Friday, January 6, 2023

Motivations to reciprocate cooperation and punish defection are calibrated by estimates of how easily others can switch partners

Motivations to reciprocate cooperation and punish defection are calibrated by estimates of how easily others can switch partners. Sakura Arai, John Tooby, Leda Cosmides. PLoS One, April 19, 2022.

Abstract: Evolutionary models of dyadic cooperation demonstrate that selection favors different strategies for reciprocity depending on opportunities to choose alternative partners. We propose that selection has favored mechanisms that estimate the extent to which others can switch partners and calibrate motivations to reciprocate and punish accordingly. These estimates should reflect default assumptions about relational mobility: the probability that individuals in one’s social world will have the opportunity to form relationships with new partners. This prior probability can be updated by cues present in the immediate situation one is facing. The resulting estimate of a partner’s outside options should serve as input to motivational systems regulating reciprocity: Higher estimates should down-regulate the use of sanctions to prevent defection by a current partner, and up-regulate efforts to attract better cooperative partners by curating one’s own reputation and monitoring that of others. We tested this hypothesis using a Trust Game with Punishment (TGP), which provides continuous measures of reciprocity, defection, and punishment in response to defection. We measured each participant’s perception of relational mobility in their real-world social ecology and experimentally varied a cue to partner switching. Moreover, the study was conducted in the US (n = 519) and Japan (n = 520): societies that are high versus low in relational mobility. Across conditions and societies, higher perceptions of relational mobility were associated with increased reciprocity and decreased punishment: i.e., those who thought that others have many opportunities to find new partners reciprocated more and punished less. The situational cue to partner switching was detected, but relational mobility in one’s real social world regulated motivations to reciprocate and punish, even in the experimental setting. The current research provides evidence that motivational systems are designed to estimate varying degrees of partner choice in one’s social ecology and regulate reciprocal behaviors accordingly.

4 Discussion

4.1 Evidence that motivational systems are designed for social ecologies with varying levels of partner choice

Ancestral variation in the availability of cooperative partners would have favored the evolution of motivational systems that treat partner choice as a continuous variable. Motivations to keep valuable cooperative partners and abandon unrewarding ones should be up-regulated in response to the perception that others can easily switch partners.

Here we tested the hypothesis that an individual’s motivations to reciprocate and punish are calibrated by that person’s estimate of the degree to which others in their local social ecology can exercise partner choice. This estimate is captured by measures of relational mobility [50]. The higher an individual’s relational mobility score, the more opportunities they believe others have to leave unsatisfying relationships for better ones.

We assessed motivations to trust, reciprocate, defect, punish, and switch partners by allowing people to cooperate for mutual benefit with a new individual. The results showed that motivations to reciprocate and punish tracked participants’ perceptions of relational mobility. The more partner choice they thought others in their social ecology could exercise, the more they reciprocated their partner’s trust and the less they paid to punish their partner—even when that partner had defected.

Providing incentives for desirable partners to stay in the relationship is the proposed function of these motivational calibrations. If that is correct, then people who have the opportunity to switch partners will be more likely to stay with a partner who reciprocates their trust and more likely to leave one who punishes them. After two rounds, half the participants were asked if they wanted to keep their current partner or switch to someone new. Holding all else equal, having been defected on more than quadrupled the odds that they wanted to switch and having been punished tripled the odds they would choose to leave. These were the two biggest independent predictors of switching decisions. The desire to leave a partner who punished was especially strong for participants who returned 40%—a response that creates a positive payoff for both parties that is almost equal. These individuals were almost 10 times more likely to want a new partner.

4.1.1 Are priors about social ecology updated by information about the situation or the person?

Perceptions of relational mobility are based on a huge database of experiences in a local social ecology—sometimes a lifetime’s worth. For this reason, we proposed that relational mobility serves as an estimate of the prior probability that others in one’s social ecology can exercise partner choice. It is a best guess before you learn what your partner is like—the situation participants faced in round 1.

If relational mobility in your social ecology is used to estimate a partner’s outside options when you know nothing else about that person, then its effect on cooperative motivations should be reduced (or eliminated) by data about that specific person’s value as a cooperative partner—to yourself and others. The evidence indicates that participants in both societies updated this prior based on first-hand knowledge of their partner’s willingness to cooperate and reluctance to punish. Once participants had experienced how their partner behaved in round 1, relational mobility no longer predicted how much they trusted, reciprocated, or punished in round 2, in either the US or Japan. The behavior of the sham partner in round 1 (and, of course, in round 2) did predict their responses. The only behavior that relational mobility continued to influence was antisocial punishment. The belief others in your social ecology can easily switch partners tempered—but did not eliminate—antisocial punishment. (See S5 Appendix.)

The results suggest that estimates of partner choice based on social ecology are updated based on properties of the person with whom one is interacting. But are these estimates updated in response to cues about a temporary situation one is facing—ones unrelated to the partner’s value as a cooperator? It is not clear that they should be.

