NEUROBIOLOGICAL MECHANISMS OF SOCIAL PUNISHMENT … (1).pdf · previous TMS study did not...

NATIONAL RESEARCH UNIVERSITY HIGHER SCHOOL OF ECONOMICS

as a manuscript

Oksana Zinchenko

NEUROBIOLOGICAL MECHANISMS OF SOCIAL PUNISHMENT AS A

COOPERATION PROMOTER

PhD Dissertation

for the purpose of obtaining academic degree

Doctor of Philosophy in Psychology HSE

Academic supervisor:

Vasily Klucharev

Candidate of Biological Sciences

Moscow 2019

Table of contentsIntroduction.......................................................................................................................3

Research goals...................................................................................................................9

Structure of the work.......................................................................................................10

Key results.......................................................................................................................11

Provisions for the defense...............................................................................................14

Conclusion.......................................................................................................................15

Acknowledgements.........................................................................................................16

References.......................................................................................................................17

Attachments.....................................................................................................................21

Attachment A. Article “Brain responses to social norms: Meta-analyses of fMRI studies”.........................................................................................................................21

Attachment B. Article “Neurobiological mechanisms of fairness-related social norm enforcement: a review of interdisciplinary studies”.....................................................21

Attachment C. Article “Commentary: The Emerging Neuroscience of Third-Party Punishment”.................................................................................................................21

Attachment D. Article “The role of the temporoparietal and prefrontal cortices in third-party punishment: a tDCS study”........................................................................21

2

Introduction

Social norms and the mechanisms of their enforcement: behavioral findings

Human society greatly depends on social norms, which work as a mechanism

supporting cooperation. Social norms can be defined as implicit or explicit rules that are

formed to govern interactions within groups and that are considered appropriate within

a society. Some examples of social norms include common courtesy and culturally

appropriate manners (Sherif and Sherif, 1953). Importantly, in human societies

cooperation is mainly based on social norms (Fehr and Fischbacher, 2004).

Different kinds of social norms regulate individual behavior, one of which is the

norm of fairness (Elster, 1989). The norm of fairness in democratic societies is usually

considered a norm of equality (Elster, 1989). A common approach to investigate social

norms is to use interactive economic games, such as the ultimatum game introduced by

Güth and colleagues (1982; see Gabay et al., 2014 for a review), the Prisoner’s dilemma

(Dickinson et al, 2015), and the dictator game (Tammi, 2013). Such games allow

different distributions of financial transfers between players. For instance, in the dictator

game there are two players, one of whom (the dictator) is given the opportunity to

distribute monetary units (MUs) between herself and another player (the recipient)

(Tammi, 2013). Behavioral studies have robustly demonstrated that many people who

play economic games prefer fair distributions to unequal ones (Guth et al., 1982;

Kahneman et al., 1986; Forsythe et al., 1994; Engel, 2010).

However, people do not always conform to social norms and sometimes tend to

violate them to maximize their own interests. Such violations usually meet with

increasing social pressure to conform to the norms. Psychological studies suggest that

the violation of social norms could result in the exclusion of the norm violator from the

group or in other less harsh forms of social disapproval (Schachter, 1951; Sherif, Sherif,

1953). It follows that the behavior conflicting with social norms can have dramatic

3

consequences. Social disapproval and social exclusion enforce norm compliance; in

fact, even the possibility of such sanctions could increase norm compliance (Ruff et al.,

2013).

Such behavior—a tendency to spend one’s own resources to punish norm

violations (e.g., unfair distributions of MUs that violate the norm of fairness)—is called

social punishment (Fehr, Fischbacher, 2004; Ruff et al., 2013). Social punishment can

be demonstrated experimentally based on material costs only, for example, when people

spend some MUs from their own budget to punish a norm violator. It can also be

expressed as social disapproval (Carpenter, Seki 2011; Masclet et al. 2003; Guala,

2012), which is more common in social life (e.g., reprimands, social exclusion, etc.).

Behavioral economics studies suggest that social punishment is usually meted out by

individuals who are directly affected by the norm violations of others (i.e., second

parties). Yet, individuals who are not directly affected by the norm violations of others

(third parties) are also willing to punish norm violators at their own expense (Fehr,

Fischbacher, 2004). It has been shown that norm violation behavior (such as unfair

behavior in the case of the norm of fairness) leads to negative emotions, such as anger

(Batson et al., 2007; Pedersen, 2012), guilt (Wagner et al, 2011), and embarrassment

(Melchers et al., 2015), that could drive individuals to punish their opponent at the

expense of monetary reward or to consider the opponent guilty. Overall, social

punishment as the “propensity of cooperative individuals to spend some of their

resources penalizing norm violators” (Zinchenko, Klucharev, 2017) is the main

mechanism supporting social norms in large social groups.

Neurofunctional model of social norms and norm violations

Because social norms are so important in maintaining social order, further

investigation is crucial to understand the roots of human behavior in different social

contexts. Montague and Lohrehz (2007) propose a neurofunctional model of social

norms based on a review of studies exploring neural correlates of adherence to shared

social norms. They suggest that the brain can flexibly adjust behavior according to

existing social norms, similar to other forms of adaptive behavior. To successfully4

interact with others in any social group, the following steps are necessary: 1) to have a

representation of the norm, 2) to have a mechanism detecting violations of this norm,

and 3) to have the chance to look at the current situation from a third-party perspective

to be able to maintain norm compliance (Montague, Lohrenz, 2007; Xiang et al., 2013).

We adopted this model to perform the first meta-analysis of neuroimaging studies of

social norms (Zinchenko, Arsalidou, 2018).

Third-party punishment as a mechanism of norm enforcement: a comparison with

second-party punishment and the model of neural activation

In addition to investigating social norms in general, it is particularly critical to

study the mechanisms of enforcement, implementation, and compliance, including

social punishment. Third-party punishment is a special form of social punishment that is

unique to human culture (Riedl et al., 2012) and that has not been observed in other

primates, including chimpanzees. While the majority of neuroimaging studies

investigate the neural basis of second-party punishment, there are not many studies

about the neural mechanisms of third-party punishment. Importantly, third-party

punishment is crucial for establishing cooperation in larger social groups. Therefore,

studies of third-party punishment are of practical importance and are relevant in the

modern urbanized world.

Neuroimaging and brain stimulation studies provide some insights on the neural

mechanisms of third-party punishment. It has been shown that second- and third-party

punishment have different neural mechanisms (Strobel et al., 2011) and that only some

regions, such as the ventral striatum, share a common activation for both types of

punishment (Stallen et al., 2018). For instance, the lateral prefrontal cortex (LPFC)—

and its subpart the DLPFC—is casually involved in both types of social punishment but

in slightly different ways. The right LPFC (rLPFC) is involved in both voluntary and

sanction-induced norm compliance in the case of second-party punishment (Ruff et al,

2013). In the case of third-party punishment, rDLPFC activity correlates with the

evaluation of the responsibility for committing norm violations (Buckholtz et al., 2008).

In particular, the emotional evaluation of the personal responsibility that results in third-5

party punishment correlates with activity of the amygdala, the medial prefrontal cortex,

and the posterior part of the cingulate cortex (Buckholtz et al., 2008).

Neuroimaging studies suggest that several distinct brain networks are consistently

recruited during third-party punishment (Krueger, Hoffman, 2016). According to

Krueger and Hoffman’s model (2016), these brain networks include the central-

executive, mentalizing, and salience networks. The mentalizing network is responsible

for the ability to imagine thoughts and possible actions of others and mainly relies on

individual experience, while the activity of the central-executive network is required for

our cognitive control, working memory, task-switching, planning, etc. Hypothetically,

in accordance with the predictions of Krueger and Hoffman’s model, third-party

punishment decisions start with the activation of the salience network (insula,

amygdala, and dorsal anterior cingulate), which allows the detection of norm violations

and consequently generates an aversive response. Next, the default mode network (TPJ,

dorsomedial prefrontal cortex or dMPFC) integrates the perceived harm and inference

of intentions into an assessment of blame. Finally, the central executive network

(DLPFC) converts the blame signal into a specific punishment decision.

Neural mechanisms of third-party punishment: neuroimaging and brain

stimulation studies

Most previous studies focus on the brain correlates of third-party punishment and

practically ignore the interactions between the large-scale brain networks. A recent

brain stimulation study shows that transcranial magnetic stimulation (rTMS) of the

rDLPFC increased third-party punishment, while psychometric methods have provided

evidence of a correlation between an individual empathy index and the intensity of

third-party punishment (Brune et al., 2012). These results may suggest that the DLPFC

integrates all signals from the previous steps of the decision-making process, including

the emotional emphatic responses.

It follows that suppression of the DLPFC should lead to increased third-party

punishment only if the activity of the DLPFC underlies the final evaluation of the costs

6

of the punishment decision. If so, suppression of the DLPFC should decrease the

perceived costs of social punishment and therefore increase third-party punishment. The

previous TMS study did not disentangle material and moral costs (Brune at al., 2012);

third parties punished the norm violator and helped the victim at the same time.

Therefore, the role of the DLPFC in third-party punishment remains largely unclear.

Considering other main brain regions from the model (Krueger, Hoffman, 2016),

the previous brain stimulation studies provided a more coherent interpretation of the

role of the rTPJ in third-party punishment. It has been shown that rTMS of the rTPJ

decreases third-party punishment of outgroup members (Baumgartner et al., 2014). This

supports Krueger and Hoffman’s model (2016) of third-party punishment and indicates

the vital role of the rTPJ in the processing of emotional information during social

punishment. This interpretation is in line with extensive meta-analyses that

demonstrated the involvement of the rTPJ in mentalizing and empathy (Van Overwalle,

2009; Garrigan, Adlam, Langdon, 2016).

A seminal functional magnetic resonance imaging (fMRI) study of third-party

punishment has demonstrated a functional interaction between the rDLPFC and the

rTPJ (Buckholtz et al., 2008). This study suggests that the activation of the rTPJ before

a punishment decision is followed by simultaneous deactivation of the rDLPFC and

results in the follow-up activation of the rDLFPC when the final decision is made.

Taking into account these findings (Buckholtz et al., 2008), we speculate that the

chronometry of the third-party punishment decision is as follows. The information

about the harm (a degree of norm violation) and the intentions (intentional versus

unintentional norm violations) are processed in the salience network (anterior cingulate,

anterior insula) and the mentalizing network (rTPJ). Subsequently, the resulting

information is transferred to the DLPFC to calculate the final decision, considering the

context of the situation and the self-maximization (if the punishment decision is costly).

Recent neuroimaging studies focus not only on the functional role of the exact

brain region but also on the interaction between different brain regions (e.g., Treadway

et al., 2014; Bellucci et al., 2017). Similarly, Feng and colleagues (2018) analyze7

resting-state fMRI data using graph theory and support Krueger and Hoffman’s model

of the key brain nodes involved in third-party punishment. Another fMRI study

investigates task-related brain activity and supports the main role of the mentalizing

(TPJ and dMPFC) and central-executive (LPFC) systems in third-party punishment

(Bellucci et al., 2017). Importantly, this study demonstrates that the dMPFC receives

the incoming signals only from the TPJ, while the activity of the dMPFC and its

functional co-activation with the dLPFC correlate with the degree of third-party

punishment (Bellucci et al., 2017). According to these findings, the TPJ is considered to

be an integrative node, receiving the information from other sub-regions.

The primary role of the mentalizing and central-executive networks in third-party

punishment is supported by traumatic brain injury studies. Glass and colleagues (2016)

show that damage to these cortical regions decreased the intensity of third-party

punishment and altruistic compassion. However, to date the functional connectivity

before or during social punishment has not been investigated using electrophysiological

methods with high time resolution. To our knowledge, the electroencephalogram studies

reported only the inter-brain connectivity between the receiver’s and the punisher’s

brain activity during third-party punishment using a hyperscanning approach (Astolfi et

al., 2015; Ciaramidaro et al., 2018).

In summary, we reviewed the key neuroimaging studies of social norms and

social norm enforcement, focusing particularly on social punishment and third-party

punishment. We identified the following gaps in the research on social norms and social

punishment, which we addressed in a series of studies: 1) no meta-analyses have been

performed to identify the key brain regions concordantly activated in relation to

representations of social norms and their violations; 2) previous studies robustly

demonstrated the role of the mentalizing and central-executive networks in third-party

punishment, but brain stimulation has not been used to demonstrate a causal relationship

between the aforementioned networks and third-party punishment or to investigate

interaction between the mentalizing and central-executive networks.

8

Research goals

1) To perform a meta-analysis of neuroimaging studies of fMRI modality to identify

the key regions related to information processing in social norms (the representation of

social norms and norm violations).

2) To perform a brain stimulation study to investigate the functional interactions of the

rDLPFC and the rTPJ during third-party punishment decisions.

3) To identify the functional roles of the rDLPFC and the rTPJ in third-party

punishment decisions.

9

Structure of the work

The PhD thesis consists of three main parts which are presented in the following

papers:

Part I (Meta-analysis). Zinchenko O. O., Arsalidou M. Brain responses to social

norms: Meta-analyses of fMRI studies // Human Brain Mapping. 2018. Vol. 39. No. 2.

P. 955-970

Part II (Neurocognitive model of third-party punishment). Zinchenko O. O.,

Belyanin A., Klucharev V. Neurobiological mechanisms of fairness-related social norm

enforcement: a review of interdisciplinary studies. Zh. Vyssh. Nerv. Deiat. 2018. 67(6),

16-27.

Part III (Brain stimulation study). Zinchenko O. O., Klucharev V. Commentary:

The Emerging Neuroscience of Third-Party Punishment // Frontiers in Human

Neuroscience. 2017. No. 11. P. 1-3; Zinchenko O. O., Belyanin, A., Klucharev V.

(2019). The role of the temporoparietal and prefrontal cortices in third-party

punishment: a tDCS study // Psychology. Journal of the Higher School of Economics.

10

Key results

Part I (Meta-analysis). We identified concordant activations in the functional

magnetic resonance imaging (fMRI) studies for the social norm representations and

norm violation using meta-analytic approach (Zinchenko, Arsalidou, 2018). For the

general map of the brain responses to social norms we detected five clusters: the largest

cluster was found in the right insula (Brodmann Area, BA 13), followed by the left

medial frontal gyrus (BA 32) that extended to the cingulate gyrus (BA 32), right

superior and middle frontal gyri (BA 9 and BA 10). Other regions included the left

insula and claustrum. Regions of significant concordance specifically for ‘social norm

representations’ included the left anterior cingulate and right medial frontal gyrus (BA

10). The meta-analysis of ’norm violation’ category revealed five suprathreshold

clusters were detected for norm violation, with the one with the highest likelihood of

being detected in the right insula (BA 13), followed by other regions: right cingulate

gyrus (BA 32), left insula (BA 13) and claustrum, and right middle and superior frontal

gyri (BA 9 and 10). While compared to norm violation, social norm representation

showed greater concordance in the anterior cingulate gyri (BA 32) and right medial

frontal gyrus (BA 10), whereas compared to social norm representation, norm violation

shows greater concordance in the right insula and claustrum and more dorsal parts of

the cingulate gyrus (BA 24, 32). To sum up, the findings suggest that rDLPFC plays

key role in social norm representations and the detection of norm violation.

Part II (Neurocognitive model of third-party punishment). In accordance with our

research goals, we performed a systematic review of behavioral, neuroimaging, and

brain stimulation studies to identify the main open research questions in the third-party

punishment research. The results that were briefly described in the Introduction section

of this thesis were published in Zinchenko, Belyanin, and Klucharev (2018). Based on

the previous fMRI study (Buckholtz et al., 2008), we speculated that an enhancement of

TPJ activity with the simultaneous suppression of DLPFC activity should lead to

increased third-party punishment due to the possible enhancement of the antagonistic

11

TPJ–DLPFC interaction. Therefore, we suggested that a simultaneous application of

tDCS to the TPJ and DLPFC should enhance such antagonistic interaction between

these two regions and increase third-party punishment. Such a behavioral effect of tDCS

could reflect changes in the functional connectivity between the TPJ and the DLPFC.

Therefore, a combined non-invasive brain stimulation–neuroimaging study is needed to

uncover the neural dynamics underlying third-party punishment.

Part III (Brain stimulation study). Based on the results of our review paper, we

formulated the new research hypotheses, which have been published in Zinchenko and

Klucharev (2017). Therefore, we conducted a tDCS experiment in which we tested the

classic stimulation protocols with anodal tDCS stimulation of the rDLPFC and the rTPJ

separately and the novel simultaneous stimulation protocol of the enhancement of TPJ

activity with the simultaneous suppression of DLPFC activity. However, we observed

only a trend relating to the effect of the joint stimulation tDCS protocol (p=0.055).

When the rTPJ was activated and the rDLPFC was simultaneously deactivated, we

observed a trend of increased third-party punishment. We suggest that tDCS is not the

ideal method to study interactions of the rDLPFC and rTPJ. In the future, online

transcranial alternating current stimulation could be used to study the synchronization

and desynchronization of these brain regions. Nevertheless, we observed the effect of

the anodal stimulation of the rTPJ, which led to decreased punishment for moderately

unfair splitting of the resources (p=0.006). A recent study involving anodal tDCS of the

rTPJ shows that subjects were assigned less blame for accidental harm during a moral

judgment task (Sellaro et al., 2015), while a meta-analysis suggests that the rTPJ

showed significant activation when one makes one’s own moral decisions (Garrigan,

Adlam, Langdon, 2016). Overall, rTPJ activity can reflect an analysis of the

consequences of the third-party’s own decision and of how harmful it would be for

others. Therefore, anodal stimulation of the rTPJ area could exaggerate the latter

process and consequently lead to diminished punishment.

One of the important findings of our tDCS study is that anodal tDCS had an

effect on moderately unfair splitting of the resources (30:10) only: when third-party

12

punishment of unfair splits created a Pareto optimal distribution of MUs (10:10:10) and

it was impossible to improve the income of one player without worsening the incomes

of the other players, while the punishment in other conditions led to advantageous and

disadvantageous inequity. Pareto optimality is a state of allocation of resources where it

is impossible to improve the income of one player without worsening the incomes of the

other players. Therefore, in our study social punishment for other splits (0:40, 15:25,

20:20, 25:15, 35:5, and 40:0) would lead to advantageous and disadvantageous inequity.

Following this, we suggest that anodal tDCS led to decreased moral costs, which

resulted in decreased punishment.

13

Provisions for the defense

1) According to our meta-analysis of fMRI studies, social norm representation is

robustly associated with activity of the anterior cingulate and right DLPFC, while norm

violation is associated with the activation of the right insula and claustrum.

2) The Krueger and Hoffman model (2016), along with the results of our extensive

systematic review and our meta-analysis, suggests the key role of the DLPFC and the

TPJ in monitoring social norms and their enforcement. However, according to our tDCS

study, anodal tDCS of the rDLPFC does not lead to changes in third-party punishment.

3) According to the tDCS study, anodal tDCS of the rTPJ decreases third-party

punishment for moderately unfair splitting of the resources. We suggest that during the

dictator game rTPJ activity underlies the initiation of the decision to punish, while

activation of the rDLPFC becomes important in the latest stages of decision making.

14

Conclusion

We conducted the first meta-analysis of neuroimaging studies on social norms

and their violations. The results suggest that social norm representation is linked to the

activation of the anterior cingulate gyri and the rDLPFC and that norm violations are

coded by the activation of the right insula and claustrum. Based on this, we proposed a

neurocognitive model of social norms for healthy adults suggesting that the

temporoparietal-medial-prefrontal circuit controls the emotional responses to norm

violations and regulates the subsequent punishment of norm violators. The results of the

brain stimulation study suggest that anodal tDCS of the rTPJ decreases the third-party

punishment for moderately unfair splitting of the resources, while joint stimulation of

the rTPJ (by anodal tDCS) and rDLPFC (by cathodal tDCS) produces only a marginal

effect. This study demonstrates that anodal tDCS of the rTPJ decreases third-party

punishment for moderately unfair behavior when the participants have an opportunity to

restore equality in their social groups. Overall, the study findings support the critical

role of the temporoparietal-medial-prefrontal circuit in third-party punishment. These

findings can be used in future studies on social norms and the mechanisms of their

enforcement in healthy subjects.

15

Acknowledgements

I would like to express my sincere gratitude to my advisor, Professor Vasily

Klucharev, for giving me opportunity to conduct and complete the PhD study at the

Centre for Cognition and Decision Making.

