobehav Rev 2012; 36:1870–1884.
38. Talmi D, Atkinson R, El-Deredy W. The feedback-related negativity signals salience prediction errors, not reward prediction errors. J Neurosci 2013; 33:8264–8269.
39. Boksem MA, Kostermans E, De Cremer D. Failing where others have succeeded: Medial frontal negativity tracks failure in a social context. Psychophysiology 2011; 48:973–979.
40. Wu Y, Zhang D, Elieson B, Zhou X. Brain potentials in outcome evaluation: when social comparison
takes effect. Int J Psychophysiol 2012; 85:145–152.
41. Qiu J, Yu C, Li H, Jou J, Tu S, Wang T, et al.. The impact of social comparison
on the neural substrates of reward processing: an event-related potential study. Neuroimage 2010; 49:956–962.
42. Bismark AW, Hajcak G, Whitworth NM, Allen JJ. The role of outcome expectations in the generation of the feedback-related negativity. Psychophysiology 2013; 50:125–133.
43. Liao Y, Gramann K, Feng W, Deák GO, Li H. This ought to be good: brain activity accompanying positive and negative expectations and outcomes. Psychophysiology 2011; 48:1412–1419.
44. Endrass T, Klawohn J, Gruetzmann R, Ischebeck M, Kathmann N. Response-related negativities following correct and incorrect responses: evidence from a temporospatial principal component analysis. Psychophysiology 2012; 49:733–743.
45. Kaczkurkin AN. The effect of manipulating task difficulty on error-related negativity in individuals with obsessive-compulsive symptoms. Biol Psychol 2013; 93:122–131.
46. Gilbert DT, Giesler RB, Morris KA. When comparisons arise. J Pers Soc Psychol 1995; 69:227–236.
47. Wood JV, Taylor SE, Lichtman RR. Social comparison
in adjustment to breast cancer. J Pers Soc Psychol 1985; 49:1169–1183.
48. Taylor SE, Wood JV, Lichtman RR. It could be worse: selective evaluation as a response to victimization. Soc Issues 1983; 39:19–40.
49. Alicke MD, LoSchiavo FM, Zerbst J, Zhang S. The person who outperforms me is a genius: maintaining perceived competence in upward social comparison
. J Pers Soc Psychol 1997; 73:781–789.
50. Corning AF, Krumm AJ, Smitham LA. Differential social comparison
processes in women with and without eating disorder symptoms. J Couns Psychol 2006; 53:338–349.
51. Darley JM. Fear and social comparison
as determinants of conformity behavior. J Pers Soc Psychol 1966; 4:73–78.
52. Dunning D, Hayes AF. Evidence for egocentric comparison in social judgment. J Pers Soc Psychol 1996; 71:213–229.
53. Gibbons FX, Benbow CP, Gerrard M. From top dog to bottom half: social comparison
strategies in response to poor performance. J Pers Soc Psychol 1994; 67:638–652.
54. Hobza CL, Walker KE, Yakushko O, Peugh JL. What about men? Social comparison
and the effects of media images on body and self-esteem. Psychol Men Masc 2007; 8:161–172.
55. Johnson SE, Richeson JA, Finkel EJ. Middle class and marginal? Socioeconomic status, stigma, and self-regulation at an elite university. J Pers Soc Psychol 2011; 100:838–852.
56. Locke KD. Status and solidarity in social comparison
: agentic and communal values and vertical and horizontal directions. J Pers Soc Psychol 2003; 84:619–631.
57. Mussweiler T, Damisch L. Going back to Donald: how comparisons shape judgmental priming effects. J Pers Soc Psychol 2008; 95:1295–1315.
58. Rothgerber H, Worchel S. The view from below: intergroup relations from the perspective of the disadvantaged group. J Pers Soc Psychol 1997; 73:1191–1205.
59. Cohen Kadosh R, Walsh V. Numerical representation in the parietal lobes: abstract or not abstract? Behav Brain Sci 2009; 32:313–328.
60. Cohen Kadosh R, Henik A, Rubinsten O, Mohr H, Dori H, van de Ven V, et al.. Are numbers special? The comparison systems of the human brain investigated by fMRI. Neuropsychologia 2005; 43:1238–1248.
61. Nieder A, Dehaene S. Representation of number in the brain. Annu Rev Neurosci 2009; 32:185–208.
62. Dormal V, Andres M, Pesenti M. Contribution of the right intraparietal sulcus to numerosity and length processing: an fMRI-guided TMS study. Cortex 2012; 48:623–629.
63. Dormal V, Pesenti M. Common and specific contributions of the intraparietal sulci to numerosity and length processing. Hum Brain Mapp 2009; 30:2466–2476.
64. Fias W, Lammertyn J, Reynvoet B, Dupont P, Orban GA. Parietal representation of symbolic and nonsymbolic magnitude. J Cogn Neurosci 2003; 15:47–56.
65. Hare TA, Schultz W, Camerer CF, O’Doherty JP, Rangel A. Transformation of stimulus value signals into motor commands during simple choice. Proc Natl Acad Sci U S A 2011; 108:18120–18125.