Delton et al. [35] examined the evolution of motivations to cooperate in Bayesian agents who knew the base rate of one-shot interactions in their population and updated this prior based on a cue about the immediate situation they were facing. The cue reflected the probability that they would never interact again with their current partner. These Bayesian agents evolved a strong disposition to cooperate even when they rationally believed the interaction was one-shot. Selection favored agents who behaved as if they would repeatedly interact with their current partner even when they knew this was unlikely. Agent-based models also show that meeting a new individual once was a good cue that you will meet them again in ancestral social ecologies [64]. Every participant in our study was exposed to this ancestrally-reliable cue to a shadow of the future: They interacted with their partner for two rounds.

We did, however, provide a verbal cue relevant to partner choice in the temporary situation that they were facing. Half the participants were told they would be interacting with the same partner in every round (i.e., they were engaged in a repeated interaction with this person). The other half were told they could change partners after two rounds (i.e., their current partner can refuse to interact with them repeatedly). If this verbal cue is used to (temporarily) update their prior probability that a newly encountered person can exercise partner choice, their motivations to cooperate or punish might shift in response.

There was little evidence that participants in round 1 used this situational cue to update a prior that was based on their social ecology. Being told whether they would have the opportunity to switch partners had no effect on how much participants punished defections by their partner: Higher relational mobility in their local social ecology predicted less punishment, regardless of condition or society. The cue did have an effect on how much American participants reciprocated their partner’s trust, however. Although average levels of reciprocation were similar in both conditions, higher relational mobility predicted more reciprocation when Americans were told they and their partner could part ways after two rounds, but not when they were told that all of their interactions would be with the same partner.

Japanese participants did not respond to this cue at all: Their estimates of relational mobility predicted more reciprocation (and less punishment) to the same extent in both conditions. That is, there was no evidence that people in Japan updated their prior hypothesis about relational mobility based on the situational cue we provided. If they did, the change was too small to influence their willingness to reciprocate or punish.

If this result generalizes to other cues about a temporary situation, it suggests that the benefits of opportunistic behavior in the short term were generally outweighed by the risk of losing a valuable, long-term cooperative partner.

4.2 What is the function of punishment in dyadic reciprocal cooperation?

What, if anything, is the adaptive function of motivations to pay a cost to punish a defecting partner? This was not a rare response: Of participants who were trusters in round 1, 44% punished when the responder defected. It is usually assumed that the function of punishing defectors is to elicit more cooperation from them in the future—especially when they do not have the option to change partners.

People who believe others in their social ecology have fewer options to switch partners did pay more to punish defectors: Low relational mobility scores predicted paying more to punish. But there was no evidence that punishment succeeded in eliciting greater cooperation from participants. Quite the contrary: Participants who were punished for returning 0–40% in round 1 did not respond by sending more points as truster in round 2. Indeed, they returned fewer points as truster (β = -.22, p = .0002), and this effect was particularly pronounced for those who had provided a positive payoff by returning 40% in round 1, β = -.41, p = .0001 (vs. β = -.12, p = .099 for those who provided a negative payoff in round 1; see S5 Appendix). Moreover, those who were punished in round 1 were more likely to retaliate by punishing their partner in round 2 (S5 Appendix; for similar results, see [6566]).

Not only did punishment fail to elicit more cooperation from punished partners, but it also drove them away. When partner switching was possible, having been punished was one of the biggest independent predictors of wanting to change partners. Driving away defectors might be a function of punishment, of course—when they were not punished, ~70% of people who returned 0–40% wanted to remain with their accommodating partner (~68% of those who returned 0–30%; ~71% of those returning 40%). Although participants in this study could prevent future interactions at lower cost by simply deciding to switch after round 2, avoiding unrewarding partners may be more difficult in real life, especially when they want to continue cooperating with you.

Krasnow et al. [57] suggest that punishing defection signals a willingness to continue cooperating with your current partner, but on more favorable terms. Using a paradigm similar to the TGP, they found that participants who punished a defecting partner in the first round were 11 times more likely to cooperate than defect in the second one (switching was not an option). This pattern was not apparent in our study: Participants who punished a defecting partner did not return more in round 2 than those who did not (39.28% vs. 35.18%, t (226.99) = 1.41, p = .160), and they were not more likely to want to remain with their partner—indeed, the more points participants paid to punish the partner, the more—although slightly—they wanted to switch (OR = 1.02; 95% CI = [1.01, 1.03]). (Note, however, that a participant’s decision to stay did not ensure a continuing interaction in our study; the partner also had the option to leave, and punished ones were likely to do so.)

Our results showing that retaliatory punishment was common—~45% of those who were punished in round 1 retaliated in round 2—suggest an alternative explanation. In Krasnow et al. [57], participants who punished defectors in round 1 may have cooperated in round 2 to avoid (very costly) retaliatory punishment by their partner. Those who did not punish partners who succumbed to the temptation to cheat in round 1 may have assumed their partner would “reciprocate” by not punishing when them when they did the same in round 2.