My sincere thanks goes to Dr. Marie Arsalidou, who is my coauthor on “Brain

responses to social norms: Meta-analyses of fMRI studies”, for the valuable

contribution.

I would like to thank Dr. Alexis Belyanin, Dr. Matteo Feurra and Dr. Anna

Shestakova for their valuable comments and help while designing and conducting these

studies.

Many thanks to Dr. Beatriz Martin-Luengo and Dr. Ksenia Panidi for reviewing

this thesis.

I acknowledge HSE University Basic Research Program and Russian Academic

Excellence Project '5-100' for the financial support through the research unit.

16

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20

Attachments

Attachment A. Article “Brain responses to social norms: Meta-analyses of fMRI

studies”.

Attachment B. Article “Neurobiological mechanisms of fairness-related social norm

enforcement: a review of interdisciplinary studies”.

Attachment C. Article “Commentary: The Emerging Neuroscience of Third-Party

Punishment”.

Attachment D. Article “The role of the temporoparietal and prefrontal cortices in third-

party punishment: a tDCS study”.

21

Attachment A. Article “Brain responses to social norms: Meta-analyses of fMRI

studies”.

Social norms have a critical role in everyday decision-making, as frequent

interaction with others regulates our behavior. Neuroimaging studies show that

social-based and fairness-related decision-making activates an inconsistent set of

areas, which sometimes includes the anterior insula, anterior cingulate cortex, and

others lateral prefrontal cortices. Social-based decision-making is complex and

variability in findings may be driven by socio-cognitive activities related to social

norms. To distinguish among social-cognitive activities related to social norms, we

identified 36 eligible articles in the functional magnetic resonance imaging (fMRI)

literature, which we separate into two categories (a) social norm representation and

(b) norm violations. The majority of original articles (>60%) used tasks associated

with fairness norms and decision-making, such as ultimatum game, dictator game,

or prisoner's dilemma; the rest used tasks associated to violation of moral norms,

such as scenarios and sentences of moral depravity ratings. Using quantitative

meta-analyses, we report common and distinct brain areas that show concordance

as a function of category. Specifically, concordance in ventromedial prefrontal

regions is distinct to social norm representation processing, whereas concordance

in right insula, dorsolateral prefrontal, and dorsal cingulate cortices is distinct to

norm violation processing. We propose a neurocognitive model of social norms for

healthy adults, which could help guide future research in social norm compliance

and mechanisms of its enforcement.

R E S E A R CH AR T I C L E

Brain responses to social norms: Meta-analyses of fMRI studies

Oksana Zinchenko1 | Marie Arsalidou2,3

1Centre for Cognition and Decision Making,

National Research University Higher School

of Economics, Moscow, Russian Federation

2Department of Psychology, National

Research University Higher School of

Economics, Moscow, Russian Federation

3Department of Psychology, Faculty of

Health, York University, Toronto, Canada

Correspondence

Oksana Zinchenko, Centre for Cognition

and Decision Making, National Research

University Higher School of Economics,

101000, Moscow, 3 Krivokolenny Pereulok,

Russian Federation.

Email: [email protected]

Funding information

The study has been funded by the Russian

Academic Excellence Project ’5-100’ to OZ.

MA was supported by the Russian Science

Foundation #17-18-01047.

AbstractSocial norms have a critical role in everyday decision-making, as frequent interaction with others

regulates our behavior. Neuroimaging studies show that social-based and fairness-related decision-

making activates an inconsistent set of areas, which sometimes includes the anterior insula, ante-

rior cingulate cortex, and others lateral prefrontal cortices. Social-based decision-making is

complex and variability in findings may be driven by socio-cognitive activities related to social

norms. To distinguish among social-cognitive activities related to social norms, we identified 36 eli-

gible articles in the functional magnetic resonance imaging (fMRI) literature, which we separate

into two categories (a) social norm representation and (b) norm violations. The majority of original

articles (>60%) used tasks associated with fairness norms and decision-making, such as ultimatum

game, dictator game, or prisoner’s dilemma; the rest used tasks associated to violation of moral

norms, such as scenarios and sentences of moral depravity ratings. Using quantitative meta-

analyses, we report common and distinct brain areas that show concordance as a function of cate-

gory. Specifically, concordance in ventromedial prefrontal regions is distinct to social norm

representation processing, whereas concordance in right insula, dorsolateral prefrontal, and dorsal

cingulate cortices is distinct to norm violation processing. We propose a neurocognitive model of

social norms for healthy adults, which could help guide future research in social norm compliance

and mechanisms of its enforcement.

K E YWORD S

brain mapping, functional magnetic resonance imaging, social norms, prefrontal cortex, humans,

cognition, norm violation

1 | INTRODUCTION

Most of us benefit by following social norms to some degree. Social

norms are spoken or unspoken rules of behavior that are formed within

group situations and are considered appropriate within a society. For

instance, common courtesy and culturally appropriate manners for

cooperative actions and bilateral exchange can be referred to as social

norms (Sherif & Sherif, 1953). Because we live, act, and interact among

others in a society we often have to equipoise our personal wants and

social norms (Cialdini, Reno, & Kallgren, 1990; Bicchieri 2016). Devia-

tion from social norms is often met with increasing pressure to con-

form. From early studies we know that if social expectations remain

unmet, deviation from social norms often results with exclusion of the

norm violator from the group or higher likelihood of reduced payoffs to

the norm violator (Schachter, 1951; Sherif & Sherif, 1953). Thus, going

against social norms has critical consequences. In other words, threat-

ening norm violators with some form of social punishment enforces

norm compliance. Punishment is usually given by individuals who are

directly affected by norm violations of others (i.e., second parties), yet

individuals who are not directly affected by norm violations of others

(i.e., third parties) are also willing to give punishment (Fehr & Fisch-

bacher, 2004).

A common approach to investigate norm violation and norm

enforcement is by using interactive economic games (Camerer, 2003;

Fehr & Camerer, 2007; Sanfey, 2007), such as the Ultimatum Game

introduced by (G€uth et al. 1982; see Gabay, Radua, Kempton, & Mehta,

2014 for a meta-analysis), the Prisoner’s Dilemma (Dickinson, Masclet,

& Villeval, 2015), and the Dictator Game (Tammi, 2013). Behavioral

findings suggest that unfair treatment leads to negative emotions, such

as anger (Batson et al., 2007; Pedersen, 2012), guilt (Wagner, N’diaye,

Ethofer, & Vuilleumier, 2011), and embarrassment (Melchers et al.,

2015) that drive individuals to punish their opponent at the expense of

monetary reward or consider the opponent guilty. Performance on

tasks with monetary outcomes highly depends on the participant’s

Hum Brain Mapp. 2018;39:955–970. wileyonlinelibrary.com/journal/hbm VC 2017Wiley Periodicals, Inc. | 955

Received: 4 July 2017 | Revised: 24 October 2017 | Accepted: 10 November 2017

DOI: 10.1002/hbm.23895

http://orcid.org/0000-0002-7976-3224

http://orcid.org/0000-0001-9879-3894

understanding of relative and absolute fairness/unfairness of the situa-

tion at hand. In case of unfair situations, participants presented with

economic paradigms, such as the Ultimatum Game are asked to accept

or reject financial offers depending on subjective equality of the

offered distribution. Some researchers identify this rejection rate to

reflect social punishment (Sanfey, Rilling, Aronson, Nystrom, & Cohen,

2003; Tabibnia, Satpute, & Lieberman, 2008). For instance, rejection

rate in an Ultimatum Game gradually increases as the proposer’s offer

becomes lower, such that a lower proposal is perceived as more unfair

(Corradi-Dell’Acqua et al., 2013; Rilling & Sanfey, 2011). In other

words, decision-making in this situation is influenced by social norms

and differs according to the responder’s understanding of norms and

their violation, consistent with the claim that social norms are self-

enforcing (Young, 2015). Overall, behavioral studies show that conse-

quences of social norms are related to both social violations and social

punishment; however, it is difficult to parse out the underlying mecha-

nisms of such complex processes with behavioral paradigms alone.

Many functional magnetic resonance imaging (fMRI) and lesion

studies examined the brain correlates of social norms (e.g., Dimitrov,

Phipps, Zahn, & Grafman, 1999; Koenigs et al., 2007; Buckholtz & Mar-

ois, 2012; Sanfey & Chang, 2008; Harl�e, Chang, Wout, & Sanfey, 2012;

Wright, Symmonds, Fleming, & Dolan, 2011; Hu et al., 2016). An

advantage of functional neuroimaging is that it allows for tracking of

continuous processes as healthy participants are working on tasks. A

recent fMRI meta-analysis on the Ultimatum Game distinguishes two

brain systems responsible for norm enforcement behavior; an intuitive-

emotional system, also called System 1, involving the anterior insula

and ventromedial prefrontal cortex and a cognitive-rational system, or

System 2, involving ventrolateral, dorsomedial, left dorsolateral pre-

frontal cortices, and rostral anterior cingulate cortices (Feng, Luo, &

Krueger, 2015). Regions involved in System 1 represent a drive to pun-

ish norm violators, whereas System 2 is responsible for cognitive con-

trol and suppression of economic self-interest (i.e., to save money;

Feng et al., 2015). It has been suggested that both these systems would

underline quick detection of norm violations, evaluation of benefits,

and costs of punishment to decide its necessity, supporting the dual

process theory (Kahneman, 2003; Kahneman, 2011). The meta-analysis

by Feng et al. (2015) provides knowledge on the brain correlates

related to the Ultimatum Game (Feng et al., 2015); however, does not

distinguish between different aspects of social norms and focuses only

on a single task. Critically, some of Feng et al. (2015) methodological

choices may be problematic or outdated. First, the analyses include

data from children and adults (i.e., G€uro�glu et al., 2011; White et al.,

2013) when behavioral evidence show differences in performance

between children, adolescents and adults (Hamlin, Wynn, Bloom, &

Mahajan, 2011; Steinbeis, Bernhardt, & Singer, 2012). Second, the anal-

yses used a low number of studies (i.e.,<17) with a threshold for multi-

ple comparison control (i.e., false discovery rate, FDR) that is currently

not recommended practice (Eickhoff, Laird, Fox, Lancaster, & Fox,

2017). Moreover, according to GingerALE developers, older versions of

the software (i.e., older than 2.3.6) had a computational error, which

did not appropriately control thresholding procedures (Eickhoff et al.,

2017). Thus, an understanding of how healthy adults process social

norms is still lacking. In this article, we focus on social norms and possi-

ble distinctions among (a) social norm representation and (b) norm

violations.

1.1 | Theoretical approach

To frame our hypotheses, we adopted a recent neurofunctional model

of social norms (Montague & Lohrenz, 2007). Montague’s model is a

product of a classic review of research studies that explored brain

activity related to adherence to shared social norms (Montague & Loh-

renz, 2007; Xiang, Lohrenz, & Montague, 2013). They proposed that

the brain could flexibly adjust behavior according to social norms in

order to develop a program of further behavior. To interact with others

in any social group, the following circumstances are required: (a) a rep-

resentation of a well-known norm as a behavioral rule about something

that is expected to be true (e.g., Montague & Lohrenz, 2007), (b) the

possibility to detect any violations of this norm, and (c) a chance to

look at an ongoing situation from a third-party perspective so to act

and make congruent decisions to maintain norm compliance (e.g., Mon-

tague & Lohrenz, 2007; Xiang et al., 2013). Because norm compliance

is not always voluntary and mostly requires sanction inducement, social

punishment is used for social norm enforcement. In line with this model

that predicts differential brain regions for mental processes associated

with social norms, for our meta-analyses we differentiate among social

norms into two subcategories: (a) social norm representation and (b)

norm violation, and expected different brain regions to underlie these

processes.

1.2 | Social norm representation

We define social norm representation as commonly expected appropri-

ate behavior in a certain situation (i.e., shared norms; Cialdini & Gold-

stein, 2004). Our category for social norm representation includes both

moral and social norms as a kind of normative attitudes as both moral

and social norms are accepted rules or normative principles. Here we

categorize experiments (i.e. contrasts) as belonging to social norm rep-

resentation if the action in the task possesses the social preferences

(“good” versus “bad,” or neutral etc.) or if a comparison between social

and non-social domain has been made (“moral” versus “semantic,” etc.).

Unlike social norm representation studies, which reflect voluntary

actions individuals do because they think they are appropriate (Bic-

chieri, 2016), social conformity studies have participants confronted

with direct peer pressure (Wei, Zhao, & Zheng, 2013; Zaki, Schirmer, &

Mitchell, 2011). Studies of social conformity were not included as a

separate category because of insufficient studies (i.e.,<17 experi-

ments; Eickhoff et al., 2017). We are interested in global normative

judgments that regard others, such as fairness-related norms modeled

in the Ultimatum Game (Brennan, Gonz�alez, G€uth, & Levati, 2008),

norms of equality (Elster, 1989), and others used to maintain social

order. Recent studies report that the ventromedial prefrontal cortex,

critical for social cognition, strongly correlates with distinguishing

“good” and “bad” in the moral domain (Bechara, Damasio, & Damasio,

2000; Dimitrov et al., 1999; Heekeren et al., 2005; Koenigs et al.,

956 | ZINCHENKO AND ARSALIDOU

2007). Such moral evaluations reflect internal representations of social

norms (Prehn et al., 2008). Although most social norm studies report

activity in the prefrontal cortex, the location is inconsistent: orbitofron-

tal (e.g., Koenigs and Tranel, 2007) and dorsolateral (e.g., Lieberman,

2007 for review; Prehn et al., 2008; Yoder and Decety, 2014) cortices.

Based on past literature, we expect that concordant brain locations

responding to “social norm representation” will be revealed in dorsolat-

eral prefrontal cortex.

1.3 | Norm violation

We define norm violation as behavioral deviations from shared social

norms (i.e., inappropriate behavior). Norm violations of another person

could affect the observer’s self-concept by threatening his or her social

identity (Melchers et al., 2015). Many functional neuroimaging studies

focus on brain responses to norm violation situations and how norm

violations influence decision-making. Specifically, they examine per-

ceived unfairness/fairness (Buckholtz & Marois, 2012; Sanfey & Chang,

2008), negative moral emotions—guilt (Wagner et al., 2011) or embar-

rassment as a consequence of norm violation (Takahashi et al., 2004,

2008). Some fMRI studies examining norm violations show key areas

being active in the insula (Denke, Rotte, Heinze, & Schaefer, 2014;

G€uro�glu, Bos, Dijk, Rombouts, & Crone, 2011; Sanfey et al., 2003) and

others in the orbitofrontal and dorsomedial cortex (Wagner et al.,

2011), yet others highlight activity in the cingulate cortex (Denke et al.,

2014; G€uro�glu et al., 2011). Considering this broad representation of

activation following norm violation processing, a meta-analysis is

needed to quantitatively verify which areas are concordantly active.

Based on previous findings, we expect that tasks in the “norm viola-

tion” category will show concordant brain locations in insular and cin-

gulate cortices.

2 | MATERIALS AND METHODS

2.1 | Literature search and article selection

The literature was searched using the standard engines of Web of Sci-

ence (http://apps.webofknowledge.com/), Scopus (https://www.sco-

pus.com/home.uri), and PubMed (https://www.ncbi.nlm.nih.gov/

pubmed/). We looked for keywords (fMRI and norm violation), and

(fMRI and social norms) on April 3, 2017. This search yielded a total of

181 articles. After removing duplicates, articles were subjected to a

series of selection criteria (Figure 1). First, articles needed to report

experiments with human participants that used fMRI or PET to study

tasks related to social norms (social norm representation, norm viola-

tion) and be written in English. These resulted in 116 articles that

underwent full-text review. Articles that reported no fMRI data, only

region of interest (ROI) results, only patient data, data on children,

reviews, and articles with irrelevant tasks were excluded. Articles,

which survived these criteria, underwent a full text review and were

screened for healthy adults, reporting stereotaxic coordinates (Talairach

or Montreal Neurological Institute, MNI) of whole-brain, within-group

results using random effects analysis. To keep methodology constant,

we included only experiments that used subtraction contrasts (i.e.,

A>B) and excluded experiments that addressed relations with specific

task ratings (i.e., “negative correlation with unfairness level”). We also

searched the references of all articles that passed the selection criteria

and identified 14 additional articles that were eligible. Thus, data from

a total of 36 articles were eligible for these meta-analyses.

To control within-group effects, a single experiment (i.e., contrast)

from each article reporting coordinates relating to overall social norms

was selected (Table 1). Experiments were further grouped into the two

categories based on careful evaluation of the task description and

responses required by the participant, as explained below. Social norm

representations were defined as behavioral rules implicitly given, rather

than explicitly given (i.e., laws and policies), related to maintenance of

social order, such as criteria of fairness, moral beauty, and willingness

to help. Eighteen articles reported experiments related to social norm

representation by examining social integration and “good” actions such

as maintenance of social integration and understanding morality (Table

1). The majority of articles used tasks that investigated social norms

through the evaluation of social welfare and exchange of financial

resources: these included the Public Goods Game (Cooper, Kreps,

Wiebe, Pirkl, & Knutson, 2010), Ultimatum Game (Civai, Crescentini,

Rustichini, & Rumiati, 2012; Corradi-Dell’Acqua et al., 2013; Harlé &

Sanfey, 2012; Servaas et al., 2015; Tabibnia et al., 2008; Tomasino

et al., 2013; Wu, Zang, Yuan, & Tian, 2015; Zhou, Wang, Rao, Yang, &

Li, 2014), Trust Game (Delgado, Frank, & Phelps, 2005), and a Dictator

Game (Feng et al., 2016; Strobel et al., 2011; Hu, Strang, & Weber,

2015). Players interacting in the Ultimatum and Dictator Games have

different roles. In the Dictator Game, a dictator is given the opportunity

to distribute points between himself and a recipient, whereas in the

Ultimatum Game a recipient could accept or reject a dictator’s offer. In

the Dictator Game the dictator’s offer remains unchanged. A dictator’s

50–50 offer is considered as normatively fair, whereas any deviation

(e.g., 60–40) is considered unfair. It has been shown that people not

only prefer fair distributions (G€uth, Schmittberger, & Schwarze, 1982)

but also tend to spend their own resources to prevent norm violation

at their own cost (Fehr & Fischbacher, 2004). Four articles used linguis-

tic material ratings (moral versus semantic; Heekeren et al., 2005; Moll,

Oliveira-Souza, Bramati, & Grafman, 2002; Prehn et al., 2008). One

article used a social interaction task (Yoder and Decety, 2014). For suf-

ficient power to detect sized effects in ALE meta-analyses, a minimum

of 17 studies are needed (Eickhoff et al., 2017), thus, due to lack of

experiments we did not examine moral (n54) and social (n514) norm

representations separately.

