Intergroup Bias: Threats and Culture

Intergroup bias is pervasive through human history. Neuroscientific research has improved understanding of the neural mechanisms behind intergroup bias. Yet, with few exceptions, current neuroscientific knowledge of intergroup bias fails to inform how psychological tendencies toward intergroup bias arose in ancestral populations. We argue that future researchers should (1) use neuroscientific methods to assess how threats such as pathogens influence neural markers of intergroup bias and (2), due to their evolving in unique ecologies, compare neural responses to ingroup and outgroup members between members of collectivist and individualist cultures. Consideration of how selective pressures and cultural evolution affect neural mechanisms of intergroup bias will ultimately provide better understanding of its occurrence.

Ethnic Intergroup Bias

Intergroup bias bears responsibility for many atrocities (Yanagizawa-Drott 2014; Voigtländer and Voth 2015); it is thus important to understand how it occurs. Intergroup bias takes multiple forms including homophobia, ageism, and ethnic intergroup bias. All merit concern, but here we focus on ethnic intergroup bias (from here on referred to simply as intergroup bias). Intergroup bias has been of interest to psychologists through the last century (see Duckitt 1992; Dovidio et al. 2012), resulting in much theoretical diversity. Given the variety in existing theories, debate surrounds which perspective best explains intergroup bias.

Given its consequences, research has focused closely on how to reduce intergroup bias. Despite this, most efforts to reduce intergroup bias are still unsuccessful (Paluck and Green 2009; FitzGerald et al. 2019), with approximately 60% of intervention efforts proving unsuccessful (Aboud et al. 2012). Through elucidation of neural mechanisms underlying intergroup bias, recent research underlines the utility of neuroscientific methods (for reviews, see Amodio 2008, 2014; Molenberghs 2013; Cikara and Van Bavel 2014; Molenberghs and Louis 2018). The use of these methods has yielded considerable understanding of neural mechanisms underlying intergroup bias. We review findings from various neuroscientific techniques used thus far.

Techniques

fMRI

Functional magnetic resonance imaging (fMRI) is used to track changes in neural activity between observation of ingroup and outgroup members (see Amodio and Lieberman 2009; Molenberghs and Louis 2018, for reviews). Using fMRI, multiple cognitive processes elicit different neural responses for outgroup members. These include face processing (Phelps et al. 2000; Richeson et al. 2003; Cunningham et al. 2004; Van Bavel et al. 2008; Molenberghs and Louis 2018), theory of mind (Gallagher and Frith 2003; Adams Jr et al. 2010; Mathur et al. 2010, Cheon et al. 2011; Bruneau et al. 2012), and empathy (Xu et al. 2009; Contreras-Huerta et al. 2013). For example, Xu et al. (2009) instructed Caucasian and Asian participants to view videos of ingroup and outgroup members being pricked by a needle. Meanwhile, fMRI activity was recorded from the anterior cingulate cortex (ACC), a region associated with regulating first person pain experience, as well as empathy when observing another person’s pain. Increased activation in the ACC occurs when seeing another person being pricked by the needle, consistent with increased empathy for the person (Lamm et al. 2007; Han et al. 2009). For both Caucasian and Chinese participants, seeing ingroup members being pricked by the needle facilitated increased activation of the ACC, inferior frontal cortex and insula (all regions involved in empathy for felt and observed pain; Xu et al. 2009). This activation was reduced when both Asian and Caucasian participants saw outgroup members being pricked by the needle. This pattern of results has been observed in similar studies (Ito and Bartholow 2009; Xu et al. 2009; Avenanti et al. 2010; Chiao and Mathur 2010; Perry et al. 2010; Cheon et al. 2011; Lamm et al. 2011; Cikara et al. 2014; Cao et al. 2015; Liu et al. 2015; Han 2018).

In a different experiment (Azevedo et al. 2013), White and Black participants in Italy watched videos of White, Black, and violet colored individuals either being touched by a Q tip or being painfully penetrated with a needle. During these videos, fMRI activity in the bilateral anterior insula—a region linked to the emotional aspect of pain—was greater when participants observed same-race (i.e., ingroup) members than different-race (i.e., outgroup) members. Moreover, participants higher in implicit bias had a greater ingroup-outgroup gap in activation of the bilateral anterior insula than those lower in implicit bias. Although replication of these studies with larger sample sizes is needed, these preliminary results nonetheless provide evidence that neural responses differ depending on group membership. Such results demonstrate the utility of using fMRI in assessing neural responses to ethnic ingroup and outgroup members.