Motivations to punish did not reflect the participant’s own commitment to stay in the relationship, but they were up-regulated by estimates that partners might have few outside options: Lower relational mobility in one’s social ecology did predict amount paid to punish defectors. The results are consistent with the hypothesis that motivations to punish evolved to deter bad treatment in the future by partners who do not seem to value your welfare [67]. Defecting now may be a reliable cue that this partner does not value your welfare sufficiently, and punishment was overwhelmingly directed at defectors. In ancestral social ecologies, partners who part ways now may nevertheless have to cooperate again in the future [646768]. Punishment may have evolved as a warning, to deter bad treatment by defectors who may darken your door in the future.

4.3 Micro and macro effects of social ecology

We measured two variables regarding participants’ real-life social ecology of partner choice. First, we measured participants’ perceptions of their partner choice ecology with the relational mobility scale [50]. Second, we recruited participants from two societies in which average relational mobility scores are typically high (US) versus low (Japan). This lets us see whether behavior at the individual level scales up to explain differences between nations.

Within each society, the motivations of individuals were calibrated by their perceptions of other people’s relational mobility: the number of opportunities they believe that others have to form new relationships. Moreover, the pattern of calibration was universal: Within each society, higher relational mobility scores predicted more reciprocation and less punishment. Individual-level effects tracked individual perceptions of the local social ecology.

What about group-level differences? The concept of relational mobility was built from Yamagishi’s seminal work on general trust: a cognitive bias to assume that newly encountered people will treat you with benevolence rather than exploitation [6970]. General trust varies across nations; scores on the standard survey measure are higher in the US than Japan, for example. Where general trust is higher, people are more willing to risk cooperating with strangers who could, if untrustworthy, profit at their expense. The benefit of trusting strangers is that it allows people to discover better cooperative partners, giving them more outside options. The resulting increase relational mobility then tempers the risk of trusting strangers: The threat that a good partner will leave for a better outside option can deter exploitive behavior and increase benevolence.

With this in mind, we compared average behavior in the US and Japan. As in other studies, perceptions of relational mobility were higher in the US than Japan (RM others: 4.12 vs. 3.57, t (1028.2) = 13.76, p = 10−16RM self: 4.20 vs. 3.37, t (1030.8) = 18.71, p = 10−16). That is, the average American believes others have more outside options than the average person from Japan does. Moreover, as Yamagishi’s view of general trust predicts, when participants had no prior experiences with their partners, American trusters risked more points on a stranger than Japanese participants did (Trust: 59 vs. 50.6, t (502.55) = 2.9, p = .004). And trusting strangers usually paid off: Most responders delivered a positive payoff in both societies (US 67%, JP 76%).

Did the perception that others have more outside options lead the average American to reciprocate more and punish less than the average person from Japan? No. Not only did Americans return less, on average, than Japanese participants, but more of them exploited their partner’s trust by delivering a negative payoff (US 33% vs. JP 24%). Americans were also more punitive, not less: They paid more to punish their partners, even when controlling for all other factors (including whether their partner defected). And, despite less reciprocation and more punishment at the macro-level, Americans were more likely to stay with their partner than Japanese participants (all else equal).

Within each society, individual differences in reciprocation and punishment were associated with individual differences in perceptions of relational mobility, but this did not translate into group-level differences between the US and Japan. Assuming that individual differences fully explain group-level differences is called the ecological fallacy [7173]. The data clearly show that the micro-level effect of individuals’ perceptions of relational mobility and the macro-level effect of society were independent of one another. The individual-level psychological calibrations and the group-level differences between nations coexist, rather than one producing the other.

Features of the social ecology other than relational mobility could be responsible for the differences in group-level calibrations between the US and Japan (see e.g., [5674]). That Japanese participants were less punitive than Americans is contrary to findings that Japan (or East Asian countries in general) has “tighter” norms than the US which, when broken, elicit great censure [7576], but perhaps consistent with studies showing greater motivations to avoid rejection in people in Japan than the US [74]. Our data cannot speak to these explanations of the group-level differences we found.

4.4 Limitations and future directions

Motivations responded when participants learned how the partner treats them, but the partner switching instructions influenced Americans only (and not much at that). This could be because repeated interactions—with interruptions between—were common ancestrally, making long-run estimates of social ecology a more reliable basis for calibration than cues about a fleeting situation. The other possibility is that a cue delivered online was too divorced from real life, devoid of psychophysical cues typical of social isolation versus community. Future studies might enhance the salience of the situational cue, perhaps by including visual displays showing many versus few alternative partners (avatars or faces), or by giving participants prior experiences of a desirable partner leaving for a better one or an unrewarding partner staying.