Norm violation was defined as behavioral actions of not following

behavioral rules related to the maintenance of social order. For this cat-

egory, we selected contrasts related to activity elicited by negative

emotions associated to situations with violation of norms, such as per-

ception of embarrassing stories related to themselves or others, and

unfair behavior related to the participant’s self or the whole social

group. Twenty nine articles used such tasks. These paradigms involved

unfair behaviors (Baumgartner, Knoch, Hotz, Eisenegger, & Fehr, 2011;

Cooper et al., 2010; Civai et al., 2012; Delgado et al., 2005; Feng et al.,

2016; Gospic et al., 2011; Guo et al., 2013; Guo et al., 2014; Halko,

ZINCHENKO AND ARSALIDOU | 957

http://apps.webofknowledge.com

https://www.scopus.com/home.uri

https://www.scopus.com/home.uri

https://www.ncbi.nlm.nih.gov/pubmed

https://www.ncbi.nlm.nih.gov/pubmed

Hlushchuk, Hari, & Sch€urmann, 2009; Harl�e et al., 2012; Hu et al.,

2016; Kirk, Downar, & Montague, 2011; Sanfey et al., 2003; Servaas

et al., 2015; Wu et al., 2015; Zheng et al., 2015) with more focus at dis-

advantageous inequity, which directly violate social norms (Fliessbach

et al., 2012) and unfair behavior in terms of cooperation, like Prisoner’s

Dilemma (Rilling et al., 2008). In the case of the Prisoner’s Dilemma

task, two players decide to cooperate or betray each other, decisions

that directly influence the player’s budgets. Specifically, the fairest deci-

sion is to cooperate as both players increase their budgets slightly. If

one player betrays the other the betrayer has higher gains than the

other player. The worse circumstance is when both players betray each

other, which results in loss of resources for both players. Others pre-

sented participants with personal embarrassing-norm violation stories

(Berthoz et al., 2002), sentences about moral depravity (Takahashi

FIGURE 1 PRISMA flowchart for identification and eligibility of articles (template by Moher et al., 2009) [Color figure can be viewed atwileyonlinelibrary.com]


http://wileyonlinelibrary.com

TABLE1

Descriptive

inform

ationofstud

iesan

dco

ntrastsused

inthemeta-an

alyses

Firstau

thor,ye

arN

FEdu

cation

Han

dedn

ess

Age

Task

Contrast

Foci

Categ

ory

Bau

mgartne

r,2011

32

0n/r

Right

21.66

2.2

Ultim

atum

game

Unfair>

fair

17

NV

32

0n/r

Right

21.66

2.2

Ultim

atum

game

Fair>

unfair

4NR

Berthoz,

2002

12

0n/r

Right

19–3

7Persona

l-im

persona

l,em

barrassing

-violation

stories

Intentional

viola-

tion>norm

alstories

18

NV

Civai,2012

19

12

n/r

Right

n/r

Seco

nd-party

andthird-pa

rty

splitting

task

Uneq

ual

>eq

ual

5NV

19

12

n/r

Right

n/r

Seco

nd-party

andthird-pa

rty

splitting

task

Equal

>uneq

ual

3NR

Coope

r,2010

38

18

Unive

rsity

Right

18–4

6Pub

licgo

ods

game

Low

>high(donationco

ndi-

tion)

2NV

38

18

university

Right

18–4

6Pub

licgo

ods

game

High>low

(donationco

ndi-

tion)

1NR

Corrad

i-Dell’A

cqua

,2013

23

9n/r

n/r

18–3

5Ultim

atum

game

Ultim

atum

game>free

win

17

NR

Delgado

,2005

12

n/r

n/r

Right

26.646

4.11

Trust

game

Share>

keep

8NR

12

n/r

n/r

Right

26.646

4.11

Trust

game

Kee

p>

share

2NV

Den

ke,2014

17

8n/r

n/r

256

3.54

Observationofno

rm-

violationbe

havior’s

sce-

nariosan

dno

rm-

confirmingbe

havior

Immoral>

moral

3NV

Fen

g,2016

22

11

n/r

n/r

22.9

61.6

Third-party

punishmen

tpa

radigm

inmone

tary

task

Unfair>

Fair

19

NV

22

11

n/r

n/r

22.9

61.6

Third-party

punishmen

tpa

radigm

inmone

tary

task

Fair>

unfair

16

NR

Fliessba

ch,2012

64

32

n/r

n/r

22–3

3Adv

antage

ous/disad

vanta-

geous

payo

ffs

DI>

E1

NV

Gospic,2011

17

12

n/r

Right

23.7

64.2

Ultim

atum

game

(u>f)placebo

4NV

Guo

,2013

21

n/r

n/r

n/r

22.446

3.49

Ultim

atum

game

Unfair>

fair

13

NV

Guo

,2014

18

5n/r

Right

21.0

62.10

Ultim

atum

game

Unfair>

fair

10

NV

Halko

,2009

23

812ye

arsof

scho

olin

g/un

iversity

Right

22–4

6Ultim

atum

game

Unfair>

fair(noco

mpetition)

12

NV

Haren

ski,2006

10

10

n/r

Right

18–2

9W

atch

-decreasepictureev

a-luationtask

Watch

moral>

odd–

even

baseline

7NV

Harl� e,2012

38

23

n/r

n/r

18–7

0Ultim

atum

game

Unfair>

fair

12

NV

38

23

n/r

n/r

18–7

0Ultim

atum

game

Fair>

unfair

3NR

(Continues)


TABLE1

(Continue

d)

Firstau

thor,ye

arN

FEdu

cation

Han

dedn

ess

Age

Task

Contrast

Foci

Categ

ory

Hee

keren,

2005

12

2n/r

Right

25.756

1.54

Ling

uistic

materialrating

(moral\im

moral,seman

ti-

cally

correct\inco

rrect)

Moraldecision>seman

tic

decision

8NR

Hu,

2015

36

24

n/r

n/r

22.726

2.85

Dictatorgame

“Help”>

“help_control”

10

NR

Hu,

2016

23

n/r

Unive

rsity

Right

19–2

5Ultim

atum

game

Unfair>

fair

3NV

Luo,2006

20

11

n/r

n/r

20–3

6Illeg

alan

dlegalbe

havioral

scen

arios’observation

Illeg

al>

legal

9NV

Kirk,

2011

40

21

n/r

n/r

n/r

Ultim

atum

game

Unfair>

fair(controls)

11

NV

Melch

ers,2015

60

39

Unive

rsity

n/r

22.9565.38

Perceptionofem

barrass-

men

ts’film

san

dno

rmal

film

s

Vicariousem

barrassmen

tfilm

s>co

ntrolfilm

s6

NV

Moll,

2002

74

n/r

Right

30.3

64.7

Moralan

dno

n-moralsen-

tenc

esjudg

emen

tMoral>

neu

tral

3NR

Prehn

,2008

23

23

Unive

rsity

Right

25.176

6.56

Sociono

rmativean

dgram

-matical

judg

emen

tsrating

Socio-norm

ativejudg-

men

ts>gram

matical

judg-

men

ts

6NR

Rilling,

2008

20

15

n/r

Right

21.26

2.9

Prisone

r’sDilemma

Unreciprocated>reciproca-

tedco

operation

6NV

Sanfey

,2003

19

0n/r

n/r

n/r

ultimatum

game

Unfair>

fair

17

NV

Schreibe

r,2012

19

n/r

Unive

rsity

n/r

20–2

3Perceptionofno

rm-violating

versus

norm

-consistent

images

Norm

-violatingve

rsusnorm

-co

nsisten

tIm

ages

5NV

Servaas,2015

120

120

Unive

rsity

Right

18–2

5Ultim

atum

game

Unfair>fair

32

NV

120

120

Unive

rsity

Right

18–2

5Ultim

atum

game

Fair>

unfair

4NR

Tab

ibnia,

2008

12

9Und

ergrad

uate

Right

21.8

Ultim

atum

gamemodifica-

tion

Highfairness>

low

fairness

8NR

Takah

ashi,2008

15

n/r

n/r

Right

20.16

0.8

Senten

ces(neu

tral,moral

beau

ty,an

dmoralde

prav-

ity)

Moraldep

ravity-neu

tral

2NV

15

n/r

n/r

Right

20.16

0.8

Senten

ces(neu

tral,moral

beau

ty,an

dmoralde

prav-

ity)

Moralbea

uty

>neu

tral

5NR

Tomasino,2013

17

0n/r

Right

27.356

3.88

Ultim

atum

game

Fair>

unfair

3NR

Tread

way,2014

41

n/r

n/r

n/r

n/r

Scen

ariosrating

(neu

tral,

emotiona

llyha

rmful)

Intentional>unintentional

(allsubjects)

18

NV

Wagne

r,2011

18

18

n/r

n/r

25–3

0Emotionco

nditions

task

Guilt

>sham

e1sadness

2NV

(Continues)


et al., 2008), scenarios with norm-violations (Denke et al., 2014),

picture evaluation task with scenes with moral norm violations

(Harenski and Hamann, 2006), norm violated behavior’s scenarios (Luo

et al., 2006), embarrassing content (Melchers et al., 2015), norm-

violating images (Schreiber and Iacoboni, 2012), a task that modulated

social interaction (Yoder and Decety, 2014), different scenarios based

on intentional and unintentional norm violation (Treadway et al., 2014),

and a task that modulated of emotions related to social content (Wag-

ner et al., 2011). Overall, 29 experiments included in this category

reflect social emotions associated with norm violation.

2.2 | Meta-analysis

Activation likelihood estimation (ALE) is a meta-analysis method, which

can be used for whole-brain, random-effects voxel-wise imaging analy-

sis (Eickhoff et al., 2009, 2017; Eickhoff, Bzdok, Laird, Kurth, & Fox,

2012). For our study, we used GingerAle version 2.3.6 (freely available

at brainmap.org/ale). It uses foci combined from different studies to

create a probabilistic map of activation that is thresholded and com-

pared against a null distribution at a voxel-by-voxel level.

This map provides the clusters (peak and volume) that have a signif-

icant likelihood of being detected across studies within a stereotaxic

coordinate space. Specifically, activation likelihood estimates are calcu-

lated for each voxel by modeling each coordinate with an equal weight-

ing using a 3-D Gaussian probability density function. ALE values can be

thresholded using a cluster-forming (i.e., in terms of magnitude) and a

cluster-level (i.e., in terms of the size of the cluster) criterion. Thus, ALE

values provide information about statistical maps of estimated activation

regarding tasks included in the analyses. To create ALE maps we used

contrast coordinates (i.e., experiments) reported in eligible, previously

published fMRI studies that include experiments on social norms “over-

all” and subcategories for (a) social norm representation and (b) norm

violation. The overall analysis (i.e., social norms overall) allows for identi-

fying concordance at the single study level with higher power as more

studies are included in this analysis; however, contrast analysis allows

for examining the conjunction and differences between the subcatego-

ries. Montreal Neurological Institute (MNI) coordinates were trans-

formed into Talairach coordinates. Significance is assessed using a

cluster-level correction for multiple comparisons at p5 .05 and a

cluster-forming threshold p< .001 (Eickhoff et al., 2012, 2017). A con-

trast analysis was performed on the thresholded ALE maps of social

norm representation and norm violation categories to identify concord-

ance that was common (i.e., conjunction) and different for these

categories. Because ALE maps are already thresholded for multiple com-

parisons a threshold of uncorrected 0.01, with 5000 permutations, mini-

mum volume 50 mm2 was used (e.g., Arsalidou, Pawliw-Levac, Sadeghi,

& Pascual-Leone, 2017; Sokolowski, Fias, Mousa, & Ansari, 2017).

3 | RESULTS

Articles included in the meta-analyses report data on 993 participants

(Table 1). Eight articles did not report gender; of the remaining articles,

52% were female participants. About a half of articles that reportedTABLE1

(Continue

d)

Firstau

thor,ye

arN

FEdu

cation

Han

dedn

ess

Age

Task

Contrast

Foci

Categ

ory

Wu,

2015

32

24

Unive

rsity

Right

22.316

2.35

Ultim

atum

game,

dictator

game

Unfair>

fairUltim

atum

Gam

e1

NV

32

24

Unive

rsity

Right

22.316

2.35

Ultim

atum

game,

dictator

game

FairUltim

atum

Gam

e>

unfair

Ultim

atum

Gam

e

3NR

Yode

r,2014

40

21

n/r

n/r

216

2So

cial

interactions’m

odu

la-

tiontask

Bad

>go

odactions

9NV

40

21

n/r

n/r

216

2So

cial

interactions’m

odu

la-

tiontask

Good>

bad

actions

15

NR

Zhe

ng,2015

25

18

n/r

Right

21.446

3.38

Ultim

atum

game

Uneq

ual

>eq

ual

15

NV

Zho

u,2014

28

15

Unive

rsity

Right

25.076

3.35

Ultim

atum

game

Unfair>

fair

4NV

28

15

Unive

rsity

Right

25.076

3.35

Ultim

atum

game

Fair>

unfair

1NR


handedness (42%) tested participants who were right-handed (100%).

Four articles did not report the age of the participants. When an age

range was given, the median of the age range was used in calculating

the average of the sample, which was a 23.8966.28 year. Twenty-five

percent of the articles reported the education level of participants, and

100% of the participants were reported to have some university educa-

tion (undergraduate or graduate). Bottom of Figure 1 shows the num-

ber of articles, number of experiments, and number of foci included in

each meta-analysis.

3.1 | ALE maps

3.1.1 | Social norms (overall)

All tasks related to social norms show concordance in five clusters

(Table 2). The largest cluster with the highest ALE value is found in the

right insula (BA 13). The second largest cluster is found in the left

medial frontal gyrus (BA 32) that extended to the cingulate gyrus (BA

32). Prefrontal activity is also observed in the right superior and middle

frontal gyri (BA 9 and BA 10). Other regions include the left insula and

claustrum.

3.1.2 | Social norm representation

Social norm representations show concordance in a cluster that

includes the left anterior cingulate and right medial frontal gyrus (BA

10; Figure 2 and Table 2).

3.1.3 | Norm violation

Five suprathreshold clusters were detected for norm violation (Figure 2

and Table 2). The one with the highest likelihood of being detected is

in the right insula (BA 13). Other regions include right cingulate gyrus

(BA 32), left insula (BA 13) and claustrum, and right middle and superior

frontal gyri (BA 9 and 10).

3.1.4 | Social norm representation versus norm violation

No common clusters survive the conjunction between social norm rep-

resentation and norm violation. Compared to norm violation, social

norm representation shows greater concordance in the anterior cingu-

late gyri (BA 32) and right medial frontal gyrus (BA 10), whereas com-

pared to social norm representation, norm violation shows greater

concordance in the right insula and claustrum and more dorsal parts of

the cingulate gyrus (BA 24, 32; Table 2).

4 | DISCUSSION

We examined neural correlates of social norms using quantitative ALE

meta-analyses. Processing tasks that assess social norms show con-

cordance mainly in frontal regions with clear significant distinctions

between instances of social norm representation and norm violation.

Specifically, our results reveal two key findings. First, norm violation

tasks show that the area with the highest likelihood of being active is

FIGURE 2 Brain maps demonstrating significant ALE values for each category. Left5 left. Note: coordinates are in Talairach space. Cluster-levelcorrection p5 .05 for multiple comparisons with cluster forming threshold p< .001 [Color figure can be viewed at wileyonlinelibrary.com]


http://wileyonlinelibrary.com

the insula, along with dorsolateral prefrontal regions and dorsal parts of

the cingulate gyrus. Secondly, social norm representations rely on activ-

ity mainly in ventromedial prefrontal regions; medial frontal and ante-

rior cingulate gyri. Findings are in agreement with Montague and

Lohrenz (2007) hypothesis, which suggests that different systems

underlie different social norm processes. We did not replicate any of

the concordance of posterior brain regions observed by Feng et al.

(2015), likely because these were smaller clusters that did not survive

our cluster-level correction for multiple comparisons. Alternatively, lack

of concordance in posterior regions may be due to visual-spatial heter-

ogeneity in task paradigms assessing “social norms.” Importantly, we

show that according to contrast analyses, the anterior cingulate and

medial frontal gyri are significantly more concordant for social norm

representation processing, whereas the right insula, dorsolateral pre-

frontal, and the dorsal cingulate cortices are significantly more concord-

ant to norm violation processing.

4.1 | Social norm representation

Social norm representation tasks show concordant activity in the left

anterior cingulate (BA 32) extended to right medial frontal gyrus (BA

10). BA 10 is mainly implicated in inferences of another person’s

TABLE 2 Concordant areas for each category

Talairach coordinates

Category Volume mm3 ALE value x y z Brain area BA

Social norms (overall) 4016 0.0480 34 18 4 Right insula 13

3392 0.0429 24 10 46 Left medial frontal gyrus 320.0342 4 20 38 Right cingulate gyrus 320.0306 4 22 28 Right cingulate gyrus 32

1808 0.0270 230 20 8 Left insula 130.0253 230 14 22 Left claustrum0.0251 234 14 0 Left insula 13

1736 0.0276 36 40 20 Right middle frontal gyrus 100.0236 34 26 32 Right middle frontal gyrus 9

936 0.0297 8 52 24 Right superior frontal gyrus 9

Social norm representation 1184 0.0163 24 50 22 Left anterior cingulate 10

0.0116 10 48 6 Right medial frontal gyrus 10

Norm violation 4368 0.0472 34 18 4 Right insula 13

4192 0.0339 6 18 38 Right cingulate gyrus 320.0329 24 10 48 Left superior frontal gyrus 60.0306 4 22 28 Right Cingulate gyrus 320.0203 26 28 30 Left cingulate gyrus 9

1912 0.0258 230 20 8 Left insula 130.0239 230 14 22 Left claustrum

1464 0.0236 34 26 32 Right middle frontal gyrus 90.0175 34 42 22 Right middle frontal gyrus 100.0150 42 22 40 Right middle frontal gyrus 8

856 0.0255 6 52 24 Right superior frontal gyrus 9

Social norm representation>norm violation

1080 3.7190 2 45 2.7 Right anterior cingulate gyrus 32

3.5400 4 48 2 Right anterior cingulate gyrus3.3528 21 52 22 Left anterior cingulate gyrus3.2389 4 52 0 Right medial frontal gyrus 103.0902 5 51 24 Right medial frontal gyrus 10

Norm violation> socialnorm representation

2848 3.7190 40.3 19.2 3.9 Right insula 13

3.5401 37 21 2 Right insula 133.2389 37 13 9 Right insula 133.1560 34.8 10.8 3.7 Right insula 13

1976 3.7190 6.7 24.3 27.3 Right anterior cingulate gyrus 243.5400 0 26 26 Left cingulate gyrus 323.3528 22 30 30 Left cingulate gyrus 323.2389 6.5 20.6 35.2 Right cingulate gyrus 323.0902 9.3 16 36.7 Right cingulate gyrus 322.9478 26 24 26 Left anterior cingulate gyrus 24

616 3.0902 35.3 24.7 36.7 Right middle frontal gyrus 92.9112 34.9 23.1 32.2 Right middle frontal gyrus 92.7703 41 22 42 Right middle frontal gyrus 8

Conjunction between norm violationand social norm representation

No clusters found


intentions, mostly social intentions (Ciaramidaro et al., 2007; Frith &

Frith, 2003). The “gateway hypothesis” states that BA 10 activity sup-

ports mechanisms that allow individuals to react to environmental stim-

uli based not on immediate perceptual information but on self-

generated and maintained representations (Burgess, Dumontheil, & Gil-

bert, 2007). Thus, this region seems to be mainly involved in processes

of relational integration by manipulation of self-generated information

and highly abstract information (Christoff et al., 2001; Christoff, Kera-

matian, Gordon, Smith, & Mädler, 2009). Previous fMRI and transcra-

nial direct current stimulation (tDCS) findings propose the right lateral

prefrontal cortex to play a key role in the behavioral control and judg-

ment between fair and selfish responses (Ruff, Ugazio, & Fehr, 2013).

The findings suggest that activity in the dorsal anterior cingulate cortex

has been implicated in processing the detection and appraisal of social

processes, such as exclusion and “social pain” phenomenon (Corradi-

Dell’Acqua, Tusche, Vuilleumier, & Singer, 2016; Dedovic, Slavich, Mus-

catell, Irwin, & Eisenberger, 2016; Kawamoto, Ura, & Nittono, 2015).

We suggest that prefrontal BA 10 serves to support abstract represen-

tation of existing norms. It would be interesting to examine the involve-

ment of these regions in newly formed social norm representations.

4.2 | Norm violation

Processing norm violations elicits activity in the insular cortex. The

anterior insula is generally considered as a relay station that sends

interoceptive information to the cortex (Menon & Uddin, 2010; Seeley

et al., 2007; Taylor, Seminowicz, & Davis, 2009). However, its activity

is also associated in all sorts of cognitive and affective activities (Duer-

den et al., 2013; Uddin, 2015). Social-emotional tasks reveal activity in

the anterior-ventral insula, while cognitive tasks elicited activation in

the anterior-dorsal part (Kurth, Zilles, Fox, Laird, & Eickhoff, 2010). It

was suggested that the insula also plays a role in fairness-related

behavior (Moll, Oliveira-Souza, & Zahn, 2008; Corradi-Dell’Acqua,

2013). In particular, the right insula (BA 13) and anterior cingulate have

been also shown to activate to first-hand and vicarious experiences of

unfairness (Cheng et al., 2015; Cheng et al., 2017), lie evaluation (Lelie-

veld, Shalvi, & Crone, 2016), and detection of distributional inequity in

economic tasks (Zhong, Chark, Hsu, & Chew, 2016), which could be

explained as a violation of social norms. Patients with damaged insula

have abnormal expressions of trust in economics tasks such as the

Trust Game, which leads to an inability to detect norm violation effec-

tively (Belfi, Koscik, & Tranel, 2015). Moreover, insular activation has

an indirect influence on social preferences as aversive emotional states

increase the frequency of receiving unfair monetary offers, which cor-

respond to worse detection of norm violation (Harl�e et al., 2012).