EEG

Electroencephalography is another common method used in assessing intergroup relations (for review, see Han 2018; Molenberghs 2013). Using EEG, differences in brain activity for ingroup and outgroup members are detected in processes such as empathy (Avenanti et al. 2010; Chiao and Mathur 2010; Gutsell and Inzlicht 2012; Sheng and Han 2012; Xu et al. 2009), motor action (Gutsell and Inzlicht 2010; Molenberghs 2013; Inzlicht et al. 2012; Gutsell and Inzlicht 2013), and application of fairness (Wang et al. 2017; Cikara et al. 2014). For example, Gutsell and Inzlicht (2012) recorded participants’ EEG activity as they observed videos of ingroup and outgroup members showing sadness. Participants were subsequently asked to recall a sad time during their lives (self-condition) (see Fig. 1). More overlap in neural activity indicating sadness occurred between the self and ingroup conditions than outgroup conditions, indicating an empathic preference for ingroup members.

Fig. 1
figure 1

Illustration of the procedure used by Gutsell and Inzlicht (2012). Participants were fitted with EEG caps and then (1) had their baseline neural activity measured for 2 min, (2) observed videos on a single monitor of sad ingroup and sad outgroup members, and (3) Recalled a sad time during their lives. Measured was overlap in neural activity between self and ingroup members, versus self and outgroup members

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ERP

Event-related potentials (ERP) are also used to assess differences between ingroup and outgroup members. As with other measures, differences involving empathy for pain (Ito et al. 2004), face perception time (Dickter and Bartholow 2007), and encoding of faces (Ratner and Amodio 2013; Cassidy et al. 2014) are all associated with ERP differences for outgroup members. For example, Dickter and Bartholow (2007) asked Caucasian and African American participants to undergo a modified flanker-based task (Eriksen and Eriksen 1974) where a picture at the center of the screen was accompanied by two pictures on both the left- and right-hand side of the screen (see Fig. 2). In this task, participants were asked to ignore the faces on each side of the screen (which consisted randomly presented African American and Caucasian faces). The task was ostensibly to name the gender of the person in the middle of the screen. They predicted that there would be increased interference in processing when the faces on sides of the screen were different from the one at the center of the screen in both race and gender. It was found that computation of the face in the center of the screen was different when the race or gender of the distractor (i.e., faces at the side of the screen) differed from the centrally presented face. While more research is needed, this tentatively suggests the N200 component has a functional role in differentiating ingroup and outgroup targets (see Fig. 2).

Fig. 2
figure 2

Outline of procedure from Dickter and Bartholow (2007). Participant’s neural activity was recorded as they first watched a baseline screen. Second, they watched a trial with a centrally presented target (in this example an African American female) flanked by a distractor (in this case a Caucasian Male); participants were instructed to ignore the distractor. After presentation of the stimulus, participants classified gender of the centrally presented target. There were four trial types: (1) compatible gender, compatible race; (2) compatible gender, incompatible race; (3) incompatible gender, compatible race; and (4) incompatible gender, incompatible race (seen in the figure)

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Summary of Findings

Researchers have utilized multiple research techniques and methodologies to understand neural mechanisms accompanying intergroup bias. These findings highlight group disparities in processes such as perception and other cognitive processes. However, they do not yield insight into how such disparities unfold. For example, there is no uniformity on whether these findings imply whether people think positively of ingroup members and neutrally of outgroup members or think neutrally of ingroup members and negatively of outgroup members. Moreover, they do not yield insight on why these processes are skewed toward favoring ingroup members in the first place.

Intergroup Bias and Evolution

Neuroscientific findings to date have delineated cognitive and neural mechanisms underlying intergroup bias. However, these studies do not explain why such mechanisms emerged in ancestral populations. Intergroup bias research often describes mechanisms associated with prejudicial reactions in one’s mind. For example, social identity theory (Hogg 2016; Tajfel et al. 1979; Turner et al. 1979) argues that we self-categorize ourselves to a group. We are then motivated to judge that group in a positive way to keep a positive view of ourselves. Such theories emphasize how intergroup bias develops and operates within one’s mind. However, social identity theory does not explain antecedent causes of intergroup bias in the social ecology, nor why humans developed this tendency given our unique adaptive pressures.