A person with fewer outside options than others in their local ecology may feel they need to reciprocate more and punish less. We did adapt the relational mobility scale to ask about the self; although self and other scores were correlated r (515) = .60 (p = 10−16) in the US and r (516) = .50 (p = 10−16) in Japan, we calculated whether RM self < RM other for each participant. In Japan, 67% of participants felt their outside options were worse than those of other people, compared to 44% in the US. And, in both countries, those who felt they have fewer outside options returned more points than those who felt their options were better than or equal to others, but the difference in points returned was not significant. A better measure in the future might be to ask, for each RM question, whether people feel they have more, the same, or fewer options than others in their society.

Dyadic cooperation may be affected by other aspects of the social ecology as well, such as how likely others will be to take advantage of you [69]. Punishment as a deterrent may be up-regulated in ecologies where the probability of being exploited are higher, as they were in the US in this study. Perceptions of these probabilities would be a fruitful variable to assess.

Lastly, our participants were from either the US or Japan, two populous, large-scale industrialized societies. Objectively speaking, most people in these countries are free to associate with anyone they like, and they are surrounded by strangers, each of whom is a potential new partner. It would be fruitful to extend the current line of research to smaller societies in which the actual—not only perceived—possibility of partner choice is more limited.

Drawing on a unique survey we examine how German citizens view the practice of discussing politics in everyday life, and what determines these attitudes; we find that only a minority appreciates talking about politics

Do people like to discuss politics? A study of citizens’ political talk culture. Rüdiger Schmitt-Beck, Manuel Neumann. European Political Science Review, January 4 2023.

Abstract: As deliberative democracy is gaining practical momentum, the question arises whether citizens’ attitudes toward everyday political talk are congruent with this ‘talk-centric’ vision of democratic governance. Drawing on a unique survey we examine how German citizens view the practice of discussing politics in everyday life, and what determines these attitudes. We find that only a minority appreciates talking about politics. To explain these views, we combine Fishbein and Ajzen’s Expectancy-Value Model of attitudes toward behaviors with perspectives from research on interpersonal communication. Individuals’ interest in politics emerges as the only relevant political disposition for attitudes toward everyday political talk. Its impact is surpassed and conditioned by conflict orientations and other enduring psychological dispositions, as well as contextual circumstances like the closeness of social ties and the amount of disagreement experienced during conversations. The beneficial effect of political interest dwindles under adverse interpersonal conditions. The social dimension of everyday political talk thus appears to outweigh its political dimension.

More confirmation of the Trivers-Willard hypothesis: Sons from high-status families achieve higher educational outcomes than daughters, while daughters from low-status families surpass sons

Parental background and daughters’ and sons’ educational outcomes – application of the Trivers-Willard hypothesis. Janne Salminen, Hannu Lehti. Journal of Biosocial Science, January 6 2023.

Abstract: This study uses Trivers-Willard hypothesis to explain the differences in daughters’ and sons’ educational outcomes by parental background. According to the Trivers-Willard hypothesis (TWH), parental support and investments for sons and daughters display an asymmetrical relationship according to parental status because of the different reproductive advantage of the sexes. It predicts that high-status parents support sons more than daughters, and low-status parents support daughters more than sons. In modern societies, where education is the most important mediator of status, the TW hypothesis predicts that sons from high-status families will achieve higher educational outcomes than daughters. Using cohorts born between 1987 and 1997 from the reliable full population Finnish register data that contain the data of over 600.000 individuals, children’s educational outcomes were measured using data on school dropout rate, academic grade point average (GPA), and general secondary enrollment in their adolescence. OLS and sibling fixed-effect regression that permitted an examination of opposite-sex siblings’ educational outcomes within the same family were applied. Sons with high family income and parental education, compared to daughters of the same family, have lower probability of dropping out of school and are more likely to enroll into academic secondary school track. In families with low parental education or income daughters have lower probability for school dropout and enroll more likely to academic school track related to sons of the same family. The effect of family background by sex can be interpreted to support TWH in dropout and academic school track enrollment but not in GPA.


This study investigated whether parental socioeconomic resources influence sons and daughters differently. The biosocial theory – the Trivers-Willard hypothesis – which states that parents with high social status invest more in sons compared to low-status parents who invest more in daughters, was applied. Sibling fixed-effects regression models were utilised by observing how parental education and family income influence sons’ and daughters’ GPA, dropout rates from secondary school and general secondary enrollment with reliable Finnish register data.

The results show that parental education has a stronger positive effect on sons’ educational outcomes than daughters in all three measured outcomes. Family income has an even more pronounced effect for dropping out from secondary education and for general secondary enrollment. However, family income did not influence the GPA based on the siblings’ sex. These results are in line with previous studies that have studied TWH in the United States (Hopcroft, Reference Hopcroft2005; Hopcroft & Martin, Reference Hopcroft and Martin2016; Pink, Schaman, & Fieder, Reference Pink, Schaman and Fieder2017). Additionally, the results support the claim that boys are more sensitive to family’s resources than girls in terms of educational outcomes (Autor et al. Reference Autor, Figlio, Karbownik, Roth and Wasserman2019; Brenøe & Lunberg, Reference Brenøe and Lundberg2018).