We also find concordance in the anterior cingulate cortex. Previ-

ous findings also suggest that anterior cingulate cortex is implicated in

social behavior and possibly processing costs and benefits (Apps, Rush-

worth, & Chang, 2016). Specifically, the anterior cingulate cortex acti-

vates when processing rewards that other people receive (Lockwood,

Apps, Roiser, & Viding, 2015) and when others make decisions related

to prediction error (Apps, Green, & Ramnani, 2013). It was shown that

anterior cingulate cortex to anterior insula connectivity may also reflect

basic prosocial motivation (Hein, Morishima, Leiberg, Sul, & Fehr,

2016). Furthermore, people with higher egoistical motivation, who

more frequently violate social norms, have weaker connectivity

between these regions (Hein et al., 2016). This is consistent with the

hypothesis that the cingulate gyrus and insula are involved in conver-

sion of affective goals into cognitive goals (Arsalidou & Pascual-Leone,

2016) as a feeling of effort in cognitively demanding situations (Arsali-

dou et al., 2017). A generic role of the insula as part of a salience net-

work has been suggested (Menon & Uddin, 2010; Uddin, 2015). We

propose that the role of the insula in norm violation may be related to

a generic sense of cognitive demand related to the “inequity encoding”

(Hsu, Anen, & Quartz, 2008) and fairness-related behavior.

Other areas related to norm violation include the right cingulate

gyrus and left claustrum. A meta-analysis suggests that cingulate cortex

is implicated in six domains according to the activation’s map: attention,

pain, language, action execution, emotions, and memory (Torta &

Cauda, 2011). The cingulate cortex has received extensive attention in

its role in social norms and was studied under paradigms of altruistic

punishment in social dilemmas (Fehr & Camerer, 2007; Feng et al.,

2016; Sanfey, Loewenstein, McClure, & Cohen, 2006). Moreover, the

dorsal anterior cingulate cortex through its strong connectivity with the

insula could be related to the detection of social norm violations during

conflict monitoring and moral context evaluation (G€uro�glu et al., 2011;

Denke et al., 2014). Therefore, in processing norm violations, we sug-

gest that the role of the dorsal cingulate to be a hub for information

where signals are sent to the insula to help evaluate possible norm vio-

lation; such process would not be pertinent during social norm

representation.

Norm violation studies also show concordant activity in the right

middle frontal gyrus (BA 10). The middle frontal gyrus BA 10 has been

associated with general abstract representations that require process-

ing of internally generated information (Christoff & Gabrielli, 2000;

Chrisoff et al., 2009). Specific to social cognition, the right lateral pre-

frontal cortex has been shown to be linked to processing of context-

dependent social interaction regulated by norms of fairness in case of

financial exchange (Ruff et al., 2013), understanding of social standards

related to fairness norms and good reputation (Knoch, Pascual-Leone,

Meyer, Treyer, & Fehr, 2006; Knoch, Schneider, Schunk, Hohmann, &

Fehr, 2009), and inferences of another person’s intentions, mostly

social intentions (Ciaramidaro et al., 2007; Frith & Frith, 2003). Evi-

dence from lesions studies and meta-analysis show that BA10 is also

involved in performance theory of mind tasks, and social cognition in

general (Gilbert et al., 2006; Roca et al., 2011). We suggest that BA 10

contribution to processing social norms could be related to the detec-

tion of norm violation and the possibility to process knowledge about

the existing norm. According to the “gateway hypothesis” (Burgess

et al., 2007), BA 10 contributes to forming self-generated representa-

tions that are not necessarily environmentally based. This hypothesis is

consistent with claims that suggest BA 10 to process highly abstract

information (Christoff et al., 2001; Christoff et al., 2009). Based on this

literature, we suggest that BA 10 contribution to processing social

norms could be related to the detection of norm violation and the pos-

sibility to process knowledge about the existing norm. This


interpretation is also consistent with Montague and Lohrenz (2007)

model that suggests the existence of specific brain representations to

keep information about existing social norms.

Another significantly concordant region for norm violation is the

claustrum, a region adjacent to the insula. The claustrum due to the

numerous input–output connections with limbic, prefrontal, sensory,

motor, and associative cortices was assumed to act as a cross-modal

integrator (Goll, Atlan, & Citri, 2015). It has also to been identified as a

key region of a network that supports consciousness (Koubeissi, Barto-

lomei, Beltagy, & Picard, 2014). Claustrum activation is also reported in

studies of fairness-related inequity during decision-making (Nihonsugi,

Ihara, & Haruno, 2015); however, its role was not semantically defined.

A meta-analysis reports that claustrum is involved in general empathy

and pain-related empathy processing (Gu, Hof, Friston, & Fan, 2013).

Concordant activity in this region supports its nonrandom appearance

in social cognition studies. Although further work is needed to clearly

define the functions of the claustrum, some evidence point to its spe-

cial impact on social behavior. Studies show that claustrum activity is

related to processes such as fear recognition (Stein, Simmons, Fein-

stein, & Paulus, 2007) and associative learning in animals (Chachich &

Powell, 2004), and multimodal information processing and emotional

responses (Bennett & Baird, 2006) in healthy humans. Anatomically the

volume of the claustrum is deficient in clinical populations that suffer

from socio-cognitive deficits. For instance, claustrum volume in autism

patients is 22% reduced compared to healthy children from 4 to 8

years (Wiegel et al., 2014). Examination of altered connectivity in indi-

viduals with autism and comparison with behavioral performance sug-

gest that claustrum and its network interactions could significantly

contribute in social and communication development (Wiegel et al.,

2014). Owing to this multimodal integration, we propose that the

claustrum could integrate aversive emotional signals and signals from

associative cortices in norm violation processing.

Our analysis also found concordant activity in left superior frontal

gyrus (BA 6). The superior frontal gyrus (BA 6) has been linked to

higher cortical functions such as internal guidance of the behavior and

its control (Luria, 1966), hand motor representations (Vara et al., 2014),

and working memory (Wager & Smith, 2003 for review; du Boisguehe-

neuc et al., 2006). Specifically, it is suggested that this region is

involved in fronto-parietal cortical network associated with attention,

working memory, episodic retrieval, and conscious perception (Naghavi

& Nyberg, 2005 for review). In addition, an activation of cingulate cor-

tex/superior frontal cortex has been found during processing psycho-

logical self (Hu et al., 2016). It has been suggested that cingulate cortex

is involved in conflict monitoring (Botvinick, Cohen, & Carter, 2004),

which could be applicable for socially driven interactions (Lavin et al.,

2013). Thus, cingulate cortex activation during norm violation process-

ing could be related to direct conflict monitoring and evaluation with

self-reference (i.e., what does norm violation mean for me). We suggest

that activation of the left superior frontal gyrus in the same cluster as

the right cingulate gyrus corresponds with the need to continuously

monitor and adjust information about others behavior in working mem-

ory relevant to norm violation processing. Overall, concordant fMRI

findings suggest that activation of the lateral prefrontal cortex during

affective information processing, of the anterior cingulate cortex during

monitoring any conflict, and of the insula during emotional processing

of aversive signals and responses to unfairness may be involved into

driving a motivation to act against norm violations.

5 | LIMITATIONS

Data presented here represent concordance across fMRI studies that

investigated social norms overall and as two different subcategories in

healthy adults. Optimally, further cortical differentiation would be pos-

sible with additional social norm subcategories such as social norm rep-

resentation in social and moral domains and social conformity.

However, an insufficient number of experiments did not allow for

examining concordance in these subcategories (i.e., n<17; Eickhoff

et al., 2017). Second, we examine the activity to various tasks that may

elicit a differentiated brain response, such as moral paradigms (scenario

ratings) and classic economic tasks (e.g., Ultimatum Game, Trust Game).

In the future, as more experiments become available, it could be possi-

ble to distinguish between these domains within social norms. Task

characteristics (e.g., visual-spatial features and task demands such as

economic games versus reading and rating tasks) could also influence

heterogeneity across studies. Importantly, our goal was to identify

common patterns in brain locations related to social norms regardless

of task specificities, and our results show that this concordance is

observed in anterior brain areas. Last, a shortcoming of the ALE

method is that it does not use effect sizes (as seed-based mapping

(SDM; Radua & Mataix-Cols, 2012; Radua et al., 2012)). Although there

are no available methods for performing robustness analyses with Gin-

gerALE, simulations of ALE analyses have been performed to test sensi-

tivity, ensuing cluster sizes, number of incidental clusters, and statistical

power (Eickhoff et al., 2016). They did so by systematically varying the

overall number of experiments and experiments activating the simu-

lated “true” location (Eickhoff et al., 2016 for details) and a recom-

mended minimum number of experiments to reach sufficient power

(n517–20; Eickhoff et al., 2017). Despite these shortcomings, the cur-

rent meta-analyses present new knowledge on the topic of social

norms with a meta-analytic methodology that provides coordinates in

stereotaxic space, which is advantageous to standard reviews.

6 | CONCLUSION

Social norms are fundamental for our daily social interactions and our

meta-analyses show that different aspects associated with social norms

elicit activity in distinct brain regions. The right anterior cingulate and

medial frontal gyri (BA 10) are critical for social norm representation

(social and moral), whereas the insula, dorsolateral, and dorsal cingulate

cortices are key for processing norm violation. Stereotaxic coordinates

reported here can serve as a normative adult framework for targeted

future studies and may be beneficial for studies investigating social

norm compliance and enforcement in patients with disorders such as

autism spectrum disorder.


CONFLICT OF INTEREST

The authors declared that they have no conflict of interest.

ORCID

Oksana Zinchenko http://orcid.org/0000-0002-7976-3224

Marie Arsalidou http://orcid.org/0000-0001-9879-3894

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23895





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Attachment B. Article “Neurobiological mechanisms of fairness-related social

norm enforcement: a review of interdisciplinary studies”.

Modern neuroimaging studies begin to explore neurobiological mechanisms of

social norms enforcement. Several regions of frontal lobes and temporo-parieto-

occipital cortex play a key role in decision making of social punishment of

fairness’ norm violation. The cutting–edge methods of brain stimulation allow to

change frequency and intensity of social punishment in different economic tasks

(games). The analysis of modern studies show that brain mechanisms of decision

making to punish non–cooperative individual requires further investigation with

brain stimulation methods to differentiate the role of frontal and temporo-

parietooccipital regions and clarify its interaction.

ЖУРНАЛ ВЫСШЕЙ НЕРВНОЙ ДЕЯТЕЛЬНОСТИ, 2018, том 68, № 1, с. 16–27

16

ВВЕДЕНИЕ

Наличие норм является важной особенно-стью социального поведения человека. С их помощью достигается не только упорядочен-ность совместных действий, но и оптимизация поведения отдельного индивида [Cialdini et al., 1990]. Современные исследования социальных норм становятся все более междисциплинар-ными, объединяя экономические [Camerer et al., 2004; Fehr, Fischbacher, 2004], социально психологические [Sherif et al., 1953; Hogg et al., 2006] и нейробиологические подходы [Spitzer

et al. 2007; Rilling et al., 2008]. Задачей насто-ящей работы является анализ исследований поддержания социальных норм, комбини-рующих современные методы картирования головного мозга и подходы поведенческой экономики.

В последнее десятилетие большое коли-чество исследований было посвящено ней-робиологическим механизмам социального наказания некооперативных индивидов, на-рушающих социальные нормы в непосред-ственном двустороннем взаимодействии. Од-нако количество исследований социального

DOI: 10.7868/S0044467718010021

Ключевые слова: социальные нормы, социальное наказание, наказание третьей стороной, дорсолатеральная префронтальная кора, дорсомедиальная префронтальная кора, темен-но-височно-затылочная область, транскраниальная магнитная стимуляция (ТМС), транс-краниальная электрическая стимуляция постоянным током (ТЭС), функциональная маг-нитно-резонансная томография (фМРТ).

Современные нейроимиджинговые исследования начинают приоткрывать нейробиологи-ческие механизмы следования социальным нормам. Настоящий обзор анализирует нейро-имиджинговые исследования поддержания социальной нормы справедливости с помощью социального наказания, с акцентом на социальном наказании третьей стороной ввиду ма-лой изученности этого феномена. Анализ литературы свидетельствует, что процесс соци-ального наказания за нарушение нормы справедливости поддерживается распределенной активностью ряда областей коры головного мозга: (а) системой оценки социальных норм и (б) системой ментализации, с регионами-интеграторами информации в лобных отделах и теменно-височно-затылочной области мозга соответственно. Однако анализ современ-ных исследований показывает, что нейробиологические механизмы принятия решения о социальном наказании некооперативного индивида требуют дополнительного изучения. Актуальным для будущих исследований представляется прояснение механизма взаимодей-ствия вышеописанных нейронных сетей методами стимуляции отделов мозга и методами магнито- и электроэнцефалографии.

Поступила в редакцию 12.12.2016 г. Принята в печать 22.05.2017 г.

1 Центр нейроэкономики и когнитивных исследований, Национальный исследовательский университет “Высшая школа экономики”, Москва, Россия.

2Лаборатория экспериментальной и поведенческой экономики, Национальный исследовательский университет “Высшая школа экономики”, Москва, Россия.

3 Центр нейроэкономики и когнитивных исследований, Национальный исследовательский университет “Высшая школа экономики”, Москва, Россия.

e-mail: [email protected], [email protected], [email protected] 3

© 2018 О. О. Зинченко1, А. В. Белянин2, В. А. Ключарев3

НЕЙРОБИОЛОГИЧЕСКИЕ МЕХАНИЗМЫ ПОДДЕРЖАНИЯ СОЦИАЛЬНОЙ НОРМЫ СПРАВЕДЛИВОСТИ: ОБЗОР

МЕЖДИСЦИПЛИНАРНЫХ ИССЛЕДОВАНИЙ

УДК 159.91

ОБЗОРЫ, ТЕОРЕТИЧЕСКИЕ И ДИСКУССИОННЫЕ СТАТЬИ

НЕЙРОБИОЛОГИЧЕСКИЕ МЕХАНИЗМЫ ПОДДЕРЖАНИЯ СОЦИАЛЬНОЙ НОРМЫ… 17

ЖУРНАЛ ВЫСШЕЙ НЕРВНОЙ ДЕЯТЕЛЬНОСТИ том 68 № 1 2018

наказания, осуществляемого сторонним на-блюдателем, т.н. третьим лицом, ограничено. Важно отметить, что именно наказание нару-шителей норм третьей стороной (человеком, наблюдающим за нарушением норм “со сторо-ны”) является ключевым для стабилизации ко-операции в больших группах индивидов [Fehr, Fischbacher, 2004]. Поэтому в нашей работе мы провели анализ исследований нейробиологи-ческих механизмов социального наказания третьей стороной для выяснения ключевых си-стем мозга, вовлеченных в поддержку нормы справедливости в социальных группах.

СОЦИАЛЬНЫЕ НОРМЫ. КАК ПОЯВЛЯЕТСЯ СОЦИАЛЬНОЕ

НАКАЗАНИЕ

Социальные нормы предписывают поведе-ние, ориентированное не на личные матери-альные интересы, а на следование определен-ным установкам или предпочтениям, одобря-емым обществом. Нормы способны влиять на поведение и приводить к сильным отклонени-ям наблюдаемых результатов от равновесных предсказаний классической экономической теории. Нормы являются частью группового наследия – общества или малой группы, и их существование поддерживается членами этой социальной группы – выражением поощре-ния за следование или наказанием за откло-нение от них [Elster, 1989]. Помимо когнитив-ного компонента (усвоенного ожидания “как следует себя вести”), важен и эмоциональный компонент норм, ведь отклонение от социаль-ной нормы порождает ряд социальных эмо-ций, таких как стыд и вина, которые, в свою очередь, становятся мощными мотиваторами действий. В задачах распределения ресурсов важную роль играет норма равенства деле-жа: такие равные дележи большинство лю-дей склонно считать справедливыми, причем даже в тех случаях, когда они могут перерас-пределить ресурсы в свою пользу [Elster, 1989; Kahneman et al., 1986]. Более того – несправед-ливость дележа также может быть источником определенного психологического дискомфор-та, поэтому стремление к справедливости мо-жет также рассматриваться в качестве способа максимизации личной выгоды [Deutsch, 1985, сh.11; Elster, 1989; Messick, Sentis, 1983].

В экономических играх социальная нор-ма справедливости и отклонения от нее

моделируются распределениями финансо-вых трансферов между игроками. Так, напри-мер, в классической экспериментальной игре в “Диктатора” участвуют два человека, один из которых (“диктатор”) принимает едино-личное решение о том, как распределить ус-ловный “бюджет” (очки, баллы, деньги и пр.) между собой и другим игроком (“получате-лем”). Норма справедливости в данном случае диктует дележ очков между участниками в со-отношении 50:50, тогда как дележ 70:30 будет восприниматься как отклонение от нормы, а дележ 90:10 – как вопиюще несправедливый [Forsythe et al., 1994; Qu et al., 2014; Sun et al., 2015]. Результаты мета-анализа, основанно-го на поведении более чем 20 000 пар игро-ков по всему миру, показывают, что “диктато-ры” в среднем склонны отдавать получателям 28.35% полученного бюджета [Engel, 2010], де-монстрируя наличие как эгоистических, так и кооперативных мотивов.

Норма справедливости может поддержи-ваться за счет нескольких факторов, среди ко-торых особый интерес исследователей вызыва-ет механизм наказания, или санкций в случае отклонения от социальной нормы для поддер-жания кооперации [Fehr, Fischbacher, 2004]. Исследования показывают, что социальное на-казание применяется индивидами даже в слу-чае однократного взаимодействия, что может объясняться переживанием негативных эмо-ций к “отступникам” – людям, нарушающим социальную норму в рамках взаимодействия [Fehr, Gächter, 2002]. Более того, объем нака-зания – количество инвестированных в нака-зание ресурсов – пропорционален величине отклонения от нормы. Попытка наказать – оказать некое негативное воздействие на того, кто повел себя несправедливо – несовместима с традиционной гипотезой рационального по-ведения – подразумевающей лишь стремление максимизировать собственную выгоду и со-хранить ресурсы. Одна из возможных теорий, почему индивиды применяют социальное на-казание, заключается в существовании “ме-та-нормы”, вызывающей неодобрение третьих лиц в случае отклонения индивида от социаль-ной нормы [Axelrod, 1986; Elster, 1989].

ВИДЫ СОЦИАЛЬНОГО НАКАЗАНИЯ

Социальное наказание можно классифици-ровать по его контексту и адресату – наказание

18 ЗИНЧЕНКО и др.


в двустороннем взаимодействии (second-party punishment) и наказание третьей стороной (third-party punishment). Наказание в двусто-роннем взаимодействии предпринимается не-посредственным участником взаимодействия (реципиентом) как реакция на несостояв-шееся кооперативное взаимодействие [Fehr, Gächter, 2002; Fehr et al., 2002]. В этом случае второй игрок (реципиент) тратит свои соб-ственные ресурсы на то, чтобы уменьшить вы-игрыш первого игрока (агента), совершившего некооперативное действие. В ситуации эконо-мической игры наказание может выглядеть как отказ от дальнейшего взаимодействия, – на-пример, в “Ультимативной Игре”, в которой агент теряет весь выигрыш, если реципиент отказывается принимать его предложение. В другом варианте наказания реципиент тра-тит собственные ресурсы на штраф, наклады-ваемый им на агента. Как показали исследова-ния, штраф обычно стимулирует реципиента следовать нормам и поддерживать кооперацию в дальнейшем [Fehr, Gächter, 2002; Herrmann et al., 2008].

Наказание третьей стороной осуществляет-ся участником (третьим игроком), который не вовлечен во взаимодействие непосредствен-но, но наблюдает за действиями других игро-ков. В этом случае участник не получает пря-мой выгоды от своих действий, поскольку не участвует в финансовых трансферах, однако может оказывать влияние на ход игры за счет имеющихся ресурсов путем применения штра-фа. Эрнст Фер с коллегами [Fehr et al., 2004] провели поведенческий эксперимент на осно-ве игр “Диктатор” и “Дилемма заключенного”, показавший, что более 60% не вовлеченных в непосредственное взаимодействие участни-ков–наблюдателей третьей стороны проявля-ли тенденцию использовать свой изначальный капитал для “наказания” – уменьшения зара-ботанной суммы агента, который распределил очки несправедливо между собой и реципиен-том [Fehr et al., 2014]. В игре “Диктатор” ре-шение о наказании третьей стороной обычно принималось, когда активный игрок передавал реципиенту менее половины своего бюджета, в то время как в “Дилемме заключенного” – в случаях, когда один участник принимал не-справедливое решение “не кооперировать”, в то время как второй участник кооперировал. В целом, традиционное экономическое пред-ставление о том, что затратные наказания за

собственный счет (без каких–либо матери-альных выгод для наказывающего) не долж-ны наблюдаться, т.к. не несут наказывающе-му никаких выгод, не нашло эмпирического подтверждения [Fehr, Fischbacher, 2004]. Что-бы объяснить подобное поведение, Эрнст Фер и Клаус Шмидт разработали теоретическую модель избегания неравенства, включающую в классическом виде оценку (А) “выгодного” неравенства – при котором бюджет игрока, принимающего решение, превышает бюджеты других игроков, и (Б) “невыгодного” неравен-ства – где бюджет игрока оказывается меньше по сравнению с бюджетами других игроков. “Невыгодное” неравенство, в свою очередь, операционализируется с помощью параметра “зависти”, в то время как “выгодное” – пара-метром “вины” [Fehr, Schmidt, 1999].