66. Pinel P, Piazza M, Le Bihan D, Dehaene S. Distributed and overlapping cerebral representations of number, size, and luminance during comparative judgments. Neuron 2004; 41:983–993.
67. Wunderlich K, Rangel A, O’Doherty JP. Neural computations underlying action-based decision making in the human brain. Proc Natl Acad Sci U S A 2009; 106:17199–17204.
68. Kedia G, Lindner M, Mussweiler T, Ihssen N, Linden DE. Brain networks of social comparison
. Neuroreport 2013; 24:259–264.
69. Lindner M, Hundhammer T, Ciaramidaro A, Linden DE, Mussweiler T. The neural substrates of person comparison – an fMRI study. Neuroimage 2008; 40:963–971.
70. Smith ER, Zárate MA. Exemplar and prototype use in social categorization. Soc Cogn 1990; 8:243–262.
71. Smith ER, Zárate MA. Exemplar-based model of social judgment. Psychol Rev 1992; 99:3–21.
72. Kedia G, Mussweiler T, Mullins P, Linden DE. The neural correlates of beauty comparison. Soc Cogn Affect Neurosci 2013; 9:681–688.
73. Chiao JY, Harada T, Oby ER, Li Z, Parrish T, Bridge DJ. Neural representations of social status hierarchy in human inferior parietal cortex
. Neuropsychologia 2009; 47:354–363.
74. Dehaene S. The organization of brain activations in number comparison: event-related potentials and the additive-factors method. J Cogn Neurosci 1996; 8:47–68.
75. Cloutier J, Ambady N, Meagher T, Gabrieli JD. The neural substrates of person perception
: spontaneous use of financial and moral status knowledge. Neuropsychologia 2012; 50:2371–2376.
76. Hoorens V. Self-enhancement and superiority biases in social comparison
. Eur Rev Social Psychol 1993; 4:113–139.
77. Beer JS, Hughes BL. Neural systems of social comparison
and the ‘above-average’ effect. Neuroimage 2010; 49:2671–2679.
78. Hughes BL, Beer JS. Medial orbitofrontal cortex is associated with shifting decision thresholds in self-serving cognition. Neuroimage 2012; 61:889–898.
79. Hughes BL, Beer JS. Orbitofrontal cortex and anterior cingulate cortex are modulated by motivated social cognition
. Cereb Cortex 2012; 22:1372–1381.
80. Hughes BL, Beer JS. Protecting the self: the effect of social-evaluative threat on neural representations of self. J Cogn Neurosci 2013; 25:613–622.
81. Rogers BP, Morgan VL, Newton AT, Gore JC. Assessing functional connectivity in the human brain by fMRI. Magn Reson Imaging 2007; 25:1347–1357.
82. Corcoran K, Cruisus J, Mussweiler TChadee D. Social comparison
: motives, standards, and mechanisms. Theories in social psychology 2011.Oxford, UK: Wiley-Blackwell;119–139.
83. Suls J, Martin R, Wheeler L. Social comparison
: why, with whom, and with what effect? Curr Dir Psychol Sci 2002; 11:159–163.
84. Redersdorff S, Guimond SGuimond S. Comparing oneself over time: the temporal dimension in social comparison
. Social comparison
and social psychology: understanding cognition, intergroup relations and culture 2006.Cambridge: Cambridge University Press;76–96.
85. Wilson AE, Ross M. The frequency of temporal-self and social comparisons in people’s personal appraisals. J Pers Soc Psychol 2000; 78:928–942.
86. Affleck G, Tennen HSuls J, Wills TA. Social comparison
and coping with major medical problems. Social comparison
: contemporary theory and research 1991.Hillsdale, NJ: Erlbaum;369–393.
87. Häfner M. Knowing you, knowing me: familiarity moderates comparison outcomes to idealized media images. Soc Cogn 2009; 27:496–508.
88. Mussweiler T, Bodenhausen GV. I know you are, but what am I? Self-evaluative consequences of judging in-group and out-group members. J Pers Soc Psychol 2002; 82:19–32.
89. Gibbons FX, Buunk BP. Individual differences in social comparison
: development of a scale of social comparison
orientation. J Pers Soc Psychol 1999; 76:129–142.
90. Buunk AP, Gibbons FXGuimond S. Social comparison
orientation: a new perspective on those who do and those who don’t compare with others. Social comparison
and social psychology: Understanding cognition, intergroup relations and culture 2006.Cambridge: Cambridge University Press;15–32.
91. Hamel AE, Zaitsoff SL, Taylor A, Menna R, Le Grange D. Body-related social comparison
and disordered eating among adolescent females with an eating disorder, depressive disorder, and healthy controls. Nutrients 2012; 4:1260–1272.
92. Sheeran P, Abrams D, Orbell S. Unemployment, self-esteem, and depression: a social comparison
theory approach. Basic Appl Soc Psych 1995; 17:65–82.
93. Guimond S, Chatard A, Branscombe NR, Brunot S, Buunk AP, Conway MA, et al.Guimond S. Social comparison
across cultures II: change and stability in self-views – experimental evidence. Social comparison
and social psychology: understanding cognition, intergroup relations and culture 2006.Cambridge: Cambridge University Press;318–344.