Humans are a social species (Dunbar 1998; Lieberman 2013). Indeed, human brain size likely increased as a function of the increasing complexity of our social relationships and interactions (Dunbar 1998). Group-based living and cooperation likely helped our ancestors ward off predators. Those of our ancestors who were cooperative and socially skilled were more likely to survive long enough to pass on their genes (Lieberman 2013; Von Hippel 2018). However, our hyper-social inclination also carries risks. Being near to others is helpful when facing a predator but also carries risk of interpersonal violence, freeloading, and pathogen transmission (Neuberg and Schaller 2016; Von Hippel 2018). Our ancestors would thus have needed to find ways to mitigate the risks brought on by increased sociality (Neuberg and Schaller 2016). Although ingroup members can cause such threats, the costs that ingroup members bring to an individual’s fitness are ultimately exceeded by the benefits. However, outgroup members by definition cannot offer the same benefits that ingroup members can (due to relative lack of interaction) and are thus more likely to be assessed as only offering risk. As such, risk aversion is more likely to be attuned to threats offered by outgroup members.

Threat Detection Systems: Development and Function

Some research has begun to address the question of why intergroup bias arose in humans in response to ancestral social environments (Neuberg and Schaller 2016). What may underlie this bias are threat detections systems geared toward threat minimization (Neuberg et al. 2011; Neuberg and Schaller 2016). Ultimately, these threat detection and management mechanisms would have allowed ancestral populations to manage threats from ingroup as well as outgroup members. However, due to the asymmetrical risk profile between the average ingroup and outgroup member, we suggest that these systems in relation to outgroup members form the basis for much contemporary intergroup bias (also see Neuberg and Schaller 2016). Here, we focus upon the influence of pathogens on the development and maintenance of intergroup bias.

Pathogens and Prejudice: Overlapping Threats

The Behavioral Immune System

Pathogens are an enduring threat to human populations (Burnet et al. 1972; Dobson and Carper 1996; Armelagos et al. 2005; Noymer and Jarosz 2008). As such, ancestral populations would have had to adopt ways to minimize the likelihood of pathogen transmission. Human immune systems have become robust to counter pathogens (Nicholson 2016), yet recent evidence also suggests the emergence of behavioral strategies to mitigate pathogen threat. Besides the biological immune system, humans also could have evolved a suite of behavioral patterns to minimize pathogen transmission (Faulkner et al. 2004; Neuberg and Schaller 2004; Neuberg et al. 2011; Schaller and Park 2011; Murray and Schaller 2016; Neuberg and Schaller 2016). This suite of behaviors dubbed the behavioral immune system (BIS). Feeling disgust may be an emotive strategy to motivate individuals to implement behaviors which mitigate pathogen transmission. If this were true, it would mean the appearance of stimuli inferring the presence of pathogens should temporarily increase the feeling of disgust. Extant research suggests this is exactly what occurs. Observation of dirty sponges (Faulkner et al. 2004), asymmetrical faces (Young et al. 2011), facial blemishes (Ackerman et al. 2009), and obese individuals (Vartanian et al. 2016) all increase feelings of disgust (see Neuberg and Schaller 2016).

These findings suggest the BIS is attuned to mitigate the likelihood of infectivity that others might pose to us. To determine this likelihood, ancestral populations would have needed to base judgments on who poses a threat of infection on cues which might alter such likelihood estimations. It would thus be expected that groups containing such cues would be more likely to be considered a pathogen risk. Indeed, groups carrying heuristic ties to infection (such as those above) are more likely to be judged as offering a pathogen carrying threat. Cues seemingly used to make such an assessment range from older age (potentially because older people have weakened immune systems and thus are more likely to carry pathogens; see Duncan and Schaller 2009), atypical hygiene practices (Faulkner et al. 2004), and foreign individuals from pathogen dense ecologies (Ji et al. 2019). For example, Ji et al. (2019) assessed the impact of temporary disgust elevation or chronic sensitivity to disgust influence decisions to let immigrants into their country. Across two experiments, they found that exposure to pathogen connoting stimuli or neutrally affective stimuli had no effect on decisions to let immigrants into their country. However, Ji et al. (2019) also found that people who were chronically worried about pathogen transmission predicted decreased likelihood to let immigrants into their country. This effect was specific to immigrants who were known to be from pathogen dense ecologies, but not for immigrants for which the origin was unknown. This suggests that the BIS operates to discriminate toward outgroups insofar as they are thought to offer the threat of pathogen transmission.