Интересно, что частота наказаний “третьей стороной” варьирует в зависимости от опреде-ленных условий. Более половины участников исследований принимали решения наказать (уменьшать выигрыш) участников, которые несправедливо распределяли выигрыши в игре “Диктатор” [Kahneman, Knetsch, Thaler, 1986]. Однако при введении возможности наградить участников, по отношению к которым было принято несправедливое решение, количество наказаний уменьшалось по сравнению с усло-виями, где нельзя было “возместить ущерб” пострадавшей стороне [Turillo et al., 2002]. Ча-вез и соавторы показали, что при предоставле-нии возможностей “возместить ущерб” и “на-казать виновного”, отняв у него определенную сумму, индивиды руководствуются следующи-ми целями: вознаградить равное распределе-ние средств, избегая неравенства; уравнять неравное распределение, сложившееся после принятия решения другим игроками; в слу-чае же, когда возможность компенсации от-сутствовала – индивиды принимали решение об осуществлении наказания [Chavez et al., 2013]. Это свидетельствует о том, что участник в роли третьей стороны предпочитает уравни-вать благосостояние игроков в первую очередь с помощью наград и лишь в отсутствие этой возможности/недостаточной ее эффективно-сти применять наказание путем уменьшения бюджета несправедливого участника.

Показано, что наказание третьей сторо-ной обусловлено определенными эмоцио-нальными процессами. Частота наказаний со



стороны третьих лиц возрастала, если в ходе эксперимента манипулировался уровень зло-намеренности (за счет модификации интен-ции нарушения социальных норм другим участником – намеренное/ненамеренное на-рушение) и вины (участник наделялся ответ-ственностью за осуществление санкций для исправления несправедливого распределения ресурсов) [Nelissen et al., 2009, Seip et al., 2014]. Так, в случае манипуляции уровнем злонаме-ренности частота наказаний возрастала, если нарушение нормы справедливости было наме-ренным. На наказание третьей стороной влия-ют и другие факторы: социальная дистанция – при ее увеличении сила наказания возрастает [Lieberman, Linke, 2007], репутация – в случае присутствия хотя бы одного наблюдателя ча-стота и наказание третьей стороной значимо возрастает [Kurzban et al., 2007].

Феномен социального наказания поэтапно формируется в онтогенезе. В 5 лет дети про-являют тенденцию взаимодействовать имен-но с индивидами, вне зависимости, следовали ли те ранее норме справедливости: дети пози-тивно взаимодействуют и с кооперативными, и с антисоциальными партнерами. Тогда как 8-летние дети проявляют избирательность, предпочитая взаимодействовать с индивида-ми (другими детьми), которые позитивно ре-агировали на просоциальное поведение и не-гативно реагировали на антисоциальное пове-дение – наказывали детей, нарушавших норму справедливости в игре [Hamlinet et al., 2011]. В возрасте 6 лет дети проявляют тенденцию осуществлять наказание игрока, несправед-ливо распределившего сумму игровых очков, находясь в роли третьей стороны, однако, если процесс наказания подразумевал трату их собственных ресурсов, частота наказаний несколько снижалась. Сравнение результа-тов экспериментов, в которых неравномерное распределение ресурсов игроками происхо-дило из-за эгоистического мотива и, напро-тив, из-за щедрости, показало, что 6–летние дети относительно плохо понимают эгоис-тические намерения при принятии решения [McAuliffe K. et al.,2015]. Судя по всему, эго-истические проявления в играх “Ультиматум” и “Диктатор” спровоцированы не невозмож-ностью понять принципы “что такое хорошо и что такое плохо”, но недостаточно разви-той у детей младшего возраста способностью

контролировать свое поведение и подавлять естественные реакции [Steinbeis et al., 2012].

Таким образом, социальное наказание тре-тьей стороной является динамическим про-цессом, последовательно формирующимся в онтогенезе и появляющимся уже в раннем детском возрасте. Такие факторы, как соци-альная дистанция и репутация, влияют на ча-стоту проявления социального наказания. При возможности возместить ущерб пострадавше-му частота наказаний снижается, из чего сле-дует, что неосознанно социальное наказание выступает как “крайняя мера”, к которой при-бегают участники взаимодействия для поддер-жания социальной нормы справедливости.

НЕЙРОИМИДЖИНГОВЫЕ КОРРЕЛЯТЫ ПРОЦЕССА НАКАЗАНИЯ

В ДВУСТОРОННЕМ ВЗАИМОДЕЙСТВИИ И ТРЕТЬЕЙ СТОРОНОЙ

Процесс принятия решения о необходи-мости наказания за нарушения нормы спра-ведливости может определяться различными мотивами, как, например, избеганием чувства вины и избеганием неравенства [Fehr, Schmidt, 1999; Carpenter, Matthews, 2009]. В контексте экономической игры избегание чувства вины представляет собой нежелание разочаровывать партнеров [Dufwenberg et al., 2000; Charness et al., 2006]. Иная мотивация – избегание нера-венства – заключается в стремлении избегать чрезмерной диспропорции в получаемых аген-том и реципиентом выигрышах [Fehr et al., 1999; Knoch et al., 2007]. Чувство вины агента может быть операционализировано как модуль разности бюджета, который инвестор ожида-ет получить обратно и реальным возвращен-ным “доверенным лицом” бюджетом. Иссле-дования с использованием функциональной магнитно-резонансной томографии (фМРТ) [Chang et al., 2011] показало, что избегание чувства вины сопровождается активацией пре-моторных отделов – преимущественно допол-нительной моторной области, а также темен-но-височно-затылочной области, островковой коры и дорсолатеральной лобной коры.

Другой мотив – избегание неравенства – может быть операционализирован как модуль разности общего бюджета и непотраченных ресурсов в экономической игре [Hsu et al., 2008]. Исследование мотивации избегания



неравенства с помощью искусственного мани-пулирования неравномерного распределения денежных средств при двустороннем взаимо-действии [Hsu et al., 2008; Tricomi et al., 2010; Haruno et al., 2010; Haruno et al., 2014], проде-монстрировало активацию передней поясной извилины, прилежащего ядра и миндалины, островковой коры и дорсолатеральной лобной коры, когда испытуемым предъявлялось не-равное распределение между ними и партне-ром. В целом, общей мозговой активностью, возникающей и при избегании чувства вины, и при избегании неравенства является акти-вация островковой коры и дорсолатеральной лобной коры.

фМРТ исследования демонстрируют не-которые различия в нейробиологических механизмах, обеспечивающих наказание в двустороннем взаимодействии и осущест-вляемое третьей стороной. Так, активация прилежащего ядра выше в ситуации нака-зания в двустороннем взаимодействии по сравнению с наказанием третьей стороной [Strobel et al., 2011]. Островковая кора так-же активируется сильнее при принятии ре-шения о необходимости наказания “отступ-ника” в двустороннем взаимодействии по сравнению с наказанием третьей стороной. Предполагается, что активность островковой коры, связанная с репрезентацией эмоцио-нальных состояний (преимущественно нега-тивных) и реакции на отклонение от соци-альных норм, играет тем самым важную роль в принятии решения об осуществлении со-циального наказания [Strobel et al., 2011].

Исследование принятия решения об от-ветственности за совершение криминально-го преступления и соответствующем размере наказания также показывает, что активность правой дорсолатеральной лобной коры меня-ется в зависимости от оценки ответственно-сти за совершение преступления, в то время как аффективная реакция коррелирует с ак-тивностью миндалины, дорсомедиальной лобной коры и задней части поясной изви-лины [Buckholtz et al., 2008]. Фенг и соавто-ры [Feng et al., 2016] изучали влияние фено-мена диффузии ответственности на поведе-ние третьих лиц, применяющих социальное наказание. Присутствие нескольких третьих лиц, осуществляющих одну и ту же функцию, когда каждый участник может подсознательно

чувствовать себя менее ответственным за под-держание норм, приводит к снижению ин-тенсивности наказания отклонения от соци-альных норм по сравнению с ситуацией, где наказание производится единственным испы-туемым [Feng et al., 2016]. Этот процесс сопро-вождается активностью дорсомедиальной лоб-ной коры, вероятно, контролирующей величи-ну наказания и получающей входные сигналы от верхней части островковой коры, вентроме-диальной лобной коры и предклинья.

Степень суровости наказания третьей сто-роной также варьирует в зависимости от того, считает ли индивид себя членом группы: в этом случае за отступление от социальных норм назначается сравнительно мягкое нака-зание, нежели за тот же самый “проступок” члену другой группы [Baumgartner T. et al., 2012]. В ситуации необходимости применения наказания к участнику “своей” группы акти-вируются дорсомедиальная лобная кора и те-менно-височно-затылочная область, ответ-ственные за ментализацию – интерпретацию мыслей и действий других игроков, в то время как при наказании членов чужой группы ак-тивировались области мозга, ответственные за принятие решений о необходимости санкций (орбитофронтальная кора, латеральная лобная кора и дорсальная часть хвостатого ядра в пра-вом полушарии). Таким образом, дорсомеди-альная лобная кора, вовлеченная в процессы ментализации, вероятно связана с определе-нием принадлежности нарушителя социаль-ных норм к группе и опосредует аффективное сопровождение процесса социального наказа-ния. Ментализация играет определенную роль в применении наказания – так было показа-но, что сознательное использование страте-гии “постановки себя на место другого” при-водит к повышению интенсивности эмоций при наблюдении за несправедливыми и спра-ведливыми предложениями в игре Диктатор [Gregucci et al., 2012]. В то же время, (дорсо-) латеральная лобная кора также играет важную роль в экономических взаимодействиях, вы-ступая в роли “хаба”, определяющего мораль-ную ответственность и оценку величины нака-зания [Buckholtz et al., 2012].

Другим свидетельством вовлечения медиаль-ных структур лобной доли в процесс осущест-вления социального наказания третьей стороной является электроэнцефалографическое (ЭЭГ)



исследование [Sun et al., 2015], изучавшее груп-пы испытуемых, различающиеся по уровню по-веденческих проявлений альтруизма, показало большую частоту применения наказания третьей стороной лицами с высоким уровнем поведенче-ского альтруизма, и различия в динамике спец-ифического связанного с событием вызванного потенциала – медиальной негативной фронталь-ной волны (МНФ). Этот компонент, возника-ющий с латентностью 300 мс, отражает эмоци-ональную категоризацию возникающего собы-тия [Fukushima, Hiraki, 2006]. Амплитуда МНФ возрастала у третьей стороны при наблюдении за максимально несправедливым предложением по сравнению со справедливыми финансовыми предложениями. В данном исследовании опреде-ление сильной или слабой предрасположенности к альтруизму осуществлялось после серии игр с финансовыми трансферами, где этим же игро-кам давалась возможность распределять очки от первого лица: так, если в 75% проб участник рас-пределял очки 50:50, ему присваивался высокий уровень альтруизма, средний – при распределе-ниях 70:30, низкий – если участник распределял очки в отношении 90:10. В противоположность этому, у лиц с низким уровнем альтруизма боль-шая амплитуда вызванного потенциала МНФ возникала при наблюдении за справедливыми финансовыми трансферами [Sun et al., 2015].

Современные статистические подходы так-же позволили обнаружить зависимость между объемом и толщиной серого вещества дорсо-медиальной лобной коры и беспристрастно-стью – способностью в равной степени нака-зывать за одинаковое нарушение социальной нормы участников своей и чужой группы, на-ходясь в роли третьей стороны [Baumgartner et al., 2013]. Показано, что чем больше разви-та дорсомедиальная лобная кора, тем меньше выражена беспристрастность, и в большей сте-пени участники в роли третьей стороны нака-зывают игроков чужой группы по сравнению с игроками своей группы. Также с беспри-страстностью позитивно коррелировал и объ-ем (толщина) анатомических связей между дорсомедиальной лобной корой и теменно-ви-сочно-затылочной областью правого полуша-рия [Baumgartner et al., 2015].

Таким образом, дорсолатеральная лоб-ная кора правого полушария, теменно-ви-сочно-затылочная область и дорсомедиаль-ная префронтальная кора могут выступать

ключевыми регионами в обеспечении про-цесса социального наказания. Нейрональные корреляты поддержания норм также обнару-живались в островковой коре, базальных ган-глиях (прилежащем и хвостатом ядрах), перед-ней и задней частях поясной извилины, хотя эти данные в меньшей степени реплицируются последующими исследованиями.

Фокус современных нейроимиджинговых исследований смещается на оценку систем-ных взаимосвязей между различными областя-ми мозга и их роли в обеспечении механизма социального наказания. В более реалистичной задаче – принятие решений о виновности/не-виновности в гипотетических криминальных сценариях и о вынесении соответствующе-го наказания третьей стороной [Belucci et al., 2016] было связано с активностью двух систем головного мозга: системы ментализации (те-менно-височно-затылочная область и дорсо-медиальная префронтальная кора) – обеспе-чивающей способность представить мысли и действия других людей, опираясь на свой собственный опыт и представления, и систе-мы оценки необходимости социального наказания (латеральная часть лобной коры), регулирую-щей рабочую память, контролирующей ког-нитивную гибкость, переключаемость, внима-ние, планирование, принятие решений и др.

Согласно данным нейровизуализации и анализа эффективной коннективности в си-туации применения социального наказания, дорсомедиальная лобная кора (системы мен-тализации) получает входящие сигналы преи-мущественно от височной области, активация которой, а также сила функциональных свя-зей с дорсолатеральной лобной корой, кор-релирует со строгостью наказания [Belucci et al.., 2016]. Эти данные согласуются с иссле-дованиями пациентов: травмы мозга с лока-лизацией в дорсомедиальной префронтальной коре – приводят к нетипичному поведению при необходимости социального наказания – снижению его интенсивности, что сопрово-ждается недостатком альтруистических пе-реживаний, и худшей работой регуляторных функций (внимания, переключаемости, рабо-чей памяти и др.) [Glass et al., 2016]. Мы при-лагаем иллюстративную схему системы оценки необходимости социального наказания и систе-мы ментализации, вовлеченных в обеспече-ние социального наказания третьей стороной



согласно данным фМРТ и ЭЭГ исследований (см. рис. 1). Предполагается, что эти системы могут взаимодействовать реципрокно – акти-вация системы ментализации сопровождается подавлением системы оценки необходимости социального наказания [Buckholtz et al., 2008].

РАСШИРЕНИЕ ПРЕДСТАВЛЕНИЙ О МЕХАНИЗМАХ СОЦИАЛЬНОГО

НАКАЗАНИЯ С ПОМОЩЬЮ МЕТОДОВ НЕИНВАЗИВНОЙ СТИМУЛЯЦИИ

МОЗГА (ТЭС, ТМС)

Методы неинвазивной стимуляции мозга с помощью магнитного поля – транскрани-альная магнитная стимуляция (ТМС) и транс-краниальная электрическая стимуляция (ТЭС, микрополяризация) – позволяют подавлять (при подавляющей стимуляции) или усили-вать активность нейронов (при возбуждаю-щей) с целью установления каузальной роли

той или иной области мозга в когнитивных процессах при выполнении задачи. Катод-ная стимуляция в ТЭС позволяет временно подавить активность целевой области мозга, в то время как анодная стимуляция – допол-нительно активировать. С помощью методов стимуляции мозга можно продемонстрировать различия в нейробиологических механизмах, вовлеченных в процессы социального наказа-ния в двустороннем взаимодействии и третьей стороной.

Фокус внимания исследователей процес-са социального наказания постепенно сме-щается к попытке понять роль корковых ре-гионов-интеграторов, таких, как медиальная и дорсолатеральная области лобной коры и височно-теменно-затылочная область. Изу-чение региона системы ментализации – меди-альной префронтальной коры – с использова-нием ТЭС показало, что эта область вовлече-на в оценку отклонения от социальной нормы

Система оценки необходимости социального наказания

Дорсальная частьхвостатого ядра

Орбитофронтальная кора Латеральная частьпрефронтальной коры

Система ментализации

Теменно-височно-затылочнаяобласть

Дорсомедиальнаяпрефронтальная кора

А

Б

Рис. 1. Ключевые регионы, активирующиеся в процессе применения социального наказания третьей стороной: А. система оценки необходимости социального наказания. Б. система ментализации. Линии указывают на одно-временную активацию данных областей.Fig. 1. Key regions activated during third-party punishment: А. system of determination of the appropriate social punishment; Б. mentalizing system. Lines indicate simultaneous activation.



справедливости в обоих случаях – когда участ-ник вовлечен во взаимодействие сам или ког-да он является третьей стороной [Civai et al., 2015]. Рис. 2 графически иллюстрирует раз-ницу в поведении, вызванную катодной сти-муляцией медиальной префронтальной коры. В ситуации двустороннего взаимодействия при подавлении активности медиальной префрон-тальной коры с помощью катодной стимуля-ции вероятность отвержения несправедливых предложений уменьшается, в то время как в ситуации наказания третьей стороной пода-вление активности этого участка коры вызвало рост отклонения несправедливых предложе-ний [Civai et al., 2015]. Таким образом, изме-нение роли участника в экономической игре демонстрирует различную степень вовлечен-ности медиального префронтального отдела лобной коры.

С помощью ТМС также была показана роль другого региона системы ментализа-ции – теменно-височно-затылочной области правого полушария – в процессе социального

наказания: ингибирующее воздействие на эту область снижало эффект “парохиализма” (parochialism) – более сильных наказаний по отношению к участникам чужой группы по сравнению с участниками своей группы – за одинаковое отклонение от социальной нор-мы [Baumgartner et al., 2014]. Использование опросников эмоционально-личностной сферы показало, что степень интенсивности парохи-ального наказания модулируется стремлени-ем к “возмездию” (retaliation) – склонностью к пропорциональному возмещению потерь. Предполагается, что процесс ментализации, поддерживаемый активностью дорсомедиаль-ной лобной коры и височно-теменно-заты-лочной области, приводит к разному уровню вовлеченности в ситуацию в непосредствен-ном взаимодействии и наблюдении за взаимо-действием других участников. Сознательное использование ментализации приводит к по-вышению интенсивности переживания соци-альных эмоций при наблюдении за неспра-ведливыми и справедливыми предложениями

Агент

Несправедливоепредложение(финансовый трансфер)

Реципиент

Снижение частотысоциального наказания

Увеличение частотысоциального наказания

Наблюдатель(третья сторона)

А

Б

Рис. 2. Влияние катодной стимуляции в ситуации наказания третьей стороной (А). и наказания в двустороннем взаимодействии (Б). В ситуации применения катодной ТЭС на область медиальной префронтальной коры (А) на-блюдается увеличение частоты социального наказания, (Б) наблюдается снижение частоты социального наказания.Fig. 2. The consequences of cathodal tDCS in third-party punishment (А) and second-party punishment (Б). In case of cathodal tDCS applied to medial prefrontal cortex (А) the frequency of social punishment is raised; (Б) the frequency of social punishment is diminished.



[Gregucci et al., 2012], что отражается в уси-лении тенденции к кооперации в двусторон-нем взаимодействии [см. обзор Krueger et al., 2008]. В ситуации наказания третьей стороной при наблюдении за несправедливыми пред-ложениями участник (третья сторона), ввиду вероятной постановки себя на место другого, применяет наказание как средство упрочения кооперации и изменения поведения индивида, отклоняющегося от социальной нормы.