The result that found the largest Trivers-Willard effect for general secondary enrollment compared to dropout and GPA indicates that parents may guide children’s educational decision-making process. Thus, parents probably give guidance to their children according to their own human and economic capital; however, this study adds that the guidance can be different for sons and daughters depending on family conditions. The biosocial mechanism explains why family conditions influence differently for sons’ and daughters’ education.


Although we can obtain reliable information with register data, there are still some limitations despite large dataset and objective information. We were not able to obtain information about the exact nature of parental behavior for children’s benefit. The lack of direct measure of parental investment is the one limitation and thus it is difficult to observe exact mechanism between parental resources and child’s educational outcome.

However, previous studies show that parental SES and the amount of investment correlates highly (see Tanskanen & Danielsbacka, Reference Tanskanen and Danielsbacka2019). Further, the results show that parental education and family income had the strongest TWH effect on general secondary enrollment compared to dropout and GPA. Thus, it can be stated that the results of the study reflect parental investments in the form of human capital accumulation of the children, because children continue to pursue higher education very likely after general secondary education that leads to higher income and socioeconomic status in adulthood. However, parents may have lower possibilities to influence children’s risks of school dropout. Avoiding school dropout does not necessarily lead to high status in adulthood, but children who avoid dropout and continue secondary schooling avoid low status and income in adulthood. GPA is determined highly by children’s intelligence and other non-cognitive traits that parents find very difficult to influence in Finland due to the absence of private schools. It has been shown, for example, that individuals’ variations in GPA are largely explained by genes but not shared environmental effects such as family background (Nielsen, Reference Nielsen2006). Finnish schools that have very low variance and thus show low inequality of learning outcomes can even amplify the genetic effects and reduce the effects of parents and thus that of TWH on GPA.

This study could not control for health and psychiatric variables. Thus, the results may reflect the fact that boys have more learning difficulties than girls (for example in the case of ADHD and other neurotypical disabilities), particularly among low status families; however, the study controlled for GPA that considers at least some of the effect of learning disabilities.

The findings come from a Finnish birth cohort born in 1987–1997. This cohort has experienced relatively high equality of opportunity in school context and the egalitarian welfare state has supported their families throughout their childhood. For these cohorts, all education levels have been free of charge. The funding of the schools and universities are based on governmental finance. There is no private school at any education level. According to the Global Gender Gap Report (2021), Finnish society is the second most gender-egalitarian country in the world and on average, women are better educated than men. However, previous studies have shown that parental education rather than family income is associated with education and later social status in Nordic countries (Elstad & Bakken, Reference Elstad and Bakken2015; Erola et al., Reference Erola, Jalonen and Lehti2016) Surprisingly, the study still found that higher family income decreases the educational disadvantage for boys. Because this effect was found in the Nordic welfare context it suggests that in other countries with different institutional context that includes tuition fees, the effect of the family income could be even stronger. If TWH is seen as universal it should be influential despite the institutional context. The results support this interpretation because the effect is found also in contexts where parental resources should not matter for children’s education. This indicates that parents’ and children’s evolutionary adaptations that mold their cognitive architecture (biases) and behavior are effective in modern societies. Additionally, the result of family income is surprising because in contemporary western societies experience an abundance of resources that leads to high investment in all children (Hopcroft, Reference Hopcroft2005). It can be argued that the logic of the TWH is problematic because high status males do not have a higher probability to reproduce than high status females on an average in all modern societies due to the use of contraception (Hopcroft, Reference Hopcroft2005). However, this argument has not gained empirical support because previous studies show that still in many modern societies high status men have higher probability to have more children than lower status men (Nisén et al. Reference Nisén, Martikainen, Myrskylä and Silventoinen2018; Nettle & Pollet Reference Nettle and Pollet2008; Weeden et. al. Reference Weeden, Abrams, Green and Sabini2006; Lappegård & Rønsen Reference Lappegård and Rønsen2013; Hopcroft Reference Hopcroft2019). Furthermore, it is important to acknowledge while applying evolutionary explanations that individuals usually do not consciously try to increase their (inclusive) fitness and maximize the number of offspring as standard rational theories used in social science would assume. Instead, it is assumed that humans have cognitive mechanisms that guide them to put effort into things that would have tended to increase (inclusive) fitness during evolutionary history (Hrdy, Reference Hrdy2011). In an evolutionary framework, parental investments are defined as any investment by the parent in a child that increases the child’s likelihood to survive and hence reproductive success at the cost of the parent’s ability to invest in another child (Trivers, Reference Trivers

1972). Thus, parental investments mean parental behavior, for example parental care, that increases a child’s inclusive fitness. Therefore, future research should analyze parental behavior by combining register and survey data to get an even more thorough picture of TWH. 

No consistent associations of well-being & brain correlates

A systematic review of the neural correlates of well-being reveals no consistent associations. Lianne Vries, Margot P. van de Weijer, Meike Bartels. Neuroscience & Biobehavioral Reviews, January 5 2023, 105036.