Однако не меньший интерес со стороны исследователей вызывает установление кау-зальной роли дорсолатеральной лобной коры правого полушария в процессе социального наказания. Показано, что подавляющее воз-действие с помощью ТМС на дорсолатераль-ную лобную кору правого полушария увели-чивает частоту наказаний со стороны третьего лица [Brune et al., 2012]. Однако в ходе развер-нутого статистического анализа с использова-нием данных опросников эмоционально-лич-ностной сферы авторы предположили, что речь идет о механизме эмпатии как триггере принятия решений о необходимости соци-ального наказания. В этом случае дорсолате-ральная лобная кора выступает областью-ин-тегратором эмоциональных сигналов – ответ-ных реакций на несправедливое предложение [Brune et al., 2012]. Усиление активности пра-вой дорсолатеральной лобной коры при помо-щи анодной ТЭС увеличивает частоту приня-тия решений наказать отклонение от социаль-ной нормы в двустороннем взаимодействии, вне зависимости от предшествующего опыта и результатов предыдущих решений [Nihonsugi et al., 2015]. Область дорсолатеральной лобной коры правого полушария, вероятно, также вовлечена в процесс осуществления социаль-ного наказания в двустороннем взаимодей-ствии, что также было показано с применени-ем катодной ТЭС, подавляющей активность нейронов дорсолатеральной лобной коры пра-вого полушария и приводит к уменьшению ко-личества решений наказывать за несправедли-вое распределение материальных благ [Knoch et al., 2008]. С помощью ТЭС также показано, что в условиях отсутствия санкций подавле-ние активности правой латеральной области лобной доли приводит к увеличению финан-совых трансферов – “активному” следованию социальной норме, в то время как в присут-ствии возможности наказания за отклонение от социальной нормы данный тип стимуляции

резко сокращает частоту финансовых транс-феров [Ruff et al., 2013]. Обнаруженный эф-фект сильнее в контексте прямого социально-го взаимодействия по сравнению с ситуаци-ей, когда остальные участники компьютерной игры находились в режиме удаленного досту-па. Из этого следует, что данный регион так-же вовлечен как в добровольное подчинение социальным нормам, так и в принудительное (спровоцированное социальным наказанием).

Ранее мы останавливались на исследова-ниях эффективной коннективности мозговых систем, вовлеченных в процесс социального наказания третьей стороной. Активность си-стемы ментализации (дорсомедиальная лоб-ная кора и височно-теменно-затылочная об-ласть правого полушария) коррелирует с оцен-кой намерений и постановкой себя на место участников взаимодействия, в то время как система оценки необходимости социального наказания (дорсолатеральная префронталь-ная кора) кодирует необходимый уровень на-казания на основе полученной информации от других систем [Krueger et al., 2016]. Согласно данным нейровизуализации, нейронная сеть, вовлеченная в процесс оценки принадлеж-ности участника к своей или чужой группе – дорсомедиальная лобная кора и теменно-ви-сочно-затылочная область, модулирует актив-ность сети принятия решений, включающей орбитофронтальную кору, латеральную пре-фронтальную кору, дорсальную часть хвоста-того ядра, о необходимости вынесения нака-зания в соответствии с социальными нормами. Однако в настоящий момент остается недоста-точно изученной проблема взаимодействия этих сетей в процессе социального наказания, что является актуальной проблемой будущих исследований.

ДАЛЬНЕЙШИЕ ПЕРСПЕКТИВЫ ИССЛЕДОВАНИЯ

НЕЙРОБИОЛОГИЧЕСКИХ КОРРЕЛЯТ СОЦИАЛЬНОГО НАКАЗАНИЯ

Нейроимиджинговые исследования позво-ляют предположить модель взаимодействия системы ментализации и системы оценки не-обходимости социального наказания в про-цессе наказания на основе анализа активации их ключевых регионов височно-теменно-за-тылочной области и дорсолатеральной преф-ронтальной коры, соответственно. Активация



височной теменно-затылочной области со-провождается деактивацией дорсолатераль-ной префронтальной коры в ходе принятия решения (фазы предрешения) и сменяется ак-тивацией дорсолатеральной префронтальной коры, когда решение о социальном наказании принято и готово к исполнению [Buckholtz et al., 2008]. Активность височно-теменно-за-тылочной области, вероятно, является ней-рональным коррелятом оценки переживаний (перспективы) другого игрока – вовлечения эмпатического ответа по отношению к участ-никам взаимодействия, в то время как ак-тивность дорсолатеральной префронтальной коры соотносится с оценкой “виновности” и необходимости понести наказание за откло-нение от социальной нормы. Таким образом, предполагается, что процесс социального на-казания поддерживается антагонистической работой этих систем.

Остается неясным, вовлечены ли эти реги-оны в непосредственное взаимодействие друг с другом в процессе принятия решения о на-казании третьей стороной, что требует даль-нейшего исследования с помощью методик неинвазивной стимуляции мозга с целью из-учения взаимодействия этих мозговых регио-нов. Проведенный анализ литературы позво-ляет предположить, что подавление работы областей, вовлеченных в систему оценки со-циального наказания третьей стороной, при-ведет к увеличению частоты наказания за счет работы системы ментализации, в то время как подавление системы ментализации приведет к уменьшению частоты социального наказа-ния. Выдвинутая гипотеза требует экспери-ментального подтверждения с помощью мето-дов неинвазивной стимуляции мозга.

ЗАКЛЮЧЕНИЕ

Проведенный анализ исследований позво-ляет заключить, что в процесс осуществле-ния социального наказания третьей стороной вовлечены две ключевые системы головно-го мозга – система ментализации и системы оценки необходимости социального наказания. Регионы-хабы информации этих систем лока-лизованы в дорсомедиальной и теменно-ви-сочно-затылочной коре, и дорсолатеральной лобной коре, соответственно. Фокусом вни-мания в настоящий момент становится дока-зательство каузальной роли вышеописанных

отделов мозга в процессе социального нака-зания третьей стороной с помощью методов неинвазивной стимуляции мозга. Однако вза-имодействие этих нейросетей через регио-ны-интеграторы (дорсолатеральную лобную кору и теменно-височно-затылочную область) при принятии решения о наказании наруши-телей социальных норм практически не ис-следовалось с помощью современных методов когнитивной нейробиологии, таких как ТЭС и ЭЭГ. Перспективным представляется про-ведение исследований, направленных на вы-явления механизмов и принципов взаимодей-ствия между дорсолатеральной лобной корой и теменно-височно-затылочной областями при поддержке испытуемыми нормативного поведения в группе.

Исследование финансировалось в рамках государственной поддержки ведущих универ-ситетов Российской Федерации “5–100”.

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Keywords: social norms, social punishment, third-party punishment, dorsolateral prefrontal cortex, dorsome-dial prefrontal cortex, temporo-parietal junction, transcranial magnetic stimulation (TMS), transcranial direct current stimulation, functional magnetic resonance imaging (fMRI).

Modern neuroimaging studies begin to explore neurobiological mechanisms of social norms enforcement. Several regions of frontal lobes and temporo-parieto-occipital cortex play a key role in decision making of social punishment of fairness’ norm violation. The cutting–edge methods of brain stimulation allow to change frequency and intensity of social punishment in different economic tasks (games). The analysis of modern studies show that brain mechanisms of decision making to punish non–cooperative individual requires further investigation with brain stimulation methods to differentiate the role of frontal and temporo-parieto-occipital regions and clarify its interaction.

1 Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russian Federation.

2 Laboratory for Experimental and Behavioral Economics, National Research University Higher School of Economics, Moscow, Russian Federation.

3 Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russian Federation.

e-mail: [email protected], 2 [email protected], [email protected]

O. Zinchenko1, A. Belyanin2, V. Klucharev3

Neurobiological Mechanisms of Fairness-Related Social Norm Enforcement: a Review of Interdisciplinary Studies

Attachment C. Article “Commentary: The Emerging Neuroscience of Third-Party

Punishment».

More than a decade of neuroimaging research has established that several distinct

brain networks are consistently recruited during social punishment, i.e., the

propensity of cooperative individuals to spend some of their resources penalizing

norm violators. Studies in behavioral economics have shown that social

punishment can explain why genetically unrelated individuals are often able to

maintain high levels of socially beneficial cooperation. Recently, Krueger and

Hoffman (2016) reviewed and summarized the roles of three brain networks that

are activated during TPP: the salience network (SN), the default mode network

(DMN), and the central executive network (CEN). First, they suggested that the SN

(the insula, amygdala, and dorsal anterior cingulate) detects and generates an

aversive experience that initiates TPP. Second, the authors argued that the DMN

(the medial prefrontal cortex, posterior cingulate cortex, and TPJ) integrates the

perceived harm and inference of intentions into an assessment of blame. Finally,

they proposed that the CEN (the dorsolateral prefrontal cortex and posterior

parietal cortex) converts the blame signal into a specific punishment decision.

These recent findings raise intriguing and testable questions for future research,

e.g., in the use non-invasive brain stimulation to further verify fMRI findings. We

speculate that an enhancement of TPJ activity, along with the simultaneous

suppression of DLPFC activity, should enhance an antagonistic CEN/DMN

interaction and lead to increased TPP. The aforementioned behavioral effect should

be associated with changes in the functional connectivity between the TPJ and

DLPFC. A combined non-invasive brain stimulation-neuroimaging approach could

further uncover the complex intrinsic network dynamics in the brain, which

underlies TPP.

GENERAL COMMENTARYpublished: 24 October 2017

doi: 10.3389/fnhum.2017.00512

Frontiers in Human Neuroscience | www.frontiersin.org 1 October 2017 | Volume 11 | Article 512

Edited by:

Xiaolin Zhou,

Peking University, China

Reviewed by:

Hongbo Yu,

University of Oxford, United Kingdom

Matthew Ginther,

Court of Federal Claims, United States

*Correspondence:

Oksana Zinchenko

[email protected]

Received: 10 July 2017

Accepted: 09 October 2017

Published: 24 October 2017

Citation:

Zinchenko O and Klucharev V (2017)

Commentary: The Emerging

Neuroscience of Third-Party

Punishment.

Front. Hum. Neurosci. 11:512.

doi: 10.3389/fnhum.2017.00512

Commentary: The EmergingNeuroscience of Third-PartyPunishment

Oksana Zinchenko 1* and Vasily Klucharev 1, 2

1Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia,2Department of Psychology, National Research University Higher School of Economics, Moscow, Russia

Keywords: third-party punishment, default mode network, central-executive network, transcranial direct current

stimulation, temporoparietal junction, dorsolateral prefrontal cortex, functional connectivity, social norms

A commentary on

The Emerging Neuroscience of Third-Party Punishment

by Krueger, F., and Hoffman, M. (2016). Trends Neurosci. 39, 499–501. doi: 10.1016/j.tins.2016.06.004

More than a decade of neuroimaging research has established that several distinct brain networksare consistently recruited during social punishment, i.e., the propensity of cooperative individualsto spend some of their resources penalizing norm violators. Studies in behavioral economics haveshown that social punishment can explain why genetically unrelated individuals are often ableto maintain high levels of socially beneficial cooperation (Fehr and Gächter, 2002; de Quervainet al., 2004; Gureck et al., 2006). In particular, social norms can be reinforced by parties thatare directly affected by norm violators (“second parties” punishment—SPP) and parties that arefinancially unaffected (“third parties” —TPP) (Fehr and Fischbacher, 2004). Importantly, normviolations often do not hurt other people directly. Thus, third-party sanctions are particularlyeffective at reinforcing group norms that regulate human behavior (Bendor and Swistak, 2001; Fehrand Fischbacher, 2004).

Pioneering behavioral studies have showed that strong emotions trigger the willingness topunish norm violators (Hirshleifer, 1987; Frank, 1988; Fehr and Gächter, 2002); in particular, TPPis motivated by both empathy toward the victim and anger toward the norm violator (Batson et al.,2007; Pedersen, 2012). Recently, neuroimaging studies have demonstrated a critical role of executive(the dorsolateral prefrontal cortex, DLPFC) and mentalizing (the temporoparietal junction, TPJ)brain regions in TPP (Baumgartner et al., 2012; Bellucci et al., 2016). Thus, neuroscience studiescould help to further develop psychological theories of TPP by clarifying the specific neurocognitivemechanisms triggering punishment decisions in various social contexts.

Recently, Krueger and Hoffman (2016) reviewed and summarized the roles of three brainnetworks that are activated during TPP: the salience network (SN), the default mode network(DMN), and the central executive network (CEN). First, they suggested that the SN (the insula,amygdala, and dorsal anterior cingulate) detects and generates an aversive experience that initiatesTPP. Second, the authors argued that the DMN (the medial prefrontal cortex, posterior cingulatecortex, and TPJ) integrates the perceived harm and inference of intentions into an assessment ofblame. Finally, they proposed that the CEN (the dorsolateral prefrontal cortex and posterior parietalcortex) converts the blame signal into a specific punishment decision.

Interestingly, these three networks partially overlap with those underlying the detection of normviolations in other social contexts. There is a growing cognitive neuroscience literature on a neuralmechanism that detects when individual behavior or beliefs differ from those of others (for reviews,

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Zinchenko and Klucharev Commentary: The Emerging Neuroscience of Third-Party Punishment

see Izuma, 2013; Klucharev and Shestakova, 2015). A numberof neuroimaging studies have demonstrated that the activityof the SN, DMN, and CEN encodes perceived deviationsfrom group norms (Klucharev et al., 2009; Berns et al., 2010;Campbell-Meiklejohn et al., 2010; Izuma and Adolphs, 2013). Inparticular, the insula, dorsal anterior cingulate, medial prefrontalcortex, posterior cingulate cortex, and DLPFC have all beenimplicated in norm monitoring. Interestingly, many of thesestudies also reported norm-monitoring activity in the ventralstriatum (Klucharev et al., 2009; Crockett et al., 2013; Xiang et al.,2013), which is a key region implicated in reward valuation.Despite the fact that the ventral striatum was not mentioned byKrueger and Hoffman (2016), recent studies have also implicatedthis region in TPP (Strobel et al., 2011; Hu et al., 2015), whichfurther indicates that these two lines of research (detection ofnorm violations and TPP) share common neural mechanismsand should be further integrated.

However, amygdala activity was reported only in SPP andTPP studies (Buckholtz et al., 2008; Yu et al., 2015; Gintheret al., 2016). This can be explained by the financial losses andharms associated with this paradigm. TPJ activity also seemsto be specific to the context of TPP (Baumgartner et al., 2012,2014). A recent quantitative review suggested that the TPJconsists of functionally and spatially distinct neuroanatomicalsub-regions specializing in different cognitive processes (Schurzet al., 2017). It has been hypothesized that the TPJ supports theprocessing of social contexts that require the representation of(a) the social context (stimuli) and (b) the context provided byattention, memory, and language (Carter and Huettel, 2013).These convergent processes constitute a theory of mind. Thisability to make inferences about other people’s mental states,which is associated with the TPJ, is critical to the ability to blamethem for violations of complex context-dependent social norms.Thus, to uncover the neural mechanisms of TPP, it is essential toclarify the neurocomputational mechanism that allows the TPJ(as a part of the DMN) to link norm-violation detection (SN) tospecific punishments (CEN).

Interestingly, TPJ activity during TPP is paralleled by an initialdeactivation of the DLPFC (Buckholtz et al., 2008). This indicatesfunctionally opposed neural activity in these two regions. TheDLPFC demonstrates a biphasic neural activity—following initialdeactivation, it increases activity—when subjects make thefinal decision to punish “based on assessed responsibility andblameworthiness” (Buckholtz et al., 2008, p. 935). Thus, it isimportant to explain the “antagonistic” relationship betweenthe DMN (TPJ) and CEN (DLPFC). Many recent studies haveevaluated functional and effective connectivity during SPP (Yuet al., 2015) and TPP (Treadway et al., 2014; Bellucci et al., 2016).They demonstrated that the lateral regions of the prefrontalcortex receive an input from the TPJ during SPP (Yu et al.,

2015), while the dorsomedial prefrontal cortex plays the role ofa hub, coordinating DLPFC and TPJ activity during the decisionstage of TPP (Bellucci et al., 2016). Neuroimaging studies havedemonstrated that the temporoparietal-medial-prefrontal circuitsuppresses the amygdala during evaluations of unintentionalharm (Treadway et al., 2014; Yu et al., 2015) in both SPP andTPP or boosts amygdala activity and strengthens its connectivity

with the lateral prefrontal regions (during TPP) when a harmis intentional (Treadway et al., 2014). This suggests that thetemporoparietal-medial-prefrontal circuit gates the emotionalresponses to norm violations and regulates subsequent reactivepunishment.

These recent findings raise intriguing and testable questionsfor future research, e.g., in the use non-invasive brain stimulationto further verify fMRI findings. There is evidence suggestingthat transcranial current stimulation could effectively modulatewithin- and between-network interactions. For example,transcranial alternating current stimulation induced oscillatorydesynchronization between the medial frontal and parietalcortices and, therefore, affected value-based decisions but notclosely matched perceptual decisions (Polanía et al., 2015).Simultaneous anodal transcranial direct current stimulationof the DLPFC, together with cathodal stimulation of thesupraorbital region, led to changes in the default mode networkand frontal-parietal networks (Keeser et al., 2011) and increasedsynchrony within the focused attention network (Peña-Gómezet al., 2012). According to Buckholtz et al. (2008), the CENexerts an inhibitory influence over the DMN in order to programdecisions about an appropriate punishment. Thus, a personcould use a simultaneous application of transcranial direct oralternating current stimulation to the TPJ and DLPFC in orderto modulate an antagonistic CEN/DMN interaction during TPP.We speculate that an enhancement of TPJ activity, along with thesimultaneous suppression of DLPFC activity, should enhancean antagonistic CEN/DMN interaction and lead to increasedTPP. The aforementioned behavioral effect should be associatedwith changes in the functional connectivity between the TPJand DLPFC. A combined non-invasive brain stimulation-neuroimaging approach could further uncover the complexintrinsic network dynamics in the brain, which underlies TPP.

AUTHOR CONTRIBUTIONS

All authors listed have made substantial, direct and intellectualcontribution to the work, and approved it for publication.

FUNDING

The study has been funded by the Russian Academic ExcellenceProject “5-100.”

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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.

Copyright © 2017 Zinchenko and Klucharev. 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

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or reproduction is permitted which does not comply with these terms.


https://doi.org/10.1093/scan/nst023

https://doi.org/10.1080/17470919.2016.1153518

https://doi.org/10.1086/321298



https://doi.org/10.1016/j.cub.2010.04.055


https://doi.org/10.1523/JNEUROSCI.2761-12.2013


https://doi.org/10.1016/S1090-5138(04)00005-4

https://doi.org/10.1038/415137a




https://doi.org/10.1016/j.conb.2013.03.009




https://doi.org/10.1016/B978-0-12-397025-1.00189-5


https://doi.org/10.1016/j.brs.2011.08.006

http://scholarlyrepository.miami.edu/oa_theses/377

http://scholarlyrepository.miami.edu/oa_theses/377

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Attachment D. Article “The role of the temporoparietal and prefrontal cortices in

third-party punishment: a tDCS study”.

Recent studies have demonstrated that the right dorsolateral prefrontal cortex

(rDLPFC) and the right temporoparietal junction (rTPJ) are causally involved in

social norm compliance. Here, we tested the hypothesis that a third party’s

decision to punish norm violations depends on the activity of the entire

rDLPFC/rTPJ network. We used transcranial direct current stimulation (tDCS) to

independently or jointly modulate rTPJ and rDLPFC activity during the third-party

dictator game. We found a significant effect of anodal tDCS of the rTPJ, which

decreased the third-party punishment of moderately unfair splits. Joint stimulation

of the rTPJ (by anodal tDCS) and rDLPFC (by cathodal tDCS) produced a

marginal effect on third-party punishment.

Zinchenko, O., Belianin, A., Klucharev, V. The role of the temporoparietal and prefrontal cortices in

third-party punishment: a tDCS study // Psychology. Journal of the Higher School of Economics.

2019. (in print).

The role of the temporoparietal and prefrontal cortices in third-party

punishment: a tDCS study

tDCS study of social punishment

Zinchenko Oksana, junior research fellow, Institute of Cognitive Neuroscience, Centre

for Cognition and Decision Making, National Research University Higher School of

Economics, National Research University Higher School of Economics, 20

Myasnitskaya Ulitsa, Moscow, 109316, Russia, [email protected].

Research interests: cooperation, social norms, social punishment.

Belianin Alexis, PhD, National Research University Higher School of Economics;

ICEF and Laboratory for Experimental and Behavioral Economics, [email protected]

Klucharev Vasily, Cand.of Science, professor, Institute of Cognitive Neuroscience,

Centre for Cognition and Decision Making, National Research University Higher

School of Economics, [email protected]

Abstract

Recent studies have demonstrated that the right dorsolateral prefrontal cortex

(rDLPFC) and the right temporoparietal junction (rTPJ) are causally involved in social

norm compliance. Here, we tested the hypothesis that a third party’s decision to punish

norm violations depends on the activity of the entire rDLPFC/rTPJ network. We used

transcranial direct current stimulation (tDCS) to independently or jointly modulate

rTPJ and rDLPFC activity during the third-party dictator game. We found a significant

effect of anodal tDCS of the rTPJ, which decreased the third-party punishment of



2

moderately unfair splits. Joint stimulation of the rTPJ (by anodal tDCS) and rDLPFC

(by cathodal tDCS) produced a marginal effect on third-party punishment.

Keywords: dorsolateral prefrontal cortex, transcranial direct current stimulation,

temporoparietal junction, third-party punishment, social norms.

Introduction

Human societies crucially depend on social norms that often regulate appropriate

actions in various situations and can be reinforced by “second” parties that are directly

affected by the norm violators and “third” parties that are not directly affected (Fehr

and Fischbacher, 2004). Since norm violations often do not directly hurt other people,

third-party sanctions are especially critical in reinforcing social norms (Bendor and

Swistak, 2001; Fehr and Fischbacher, 2004). More than a decade of neuroimaging

research has established that several distinct brain networks are consistently recruited

during social punishment; that is, cooperative individuals’ propensity to spend part of

their resources to penalize norm violators (Krueger and Hoffman, 2016). Here, we

further investigate the neural underpinnings of third parties’ punishment of a fairness

norm violation.

The social norm of fair distribution implies a rejection of the distribution of goods that

violates the equality principle (Elster, 1989; Kahneman et al., 1986). The norm of

fairness is often investigated using economic games, allowing different distributions of

financial transfers between players. Importantly, behavioral studies have robustly

demonstrated that many players (including third parties) in economic games not only

prefer fair distributions to unequal ones (Guth et al., 1982; Engel, 2010), but they also

tend to spend personal resources to punish unfair distributions (norm violations) on

their own accord (Fehr and Fischbacher, 2004; Ruff et al., 2013).

3

Functional magnetic resonance imaging (fMRI) and brain stimulation studies have

suggested that the right dorsolateral prefrontal cortex (rDLPFC) controls selfish

impulses (Strang et al., 2015) and responds to inequity (Fliessbach et al., 2012), where

individual differences in sanction-induced norm compliance correlate with rDLPFC

activity (Spitzer et al., 2007). Brüne and colleagues (2012) showed that inhibitory

rTMS of the rDLPFC increased third-party punishment during the dictator game,

which suggests that the rDLPFC associated third parties’ emotional responses to

observed unfairness of dictators. In contrast, rTMS of the rDLPFC resulted in

decreased third-party punishment when participants where shown criminal scenarios

ranging from simple theft to murder (Buckholtz et al., 2015). Inconsistencies in effects

of rTMS on rDLPFC require further work to clarify the role of the rDLPFC on third-

party punishment. Like Brüne and colleagues (2012), the current project utilized the

third-party dictator game but in contrast to their experiment manipulations, we aimed

to apply excitatory anodal tDCS on the rDLPFC, and predict that the opposed effects

would ensue and therefore decrease third-party punishment.

Another neuroanatomical structure that has been found to play a critical role in third

parties’ punishment decisions is the right temporoparietal junction (rTPJ)

(Baumgartner et al., 2012; Baumgartner et al., 2014). Importantly, the ability to make

inferences about other people’s mental states is associated with TPJ activation, that is

crucial for the ability to blame others for violations of complex context-dependent

social norms. Increased rTPJ activity has been associated with reduced punishment of

defecting in-group members during the prisoner’s dilemma game (Baumgartner et al.,

2012). Here, we hypothesized that excitatory anodal tDCS of the rTPJ should reduce

third-party punishment during the third-party dictator game.

Recently, Krueger and Hoffman (2016) argued that during third-party punishment, the

TPJ integrates the inference of intentions into an assessment of blame. The

DLPFCconverts the blame signal into a specific punishment decision. Thus, the

4

DLPFC plays an executive role, while the TPJ drives processes associated with blame

and initiates punishment. Although these mechanistic actions are neurobiologically

plausible, the exact interaction between the rTPJ and rDLPFC for the function of third-

party punishment remain unclear, because it is unknown whether the rDLPFC entrains

the rTPJ or that rTPJ activates independently (for a detailed discussion, see Zinchenko

and Klucharev, 2017). It has also been shown that, TPJ activity during third-party

punishment is paralleled by an initial deactivation of the DLPFC which indicates

functionally opposed neural activity in these two regions (Buckholtz et al., 2008). The

DLPFC demonstrates biphasic neural activity—after the initial deactivation, it later

increases in activity—when subjects make the final decision to punish “based on

assessed responsibility and blameworthiness” (Buckholtz et al., 2008, p. 935). Overall,

Buckholtz and colleagues (2008) suggested that this pattern of reciprocal activation

could reflect a crucial mentalizing process before an appropriate punishment is

determined and a decision is made. Therefore, it would be important to further study

the functional interaction of the rTPJ and rDLPFC during third-party punishment

through the use of joint stimulation of the rDLPFC and rTPJ in a reciprocal manner.

In the current study, we further investigated the role of the DLPFC and TPJ in third-

party punishment with an overarching aim of understanding neural resource activation

plays a role in social norm reinforcement. Our motivation was based on previous

studies (Baumgartner et al., 2012; Brüne et al., 2012) and sought to replicate their

results, but by uniquely testing the opposed effect of independent excitatory anodal

tDCS of the rTPJ or rDLPFC and predict that decreased third-party punishment of

unfair splits would be resultant (Hypothesis I, Study 1) compared to sham stimulation.

On the other hand, based on the seminal fMRI study (Buckholtz et al., 2008), we

hypothesized that a joint anodal tDCS of the rTPJ and cathodal tDCS of the rDLPFC

of third parties might make third-party punishment of unfair splits stronger comparing

to sham stimulation (Hypothesis II, Study 2). Therefore, in Study 1, we stimulated the

5

rDLPFC and rTPJ independently, while in Study 2, we jointly stimulated the rDLPFC

and rTPJ in a reciprocal, antagonistic manner. Importantly, according to the theory of

inequity aversion, individuals dislike outcomes that are perceived as inequitable (Fehr

and Schmidt, 1999). Therefore, we expected to find the strongest effect of tDCS on

third-party punishment in trials with a payoff structure, where sanctioners (third

parties) were able to establish the equality between all players (Hypothesis III).

Overall, we used tDCS to further investigate the role of the rDLPFC and rTPJ in third

parties’ punishment of a fairness norm violation. According to our hypotheses, an

independent or joint stimulation of the rDLPFC and rTPJ could lead to different

behavioral effects.

Methods

Subjects

Twenty-three healthy, right-handed subjects (mean age = 21.5 years, range = 18–27

years, 7 males) participated in Study 1. Twenty-one healthy, right-handed subjects

(mean age = 22.79 years, range = 18–27 years, 10 males) participated in Study 2. Each

subject participated in only one of the two studies. All subjects gave written informed

consent to participate in the study. Subjects (n = 5) who did not punish at least once or

demonstrated only antisocial punishment in fair trials (20∶20 split condition) were

excluded from the analysis, resulting in 20 (n = 20, Study 1) and 19 (n = 19, Study 2)

subjects respectively. The studies conformed to the Declaration of Helsinki, and the

experimental protocol was approved by the university ethics committee. The sample

size was based on the previous study of Brüne and colleagues (2012), which included

20 subjects.

Procedure

6

Each subject participated in three sessions of the dictator game that were separated by

7±2 days. Next, tDCS was applied for 15 minutes. The third-party dictator game lasted

approximately 20–25 minutes. A structured debriefing after each session revealed that

the subjects believed the instructions and their behavior were comparable to those in

“real-life” situations.

Study design

Dictator game with third-party punishment

The subjects participated in multiple rounds of a preprogrammed dictator game as

sanctioners (third parties). In the instructions, the dictator distributed 40 experimental

monetary units (MUs; 1 MU ≈ 0.26 Russian rubles, or 0.004 U.S. dollars) between

herself and the recipient.

Figure 1 demonstrates the details of the trial structure. To make the game more social,

in each trial the participants first observed pictures of two individuals (a dictator and a

recipient). The genders of the dictators and recipients were counterbalanced across

subjects. Participants (sanctioners) were able to punish dictators using a budget of 20

MUs. The budget was renewed for each round, and all points not invested in

punishment were converted into a monetary payoff and paid to the participant after the

experiment. To avoid demand effects, the instructions described the task using neutral

language, such as “You will be able to deduct the first player’s earnings.” Sanctioners

could use 0–18 MUs out of their 20 MUs budget to punish the dictator, and were able

to use an even number of MUs, such as 2, 4, 6, etc. These MUs were multiplied by two

and deducted from the dictator’s budget. For example, if the sanctioner used 10 MUs

to punish the dictator, 20 MUs (2 × 10 MUs) were deducted from dictator’s budget.

7

Figure 1. Trial structure of the dictator game with third-party punishment. At the

beginning of each trial, a dictator (Player 1) received 40 monetary units (MUs; Stage

I) to choose whether to give some MUs to the recipient (Player 2; Stage II). Next, the

subject (Player 3, sanctioner) received 20 MUs (Stage III) to choose how much (if

any) to spend on punishing the dictator (Stage IV), in which every MU spent by the

sanctioner reduced the dictator’s payoff by 2 MUs.

The photos of dictators and recipients were preselected from 300 photos of young

adults. The images were retrieved from the Internet from open access sources, such as

popular social media without being logged in. For ethical reasons, it was carefully

ensured that the photos stayed anonymous—no personal information was stored.

Similar to the study of Brüne and colleagues (2012), we pretested stimuli: photos were

evaluated for attractiveness, trustworthiness, and cooperativeness on a seven-point

Likert-type scale by 17 subjects (10 females) prior to the study. We calculated the

8

average rating of each measure (attractiveness, trustworthiness, and cooperativeness)

for each photo. Similar to the previous rTMS study (Brune et al. 2012), only photos

with a mean average rating between 2.5 and 5.5 points were used in the current study.

If the average rating for at least one measure was higher or lower than this range, the

photo was excluded and never used in the study.

The following information was emphasized to the participants: (1) their partners were

real people participating in the game at the same time, located in different rooms; (2)

the partners varied in each round; and (3) both the participants and their partners

would be paid real money, as all points that had not been invested during the game

would be paid out at the end of the study. Although the subjects believed that they

were playing an “online” game, they were, in fact, playing with prerecorded human

players (dictators and recipients) who had played the same game before against other

human opponents (see Brüne et al., 2012, for the same approach). Therefore, each

session consisted of 48 trials per split condition, with shares of 0:40 (n = 2), 15:25 (n =

1), 20:20 (n = 26), 25:15 (n = 4); 30:10 (n = 6), 35:5 (n = 3) and 40:0 (n = 6). The trials

were randomized in each session. All the subjects were native Russians recruited via

email. The number of trials in each split condition was defined based on a behavioral

pilot study (n = 178).

tDCS

The tDCS is a noninvasive brain stimulation technique that can modulate activity in

specific regions of the cortex (Nitsche and Paulus 2001, Nitsche et al. 2003; Paulus

2011). During tDCS, weak electrical currents are applied to the scalp surface from the

anode to cathode: anodal tDCS typically depolarizes (excites) and cathodal tDCS

typically hyperpolarizes (inhibits) neurons. In the current study, a direct current was

induced using two saline-soaked surface sponge electrodes (active electrode area = 25

9

cm2) and delivered by a battery-driven, constant current StarStim 8 stimulator

(Neuroelectrics). The stimulation intensity was set at 1.5 mA and lasted 15 minutes,

with ramping up and ramping down time equal to 30 seconds. Impedances were kept

below 10 kOhm.

After 15 minutes of tDCS, participants immediately participated in the dictator game

as a third-party. Importantly, several methodological studies demonstrated that even

tDCS (1 mA) delivered for a short time (5–13 minutes) induced long-lasting changes

of cerebral excitability: up to 90 minutes after the end of stimulation (Nitsche and

Paulus, 2001) for anodal tDCS and up to one hour for the cathodal tDCS (Nitsche et

al., 2003). Therefore, a 15-minute tDCS in our study should modulate cortical

excitability during the entire dictator game.

The stimulation point for the rDLPFC was defined using the MNI coordinates reported

by Spitzer et al. (2007) for rDLPFC activity (x = 52, y = 28, z = 14), which showed

both stronger fMRI activation for punishment condition minus baseline condition as

well as a correlation of brain activity with the transfer difference between punishment

and baseline conditions (see Ruff et al., 2013 for a similar approach). To further clarify

the optimal electrode position, we simulated tDCS using SimNIBS software, version

2.1.1. (see Figure 2; www.simnibs.de/start; Thielscher, Antunes and Saturnino, 2015).

10

Figure 2. Simulations of electric current distributions (E-field, V/m) for different

tDCS protocols.

A: Simulations of the tDCS protocols used in the current study (F8 electrode for

rDLPFC stimulation, CP6 electrode for rTPJ stimulation), B: Simulations of the

alternative tDCS protocol, where F8 electrode is replaced with F4 (F4 electrode for

rDLPFC stimulation, CP6 electrode for rTPJ stimulation).

Overall, the results of the simulation indicated that the F8 electrode position was an

adequate target for the rDLPFC stimulation. To stimulate the rTPJ, the target electrode

was located over CP6 region (Santiesteban et al., 2012; Sellaro et al., 2015). For the

sham stimulation, the intensity and position of the electrodes were the same as during a

real stimulation, but the stimulator was only turned on for 30 seconds. The positions of

the electrodes for the sham stimulation in Study 1 and Study 2 were randomized and

counterbalanced, as was the order of the stimulation sessions (see Figure 3).

11

Figure 3. Transcranial direct current stimulation (tDCS) set-ups for Study 1 and

Study 2. Study 1: Condition 1.1—anodal tDCS of the rDLPFC; Condition 1.2—

anodal tDCS of the rTPJ; Condition 1.3—sham condition. In all conditions of Study 1,

the cathodal electrode was placed over vertex. Study 2: Condition 2.1—simultaneous

anodal tDCS of the rDLPFC and cathodal tDCS of the rTPJ; Condition 2.2—

simultaneous cathodal tDCS of the rDLPFC and anodal tDCS of the rTPJ; Condition

2.3—sham.

In Study 1, we applied the anodal tDCS of the rDLPFC and rTPJ independently, as

follows: (1) rDLPFCa condition (Condition 1.1)—anodal tDCS of the rDLPFC; (2)

12

rTPJa condition (Condition 1.2)—anodal tDCS of the rTPJ; and (3) sham condition

(Condition 1.3). In all conditions of Study 1, the cathodal electrode was placed over

the vertex (Cz electrode position). We expected (Hypothesis I) to decrease third-party

punishment in Conditions 1.1 and 1.2 as compared with the control (Condition 1.3).

In Study 2, we simultaneously modulated rDLPFC and rTPJ activity, as follows: (1)

rDLPFCa/rTPJc condition (Condition 2.1) — simultaneous anodal tDCS of the

rDLPFC and cathodal tDCS of the rTPJ; (2) rDLPFCc/rTPJa condition (Condition 2.2)

— simultaneous cathodal tDCS of the rDLPFC and anodal tDCS of the rTPJ, and (3)

sham condition (Condition 2.3), which was the same as in Study 1. Following the

findings of Buckholtz and colleagues (2008), which demonstrated a reciprocal

activation of the rDLPFC and rTPJ, we expected (Hypothesis II) to increase third-party

punishment in Condition 2.2 as compared with Conditions 1.2 and 2.3.

There is evidence suggesting that tDCS could effectively modulate within-network and

between-network interactions. For example, the simultaneous anodal tDCS of the

DLPFC, together with cathodal tDCS of the supraorbital region, led to changes in the

default mode network (Keeser et al., 2011; Peña-Gómez et al., 2012). Here, we used a

simultaneous application of tDCS to the rTPJ and rDLPFC to modulate their

interaction during third-party punishment. Thus, we developed a mixed design that

allows exogenous modulation of between-network interaction.

Statistical analysis

For each experimental condition, we calculated a sum of MUs, which were used to

punish the dictator, to estimate the punishment level, or total investment in punishment

(see Brune et al., 2012 for the same approach). According to the payoff matrix of the

dictator game, our participants would experience advantageous inequity (when they

receive more than others) or disadvantageous inequity (when they receive less than

others) after all splits except for the 20:20 split. Importantly, only when the dictator

13

chose a 30:10 split were participants able to restore equality by spending 10 of their

own MUs on punishing the dictator. Interestingly, only in the case where participants

observed moderately unfair 30:10 splits, the conflict between material (selfish) and

moral (prosocial) costs was minimal, since participants either did not punish or

punished extremely little if the material costs were high. Therefore, we could expect

that the strongest effect of tDCS would be observed in the 30:10 split condition, when

participants were able to restore equality and protect their own material interests

(Hypothesis III).

To test Hypothesis III, we aggregated split conditions of the game into three trial

types: FS-trials—fair splits (20:20 and 25:15 splits), US_equal-trials—unfair splits

(30:10 splits), where third-party punishment was able to establish equality between all

players, and US_inequal-trials (35:5 and 40:0 splits), where participants were unable

to establish such equality. Due to a very low number of observations, 0:40, 15:25 split

conditions were not included in the main analysis. However, Table 1 provides

descriptive statistics for all split conditions.

14

Table 1. The mean and standard deviations of punishment level in Study 1 and Study 2.

Condition/

Types of splits

0:40 +

15:25

(not

included

into main

analysis)

20:20+25:15

[FS-trials]

30:10

[US_equal-

trials]

35:5+40:0

[US_inequal-

trials]

Study 1

Condition 1.1.

Mean 0.5 22 48.60 118.30

SD 1.43 10.05 19.22 45.17

Condition 1.2.

Mean 2.7 20.40 46.20 112

SD 6.53 10.59 17.96 43.61

Condition 1.3.

Mean 1.5 21.30 49.50 119.30

SD 3.55 10.02 16.78 39.70

Study 2

Condition 2.1.

Mean 0.21 13.79 37.05 112.53

SD 0.92 11.25 20.56 33.65

15

Condition 2.2.

Mean 1.16 13.37 40.52 109.37

SD 4.18 10.67 19.43 32.19

Condition 2.3.

Mean 2.11 11.26 34.21 111.37

SD 8.23 8.92 20.36 28.86

Since the punishment levels were not normally distributed, behavioral results were

analyzed using the Wilcoxon signed-rank test and the Friedman test, and p-values <.05

were considered significant. To correct for multiple comparisons, the false discovery

rate (FDR) correction at 10% level using the Benjamini-Hochberg procedure (1995)

was computed to compare the effects of three types of stimulation (Conditions 1.1, 1.2,

and 1.3) and three types of splits (FS-trials, US_equal-trials, and US_inequal-trials) in

Study 1. To compute the FDR correction, p-values obtained in the statistical analysis

were ranked from the lowest to the highest and then compared to FDR-corrected alpha

levels (Benjamini-Hochberg critical value). Only p-values not exceeding FDR-

corrected alpha levels were considered significant. To control individual differences in

third-party punishment, we normalized punishment levels: for each trial type, the

punishment level was divided by the punishment level in the sham condition and

multiplied by 100%. Between-group differences were further evaluated using the

Kruskal–Wallis H test, which was applied to normalized data.

Results

Study 1: Independent modulation of the rDLPFC and rTPJ

16

In total, in the sham condition (Condition 1.3), participants spent only 1.5 (±3.6) MUs

for the punishment of generous 0:40 and 15:25 splits, 21.3 (±10.0) MUs—for the

punishment of fair FS-trials, while for unfair US_equal-trials they used 49.5 (±16.8)

MUs and for US_inequal-trials, 119.3 (±39.7) MUs. Due to a very low number of

observations, 0:40, 15:25 split conditions were not included into further analyses.

The lowered punishment level of FS-trials compared with US_equal-trials and

US_inequal-trials was observed in all experimental tDCS conditions. Table 1

represents the mean and standard deviations of punishment level of third-party

punishment for each. As expected, the participants punished unfair splits much more

strongly than they did fair splits.

rDLPFCa condition. We observed a trend of a stronger third-party punishment in the

rDLPFCa condition (Condition 1.1) than in the rTPJa condition (Condition 1.2): Z = -

2.177; p = 0.029, which did not survive FDR correction (see Table 2 for FDR-

corrected alpha levels).