• We performed a systematic review on the neural correlates of well-being.

• A wide range of brain regions was involved in well-being in the different studies.

• More left than right brain activation might be related to higher well-being.

• Replication of associations across studies was scarce, in strength and direction.

• Well-powered brain-wide association studies are needed to study neural correlates of well-being.

Abstract: Findings from behavioral and genetic studies indicate a potential role for the involvement of brain structures and brain functioning in well-being. We performed a systematic review on the association between brain structures or brain functioning and well-being, including 56 studies. The 11 electroencephalography (EEG) studies suggest a larger alpha asymmetry (more left than right brain activation) to be related to higher well-being. The 18 Magnetic Resonance Imaging (MRI) studies, 26 resting-state functional MRI studies and two functional near-infrared spectroscopy (fNIRS) studies identified a wide range of brain regions involved in well-being, but replication across studies was scarce, both in direction and strength of the associations. The inconsistency could result from small sample sizes of most studies and a possible wide-spread network of brain regions with small effects involved in well-being. Future directions include well-powered brain-wide association studies and innovative methods to more reliably measure brain activity in daily life.

Keywords: well-beingbrainneural correlatesbrain-wide associations


To understand observed differences in well-being between people in more detail, it is essential to identify the biological and neural factors related to well-being. The goal of this systematic review was to bring together the available literature on well-being and brain structures and brain functioning. We first summarize and discuss the findings and based on the results, we propose directions for future research.

Brain structure

The systematic review of the brain areas where grey matter volume was associated with well-being revealed large inconsistencies. While the grey matter volumes of the (medial) PFC, ACC, the precuneus, hippocampus, and brainstem were related to well-being in multiple studies, for all these areas, there was inconsistency in the direction of the associations. Whereas in some studies smaller grey matter volume of the PFC, ACC, precuneus, hippocampus, or brainstem was related to higher levels of well-being, in other studies a larger grey matter volume of these areas was related to higher well-being.

These discrepancies might be the result of the small sample sizes (ranging from 15 to 724) in most structural MRI studies. Especially if the effect sizes are small, a large sample size is needed to have enough power to detect associations (Marek et al., 2022). Only two studies included more than 700 participants and only five studies more than 200 participants, indicating the need for larger sample sizes before we are able to reliably test for an association between the structure and volume of brain areas and well-being.

More recent studies went beyond brain volume and reported for example that well-being was associated with higher orientation dispersion, i.e., brain development and more dendritic complexity (Cabeen et al., 2021). This suggests that other, more detailed, features of brain structures might be related to well-being. The development and application of higher resolution imaging sequences allows us to, for example, investigate the cortical microstructure and complexity of brain structures in relation to phenotypes in more detail (Zhang et al., 2012).

Brain functioning


Three studies related well-being to the profiles of resting EEG power. Resting EEG power measures spontaneous brain activity, which can be divided into different frequencies. In single studies, the slower frequency signals, theta and alpha, were negatively related to well-being, whereas delta power, a faster brain oscillation, was positively related to well-being. A recent and larger study reported only a relation between the interaction between alpha, beta, and delta power and well-being, whereas the relation between the power of the single frequency bands and well-being was not significant. This could indicate that the relative amplitude of different frequency bands is important for well-being instead of the absolute power of single frequency bands. However, replication in studies with larger sample sizes is needed to draw a conclusion on the association between well-being and the different frequency bands in the brain.

(Frontal) alpha asymmetry was examined in more studies and positively associated with a measure of well-being in seven of the nine studies, whereas the other studies did not report a significant effect. Additionally, the small meta-analysis of alpha asymmetry and well-being indicated a positive relation (r=.19), but also suggested a possible publication bias. If replicated, greater left than right frontal activation is associated with well-being. This is in line with theory that alpha asymmetry is related to approach motivation and therefore the experience of positive feelings (Angus and Harmon-Jones, 2016). The opposite asymmetry, greater right-frontal activity, is assumed to be involved in withdrawal motivation, and some studies have found a relation with depression (but see (Olbrich and Arns, 2013) for a discussion about the unsuccessful replications). Noteworthy is that most studies on alpha asymmetry included measures of positive affect and/or life satisfaction, whereas the psychological well-being scale was only included in one study. More research on the moderating effect of the well-being scale used is therefore needed in future studies.


The results of the included studies on the associations of well-being and brain activity and functional connectivity across brain regions/networks are very heterogenous. As can be seen in Fig. 4, many brain regions across the whole brain were associated with well-being in the different studies. However, replication of the associations across multiple studies was mostly absent. Furthermore, if a brain region was associated with well-being in multiple studies, the direction of the association was inconsistent. For example, in the fMRI studies that associated the activity or functional connectivity of the PFC, orbitofrontal cortex or precuneus to well-being (respectively 14, 5 and 4 studies in total, see Supplementary Table S1), for all brain areas half of the associations with well-being were negative, whereas the other half were positive. The most consistent finding in fMRI studies that investigated the connectivity between brain areas in relation to well-being is that a stronger functional connectivity within the default mode network (DMN) is related to lower well-being. The DMN consists of brain regions in the ventral and dorsal medial PFC, and the PCC. This network of cooperating brain regions is active when a person is in resting state or when not focused on the outside world (Raichle, 2015). The DMN has been involved in daydreaming and mind wandering. The positive correlation between connectivity in the DMN and well-being suggests that the activity of several brain areas related to thinking spontaneously is connected stronger in happier people.


The results of the reviewed studies on the neural correlates of well-being are very heterogeneous. Across all studies and methods, brain areas most often associated with well-being were the PFC, ACC, insula, default mode network, orbitofrontal cortex, visual networks, precuneus, and somatosensory networks (see supplementary Table S1). The association between well-being and the structure and/or functioning of the PFC, ACC, insula, and precuneus was reported in studies using different techniques (e.g., fMRI, MRI and EEG). However, the direction and strength of these associations differed to a great extent and many other brain areas have been identified in single studies, but not replicated in other studies. We replicated part of the conclusions of (Machado and Cantilino, 2016) and (King, 2019) about the relations between well-being and various brain areas. However, the involvement of networks, like the DMN, visual, and somatosensory networks emerged mostly in more recent studies included in the current review.

A first explanation of the inconsistent results is the large differences in brain imaging methods and analysis techniques. Different brain functioning imaging methods might lead to different results, e.g., EEG and fMRI both assess brain functioning, but are completely different techniques with different temporal and spatial characteristics. The brain areas covered with these techniques are at the surface with EEG assessment, but include the whole brain with fMRI assessments. Furthermore, when using the same imaging technique, the analysis techniques differed a lot. For example, the resting state fMRI studies either applied fALFF, functional connectivity analyses, or regional homogeneity (ReHo) to assess the regional neural activity or connectivity between brain areas. Lastly, although it has been shown that the function of a brain area and its structure are related (Sui et al., 2014Toosy et al., 2004), the findings of MRI and fMRI are not completely comparable. These differences in methods and analyses add a first difficulty in comparing the results of the studies and harmonization is needed in future studies.

In addition, a limitation in the field of imaging is the small sample sizes, mainly due to the costs, leading to low power of the study and low reproducibility of results (Button et al., 2013). As discussed in more detail in the section below, the small samples in combination with potential small effects of the involvement of single brain regions in well-being can explain the failure to replicate findings.

Brain-wide association studies

Similar to the inconsistent results of our review, meta-analyses and reviews on the association of brain regions with other behaviors or complex traits reported largely inconsistent results and a wide range of potentially associated brain regions as well. For example, in a meta-analysis of resting state fMRI studies of attention deficit hyperactivity disorder (ADHD), (Cortese et al., 2021) did not find any convergence of connectivity patterns across studies. The same replication problem was shown in a meta-analysis of brain regions in relation to depression ((Müller et al., 2017). Across 99 neuroimaging experiments there were large inconsistencies in results.

In light of these wide-spread replication problems across behaviors and traits, and related to the small sample sizes used in neuroimaging research, an explanation for the diversity in results could be the small effects of the involvement of single brain regions in well-being and other human behaviors and traits. Similar to findings of genome-wide association studies (GWAS) that indicate that there are no “well-being genes” with a large effect on well-being, but many genes with small effects (Baselmans et al., 2019aOkbay et al., 2016), it is unlikely that there is a “well-being brain region” or a few brain areas that have large effects on well-being. In contrast, a wide network of brain areas that all have small effects on well-being is to be expected. Using GWAS as example, brain-wide association studies (BWAS) have been proposed to reliably and without a priori hypotheses investigate the involvement of the brain in human behavior and traits (Gong et al., 2018Marek et al., 2022). BWAS with sufficiently large sample sizes, i.e., samples with thousands of individuals, are needed improve reproducibility and the reliability of the brain–behavioral phenotype associations. Following the example of the genetic community, neuroimaging research should start large-scale collaborations to create the needed large sample sizes that are mostly missing in brain-wide association analyses (Poldrack et al., 2017).

An example of an already worldwide collaborative network is the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium, including 100k+ participants and 45 countries that focuses on disorders (Thompson et al., 2014). For Major Depressive Disorder (MDD), this consortium has already led to reproducible results, including a smaller hippocampal volume in MDD participants (n= 1728) compared with healthy controls (n=7199) and lower cortical thickness in the cingulate cortex, bilateral medial OFC and insula (Schmaal et al., 2020). Similarly, for other disorders like ADHD, bipolar disorder, and schizophrenia, robust brain correlates have been found in the large ENIGMA samples. In a recent application of BWAS to cognitive ability and psychopathology with more than 10 thousand participants, (Marek et al., 2022) showed a widely distributed circuitry of associations. These patterns indicate the involvement of many brain areas not detected in studies with the typical smaller sample sizes. This approach of well-powered brain-wide association studies is needed to investigate the brain-well-being associations as well.