Table 2. The false discovery rate computation (Study 1).

Study 1

Condition

p-values obtained

in the statistical

analysis Rank

FDR-corrected

alpha levels

(Benjamini-

Hochberg critical

values)

Condition 1.2–

Condition 1.3

(30:30)

0.006*

1 0.011

17

Condition 1.1–

Condition 1.2

(35:5+40:0)

0.029

2 0.022

Condition 1.2–

Condition 1.3

(35:5+40:0)

0.045

3 0.033

Condition 1.1–

Condition 1.2

(20:20+25:15)

0.347

4 0.044

Condition 1.1–

Condition 1.2

(30:10)

0.450

5 0.055

Condition 1.1–

Condition 1.3

(20:20+25:15)

0.459

6 0.066

Condition 1.1–

Condition 1.3

(30:10)

0.649

7 0.077

Condition 1.1–

Condition 1.3

(35:5+40:0)

0.678

8 0.088

Condition 1.2–

Condition 1.3

(20:20+25:15)

1.000

9 0.100

18

rTPJa condition. We found that the third-party punishment in US_equal-trials (30:10

splits) in the rTPJa condition (Condition 1.2) was significantly smaller than it was in

the sham condition (Condition 1.3): Z = -2.746, p = 0.006 (see Table 1 and Table 3 for

details). We also observed a trend of a smaller third-party punishment in US_inequal-

trials (35:5 and 40:0 splits) in the rTPJa condition (Condition 1.2) compared with the

sham condition (Condition 1.3): Z = -2.006, p = 0.045, which did not survive FDR

correction (see Table 2 for FDR-corrected alpha levels).

Table 3. Effect of unilateral transcranial direct current stimulation on third-party

punishment (Study 1).

Split 20:0+25:5 30:10 35:5+40:0

Rank (1.90; 1.88; 2.23) (2.30; 1.58; 2.13) (2.20; 1.60; 2.20)

χ2 1.937 7.508 5.408

df 2 2 2

p 0.380 0.023* 0.067

Notes: Friedman test for 3 samples. * Significant at the level of p = 0.05.

Condition 1.2–Condition

1.3

Split 20:0+25:5 30:10

35:5+40:0

Z 0.000 –2.746

-2.006

p 1 0.006* 0.045


1.3

Split 20:0+25:5 30:10

35:5+40:0

19

Z -0.741 –0.456

-0.415

p 0.459 0.649 0.678


1.2

Split 20:0+25:5 30:10

35:5+40:0

Z -0.940 –0.755

-2.177

p 0.347 0.450 0.029

Notes: Wilcoxon signed-rank test for sums of punishment points. * Significant at the

level of p = 0.05.

We found no other significant effects of tDCS on third-party punishment. Therefore,

Hypotheses I and III were partly supported: anodal tDCS of the rTPJ significantly

decreased third-party punishment, but only in US_equal-trials (unfair 30:10 splits),

where third-party punishment was able to establish equality between all players.

Study 2: Simultaneous modulation of the rDLPFC and rTPJ

Similar to Study 1, the participants in Conditions 2.1, 2.2, and 2.3 punished unfair

splits (US_equal-trials and US_inequal-trials) more strongly than they did fair splits.

We found no significant effects of tDCS in Study 2. Interestingly, the third-party

punishment for 30:10 splits in the rDLPFCc/rTPJa condition (Condition 2.2) tended to

be higher than that in the sham condition (Condition 2.3), Z = -1.917, p = 0.055

20

(uncorrected; see Table 4 for details). Therefore, our results did not support

Hypothesis II.

Table 4. Effect of reciprocal transcranial direct current stimulation on third-party

punishment (Study 2).

Split 20:20+25:5 30:10 35:5+40:0

Rank (1.71; 2.16; 2.13) (1.66; 2.24; 2.11) (1.92; 2.08; 2.00)

χ2 2.984 5.115 0.269

df 2 2 2

p 0.225 0.077 0.874

Notes: Friedman test for 3 samples.


2.3

Split 20:0+25:5 30:10

35:5+40:0

Z -0.999 –1.917

-0.028

p 0.318 0.055 0.977


2.3

Split

20:0+25:5

30:10

35:5+40:0

Z -1.307 –1.401

-0.087

21

p 0.191 0.161 0.930


2.2

Split

20:0+25:5

30:10

35:5+40:0

Z -0.140 –1.337 -0.570

p 0.888 0.181 0.569

Between-group analysis

A Kruskal–Wallis H test showed that the normalized punishment levels for 30:10

splits differed in Study 1 and Study 2: χ2 = 4.481, p = 0.034, for 30:10 splits

(Condition 1.2 versus Condition 2.2; see Table 5). Third-party punishment for 30:10

splits was significantly lower in Study 1 than in Study 2. This could indicate an

opposite effect of the anodal tDCS of the rTPJ (rTPJa condition) compared with the

anodal tDCS of the rTPJ when paralleled with cathodal tDCS of rDLPFC.

Table 5. Comparison of transcranial direct current stimulation effects on third-party

punishment in Study 1 and Study 2 (Condition 1.2–Condition 2.2 [Normalized Data]).

Split 25/15 30/10 35/5 40/0

Rank (23.28; 16.55) (16.25; 23.95) (23.10; 16.74) (20.23; 19.76)

χ2 3.420 4.481 3.105 0.016

df 1 1 1 1

p 0.064 0.034* 0.078 0.898

22

Inequity aversion model

To assess the effect of stimulation on third-party punishment from theoretical

viewpoint, we used a modified inequity aversion model (Fehr and Schmidt, 1999)

extended to third parties (Svedsater and Johannsson, 2005). The model assumes that

each player in the game generally dislikes unfair outcomes reducing their utility. First,

consider the utility function of sanctioner, who observes the dictator game between

dictator and recipient, but who has no punishment option. The sanctioner receives an

endowment and feels unhappy whenever any other players receive either more (with

parameter α) or less than she does (with parameter β). The sanctioner also experiences

moral loss when the payoffs of the dictator and recipient are unequal (with parameter

γ). In terms of inequity aversion model of Fehr and Schmidt (1999), the resulting

utility is:

U3N = w3 − α max(X1 − w3,0) − α max(X2 − w3,0) − β max(w3− X1,0) − β max(w3 −

X2,0) − γ|X1 − X2|. (Eq. 1)

Here, X1 and X2 are MUs collected by dictator and sanctioner, respectively, X1 + X2 =

40 (MUs); w3 = 20 is the endowment of sanctioner, and α, β, and γ are parameters of

inequity aversion. Only if both other players receive exactly as much as the third

player (and hence, their respective payoffs are equal) the third player experiences no

utility loss, receiving just w3.

Fehr and Schmidt’s (1999) canonical two-player inequity aversion model typically

assumes that α > 1 > β > 0; this captures the envy of each player who dislikes being

treated unfairly more than (s)he dislikes being unfair towards another player. In our

study, dictator’s decision does not materially affect the sanctioner, who may want to

punish the former player only for violations of ethical standards, but not because of

personal material losses. Hence, moral loss of the sanctioner can be assumed to be

23

larger than the cost of punishment; that is, 1 > α > β > 0. Furthermore, in our

application, we may separate two feelings of the sanctioner, as follows:

(1) The sanctioner’s discomfort/disapproval of unfair actions of the dictator, which

she may compensate for by the third-party punishment. The level of this discomfort is

proportional to the extent of unfairness, and its strength is captured by parameter γ (we

assume that γ > 1); and

(2) The costs of punishment, which consist of two elements, namely the monetary cost

of punishment and the sanctioner’s wellbeing relative to that of the other players.

Inequity-averse sanctioners are concerned about fairness of the terminal distribution;

hence, these feelings are proportional to the realized differences between the revenues

of Players 3 and 1 and 3 and 2, taken with strengths α and β, respectively. We assume

that the sanctioner does not distinguish between her residual income relative to Players

1 and 2’s terminal incomes; hence, parameters α and β of the sanctioner are the same

when applied to Players 1 and 2.

In total, the sanctioner’s utility in the case of punishment is

U3P=w3 − x3 − α max((X1 − kx3 − (w3 − x3), 0)) − α max((X2 − (w3 − x3), 0)) − β

max((w3 − x3 − (X1 − kx3), 0)) − β max((w3− x3) − X2,0)) − γ|X1 − kx3 − X2|,

(Eq. 2)

where k (=2) is the punishment efficiency parameter — the number of MUs taken

from Player 1 if that player is punished by x3 (x3 ≤ w = 18). This utility function is

maximized with respect to x3 (punishment size), and it reaches a maximum when all

terms involving x3 are brought to 0, that is, when the shares of Players 1 and 2 are

exactly equal. A rational Player 3 (sanctioner) with these preferences will punish if

Eq.2 > Eq.1.

24

Proposition: A unique equilibrium punishment strategy of Player 3 with utilities given

by Eq.1 and Eq.2 is

x3 = 0 if X1<20,

x3 = X1 g / (g − 1) − 20(g +1) / (g − 1) if 20<X1 and x3<18, where g = α+β+2γ,

x3 = 18 if x3>= 18.

Equilibrium punishment strategy and model predictions are the following: the more

unfair the split the sanctioner observes, the stronger the punishment she assigns to

Player 1, until the maximum number of MUs allowed, 18.

Positive punishment should take place whenever Eq. 1< Eq. 2. By construction, X1 >

w3 whenever w3 > X2, hence Eq.1 equals either

U3Na

= w3 − α max(X1 − w3,0) − β max(w3 − X2,0) − γ(X1 − X2) (Eq.3)

or

U3Nb

=w3 − α max(X2 − w3,0) − β max(w3 − X1,0) − γ(X2 − X1) (Eq.4)

provided X1 ≠ X2 (otherwise, there is no inequity and no reason to punish at all). When

punishment takes place, Eq. 2 becomes either

U3Pa

=w3 − x3 − α max((X1− kx3− (w3 − x3), 0)) − β max((w3 − x3) − X2,0)) − γ(X1 − kx3

− X2) (Eq.5)

or

U3Pb

=w3 − x3 − α max((X2− (w3 − x3), 0)) − β max((w3 − x3 − (X1 − kx3), 0)) − γ(X2 −

X1+kx3) (Eq.6)

25

given the definition of X1 = 40 − X2, and k, it is straightforward to see that X1 − kx3 −

(w3 − x3) and X2 − (w3 − x3) cannot be both > 0.

Hence, we can limit attention to two possible cases:

X1 > X2, and choice between Eq.3 and Eq.5, and

X1 < X2, and choice between Eq.4 and Eq.6.

Consider them in turn:

Case 1: X1 > X2

Decision to punish takes place when U3Na<U3Pa, i.e.

w3 − α (X1 − w3) − β (w3 − X2) − γ(X1 − X2) <w3 − x3 − α (X1 − kx3 − (w3 − x3)) − β (w3

− x3) − X2) − γ(X1 − kx3 − X2)

=> 0<x3( α + β + 2γ − 1)

(Eq.7)

which holds true whenever α, β, γ are all positive and large enough. Hence in this case

player 3 should punish until the condition is satisfied, i.e. up to the tipping point when

Eq.7 becomes violated. From Eq.5, it is straightforward to see that utility increases in

x3 and is given by

x3 = X1 (α + β + 2γ)/(α + β + 2γ − 1) − (w3(α − β + 1)+ 40(β + γ)) / (α + β + 2γ − 1) =

X1 (α + β + 2γ) / (α+β+2γ − 1) − 20 (α+β+2γ+1) / (α+β+2γ − 1)

(Eq.8)

as stated in the proposition. If g =α+β+2γ>1, this strategy increases from X1=20 to the

maximum punishment allowed of 18 at a rate greater than 1, up to the point where X1

26

− 20 − x3 >0. This last condition is satisfied provided X1 − 20 − X1 γ / (γ − 1) − 20(γ

+1) / (γ − 1) = (40 − X1) / (γ − 1) >0, which is true for any value of X1.

Case 2: X1 < X2

Punishment takes place whenever

U3Na

< U3Pb

, i.e.

w3− α (X2 − w3) − β (w3 − X1) − γ(X2 − X1) < w3 − x3 − α (X2 − (w3 − x3)) − β (w3 − x3

− (X1 − kx3)) − γ(X2 − X1 + kx3)

=> 0<− x3( α+β+2γ+1)

(Eq.9)

which condition can never be true if the parameters are positive.

In sum, the inequity aversion model (Fehr and Schmidt, 1999; Svedsäter and

Johansson, 2005) predicts that third-party punishment (as given by Eq.8) increases

linearly if X1>20, up to the maximum allowed amount of 18, and is zero otherwise.

Model predictions

To elaborate on our results, we used a computational model: participants’ material

costs were defined by parameters α and β, where α represents disadvantageous

inequality and β represents advantageous inequality. The model predicts no third-party

punishment of equal (20:20) splits and a stronger third-party punishment of more

unfair splits.

The model implies that the third-party punishment decision depends on two key

components: material costs (underlined by rDLPFC activity) and moral costs

(underlined by rTPJ activity). Material costs of third-party punishment increase as the

sanctioner pays higher amounts to punish the unfair behavior of the dictator. In

27

contrast, for moral costs, the sanctioner is better off the more she pays to punish the

dictator’s unfair behavior. Both components are depicted in Figure 4, which also

shows the following hypothetical effect of stimulation as predicted by the model:

anodal tDCS of the rTPJ, where the activation of moral feelings increases the

parameter γ and changes the slope of the moral cost line, but only up to the point

where the material costs do not exceed the moral ones. This may suggest an optimum

equilibrium of material and moral costs for third-party punishment, where the further

increase of punishment increases the material costs, while a decrease of punishment

would increase the moral costs.

The discussion above suggests that anodal tDCS of the rTPJ could increase the

marginal utility of the moral costs, which could shift the utility function of such costs

(Figure 4, optimal punishment point X3 changes to X3*), and consequently, decrease

third-party punishment. This effect of anodal tDCS of the rTPJ was indeed observed in

Study 1 (Condition 1.2). In contrast, when paralleled with cathodal stimulation of the

rDLPFC, anodal tDCS of the rTPJ should increase the marginal utility of the moral

costs while decreasing the marginal utility of the material costs, consequently

increasing third-party punishment. Interestingly, we observed a trend of this tDCS

effect in Study 2 (Condition 2.2).

Importantly, in our version of the dictator game, third-party punishments of extremely

unfair splits are quite costly. Accordingly, the model implies a strong conflict between

material and moral costs when participants punish such splits. Interestingly, only in

the case where participants observe moderately unfair 30:10 splits, the conflict

between material and moral costs is minimal, since participants either do not punish or

punish extremely little if the material costs are high. Therefore, tDCS could have the

strongest effect on the third-party punishment of 30:10 splits, as increased moral costs

would not conflict with marginally affected material costs. Thus, the model could

explain our findings of the significant effect of tDCS on third-party punishment of

28

slightly unfair 30:10 splits. Importantly, the model suggests that only for moderate

(30:10) splits were the subjects able to maximize the utility of third-party punishment,

and at the same time, minimize all players’ inequity. Interestingly, third-party

punishment of 30:10 splits creates a Pareto optimal distribution of MUs (10:10:10),

where it is impossible to improve the income of one player without worsening the

incomes of the other players.

Figure 4. Hypothetical scenario of moral and material costs’ interaction during

third-party punishment. The intersection of lines representing material costs and

moral costs indicates an optimal punishment decision (x3), while x3*

represents an

optimal punishment decision when the moral costs are affected by anodal tDCS to the

rTPJ.

Discussion

Our study demonstrated that anodal tDCS to the rTPJ decreased third-party

punishment of moderately unfair splits during the dictator game. Our finding is

consistent with the recent TMS study (Baumgartner et al. 2014), which demonstrated

29

that an inhibition of the rTPJ decreased the parochial punishment of outgroup

members.

A previous study showed that anodal tDCS applied to the rTPJ led to less blame for

accidental harms during a moral judgment task (Sellaro et al., 2015). This suggests that

rTPJ is involved in processing the agent’s moral intentions. Recent meta-analysis

suggests that rTPJ showed significant activation when making one’s own moral

decisions (Garrigan, Adlam and Langdon, 2016). Thus, rTPJ activity in our study

could underlie the processing of the dictator’s mental state—her moral intentions.

Alternatively, it could reflect thinking about the consequences of the third-party’s own

decision and how harmful it would be for others. Thus, anodal stimulation of this area

could exaggerate the latter process and consequently diminish the punishment.

Overall, anodal tDCS of the rTPJ could affect the perceived degree of the moral norm

violation, and consequently decrease the assigned blame and punishment of the

dictator.

Our results only partly support Hypothesis I, since we did not find a significant effect

of anodal tDCS of the rDLPFC on third-party punishment. A previous study showed

that the suppression of rDLPFC by TMS leads to increased third-party punishment

(Brüne et al., 2012). Importantly though, in this previous study, third-party punishment

was combined with helping behavior—the recipients’ payoffs increased by the same

amount that was taken from the dictators’ budget by the sanctioners. A recent study

suggested that the rDLPFC is especially activated during the helping behavior of third

parties (Hu, Strang and Weber, 2015). Thus, one possible explanation for the

discrepancy with our results is that, in our paradigm, third-party punishment was not

associated with helping behavior.

Interestingly, anodal tDCS of the rTPJ significantly decreased third-party punishment

only in US_equal-trials, where third-party punishment was able to establish equality

30

between all players. In our study, third-party punishment of 30:10 splits created a

Pareto optimal distribution of MUs (10:10:10), where it was impossible to improve the

income of one player without worsening the incomes of the other players. . Our model

predicted a minimal conflict between the material and moral costs of third-party

punishment in moderately unfair (30:10) splits. Thus, only the punishment of 30:10

splits could maximize the utility of third-party punishment and minimize the inequity

of all players. Overall, we speculate that anodal tDCS of the rTPJ could increase the

marginal utility of moral costs, which could shift the utility function of the moral costs

and decrease third-party punishment.

In Study 2, we simultaneously applied cathodal tDCS to the rDLPFC and anodal tDCS

to the rTPJ. A previous fMRI study demonstrated that TPJ activity during third-party

punishment is paralleled by an initial deactivation of the DLPFC (Buckholtz et al.,

2008). We found only a trend of effect of the reciprocal stimulation protocol on third-

party punishment and failed to confirm Hypothesis II. A recent meta-analysis showed

that the excitatory effect of anodal tDCS is replicable in cognitive studies, while the

cathodal stimulation effect is not stable and rarely leads to inhibition (Jacobson,

Koslowsky and Lavidor, 2012). In our study, cathodal tDCS of the rDLPFC could

have led to a marginal effect of rDLPFCc/rTPJa stimulation. Overall, the trend of an

increment of third-party punishment after rDLPFCc/rTPJa stimulation in our study

could indicate an effect of tDCS on the interaction of the default mode network (TPJ)

and central executive network (rDLPFC). Additional studies are needed to investigate

the effects of the rDLPFCc/rTPJa tDCS protocol.

To further probe the frontoparietal interactions during third-party punishment, follow-

up studies could combine brain stimulation and brain imaging techniques.

Electroencephalography coherence as a measure of functional cortical connectivity on

a centimeter scale (Srinivasan et al., 1998; Nunez and Srinivasan, 2006) could offer a

31

tool for studying TPJ/DLPFC synchronization during third-party punishment

decisions.

Conclusion

Our study demonstrates that anodal tDCS of the rTPJ decreases third-party punishment

of moderately unfair behavior when the participants have an opportunity to restore

equality in their social groups. We found only a small, insignificant trend of the effect

of simultaneous anodal tDCS of the rTPJ and cathodal tDCS of the rDLPFC on third-

party punishment. Overall, our findings support the critical role of the rTPJ in third-

party punishment.

Acknowledgement

We thank Maartje Elisa Dankbaar, MSc, for her assistance in stimulus preparation; Dr.

Matteo Feurra for his expertise in tDCS; and Dr. Alexei Zakharov, who provided the

original behavioral data of the dictator game. This study used the HSE Synchronous

Eye-tracking, Brain Signal Recording and Non-Invasive Brain Stimulation System.

Funding

The article was prepared within the framework of the HSE University Basic Research

Program and funded by the Russian Academic Excellence Project '5-100'.

32

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