Furthermore, following the successful polygenic scores in the field of genetics (Wray et al., 2007), recently, the use of polyneuro scores has been proposed (Mooney et al., 2021). Polyneuro scores are summary scores of the cumulative effect of brain-wide measures that capture effects across widely distributed brain systems and regions that are involved in different human traits (Mooney et al., 2021). Applied to ADHD, (Mooney et al., 2021) showed that such summary scores of functional connectivity across the brain have increased predictive power for ADHD symptoms. The scores explained around 8 times more variation than the variation explained by the most significant connection in the brain. However, the explained variance is still small, ~4% of the variation in symptoms is explained by the polyneuro scores.

Returning to the results of our review on well-being, this idea of brain wide associations for well-being is supported by the wide range of brain areas potentially associated with well-being. Furthermore, some specific findings of the more recent studies are in line with brain wide associations. For example, the association of neural diversity or variability in functional connectivity and higher well-being suggests that a higher complexity or more connectivity, i.e., more collaboration between brain areas leads to higher well-being (Cabeen et al., 2021). However, future brain-wide association studies are needed to support this idea for well-being and to be able to create polyneuro scores for well-being. To create the large sample sizes that are needed for brain-wide association studies, existing brain consortia could either include a well-being questionnaire, or brain and well-being researcher could combine their efforts in large consortia.

Innovative methods and analyses

The rapid development in the methods and techniques that measure brain structure and functioning at smaller temporal and spatial resolution give rise to new opportunities as well. For example, recent studies on the microstructure of the brain enables investigations of the relation between well-being and more detailed aspects of brain structures and functioning (Cabeen et al., 2021). However, also with such research to microstructures, a brain-wide approach should be applied to prevent non-replicable results.

Another direction for future research is the improvement of ecological validity in neuroscience research. At the moment, most brain imaging research is conducted in MRI scanners or in a controlled setting in the lab. This raises the question of the ecological validity, i.e., the generalizability to daily life or to which extent the results predict behaviour outside the testing environment (Matusz et al., 2019). Various solutions have been thought of to enhance the ecological validity in neuroscience. As an example of using more naturalistic stimuli and tasks, (Reggente et al., 2018) reviewed the use of virtual reality in fMRI research to memory. The results suggest the neural correlates associated with virtual reality (VR) images are more likely to generalize to real-world behaviors. This might help to find the relevant neural correlates for daily life, without introducing more variation because of uncontrollable external influences that exist in daily life. Another way to enhance ecological validity is by using portable devices, such as portable EEG and fNIRS caps, to measure neural correlates in real life and daily life (Balardin et al., 2017). Recently a portable MEG helmet has been developed as well (Boto et al., 2018). These mobile methods lead to many more possibilities to measure and understand brain activity and functioning in real-life settings and scenarios. EEG has already been recorded during walking, cycling, sports, and even skateboarding (Ladouce et al., 2019Park et al., 2015Robles et al., 2021Scanlon et al., 2019). Furthermore, people from all ages, including babies and children can participate more easily, as movement is less of an issue with the portable devices.

Related to innovations in the methods for neuroimaging, there are also rapid developments in the approaches to analyse (big) data. Using the developments in the artificial intelligence and machine learning fields, patterns can be detected in imaging data that we would not predict or expect. These approaches enable us to focus more on data-driven research instead of hypothesis driven research (Scheel et al., 2020). Using a data driving approach, (Liu et al., 2020) analysed fMRI data from major depressive patients and healthy controls. Their models could distinguish between the patients and healthy controls (accuracy=0.77) and the authors reported several brain-wide features that differed between patients and controls.


Because of the inconsistency in study design, measures, neuroimaging analyses, and reported results, a meta-analysis on the association of brain areas and well-being was mostly not possible. Conclusions should therefore be drawn with caution. Although more studies are being performed currently, future research should be harmonised to allow meta-analyses and to reach the desired sample size of thousands of participants. Whereas we did perform a small meta-analysis on the association between frontal asymmetry and well-being, the estimate was based on only a few studies and the analysis pointed towards a potential publication bias. Therefore, these results should be interpreted with caution as well.

Furthermore, it is difficult to compare earlier neuroimaging studies to the more recent studies, because of the rapid technological advancements and changing guidelines and methods in the neuroscience field. In earlier research, regions of interest (ROIs) were decided up front, whereas nowadays a voxel-wise whole brain analysis is preferred. However, as mentioned before, most brain-wide studies did not include sufficiently large sample sizes. The often small sample sizes in neuroscience research are a limitation for interpreting the results reliably, since this increases the variability and reduces statistical power. As proposed, future studies should perform power calculations before running imaging studies and start collaborations to reach the required sample sizes for brain-wide association studies (Marek et al., 2022Szucs and Ioannidis, 2020).