This research suggests that perception of outgroup members combined with relevant heuristic cues increases the likelihood that they would be considered a risk of pathogen transmission, prompting the feeling of disgust activated by the behavioral immune system (Navarrete and Fessler 2006; Oaten et al. 2009; Neuberg and Schaller 2016). There are two primary reasons for this. First among these is a potential byproduct of how the physical (or classical) immune system functions. We lived with only other ingroup members for much of our evolutionary history (Neuberg and Schaller 2016). Our bodies thus had time to develop immunity to pathogens our ingroup members had. It therefore makes sense that our BIS would be more readily alarmed by the presence of outgroup members. For example, most of the Incas and Aztecs died from pathogens that the Spanish colonists brought with them (Lovell 1992). Spanish colonizers had faced the threat of smallpox in Europe for centuries and thus had time to build immunity to it. Yet given the Incas and Aztecs had not encountered smallpox before they had no such immunity (Lovell 1992), this lack of physical immunity may have resulted in the increased attuning to cues of foreign appearance by way of inferring whether someone offers a pathogen threat.

Second among the reasons heuristic pathogen cues could lead to increased intergroup bias is the inherent lack of clarity present during observation of an outgroup member. Mere perception of someone (e.g., an outgroup member) does not provide accurate information on the cultural and hygienic norms and practices of their culture. To mitigate pathogen risk, individuals may therefore assume that the perceived person’s cultural norms concerning hygiene and cultural practice are not as stringent as their own. Indeed, this unsurety concerning outgroups hygiene practices may be a driver for increased intergroup bias (Karinen et al. 2019). Through these dual pathways, ancestral populations may have become more likely to assume outgroup members (particularly with physical cues indicating the presence of pathogens) pose fitness-related threats. Experimental evidence suggests this is the case (Faulkner et al. 2004; Navarrete and Fessler 2006). This combination of experimental and historical evidence supports two claims. First, people unconsciously look for cues indicating that a person carries infectious pathogens. Second, people use (ethnic) appearance as a cue to determine whether someone might carry harmful pathogens.

The Behavioral Immune System and the Classical Immune System

At a physiological level, the BIS and the brain are shown to work in tandem (see below). However, the roles they play in relation to managing pathogen risk can be delineated (Ackerman et al. 2018). In the literature, this is broadly defined as the proactive versus reactive outputs the BIS generates (Schaller and Park 2011; Ackerman et al. 2018). Reactive output typically occurs in response to an immediate threat (Tybur et al. 2013; Ackerman et al. 2018) upon perception. Meanwhile, proactive outputs of the BIS are geared at the persistent management of pathogen threat in the long term (e.g., selecting for facial symmetry in a mate (Gangstead and Buss 1993). As such, the BIS manages threats in a flexible and dynamic manner—both in reaction to immediate pathogen connoting stimuli and longer term management of pathogen threats (Tybur et al. 2013; Ackerman et al. 2018).

Indeed, recent work has shown how reactive responses manifest in the brain. The insular cortex (insula) is an area heavily linked to experiencing disgust and seeing others feel disgust (Wicker et al. 2003; Jabbi et al. 2008; Uddin et al. 2017). For example, Wicker et al. (2003) had participants inhale foul smelling odors and then watch videos of other people experiencing disgust. It was found that feeling and viewing others feel disgust activated the left and right anterior insula (indicating experience of disgust) and increased activity in the anterior cingulate cortex (involved in the experience and observation of aversive stimulus). These results show how specific neural activity may yield information on how downstream judgment, such as judging someone as a pathogen threat, ultimately arise.

Experience disgusting stimuli is also shown to elicit non-neural physiological responses. Measurements such as facial muscle activation (Vrana 1993), cardiovascular activity (Rohrmann and Hopp 2008), autonomic activation (Ottaviani et al. 2013), and white blood cell count (Schaller et al. 2010) are all methods used in determining the physiological correlates of disgust responses. For example, Schaller et al. (2010) had participants attend to either photos of guns or photos of people with physical signs of infectious disease. It was found that participants who observed the photos of the people with signs of infection had elevated white blood cell counts (indicating increased immune response) compared to participants who observed the photos of the guns. This result was indicative of the relationship between the BIS and classical immune system, such that perception of disease cues immediately causes the body to respond to potential pathogen threat. As such, these results suggest a symbiotic relationship between the physical and behavioral immune systems, which combine to help organisms avoid infection. The extant literature on the relationship between the BIS and the classical immune system offers two key claims for our purposes here. First, they mutually coalesce to enable organisms to manage pathogen threats in the short and long term. Second, physiological and neural measurements of felt disgust can be used as a reliable proxy for determining activation of the BIS (in particular reactive responses).

Bias and the Smoke Detector

What remain unknown are the mechanisms by which these psychological and physical processes are set in motion. However, mere observation of another person does not reliably inform if they genuinely pose a threat of pathogen transmission (Neuberg and Schaller 2016). Threat detection systems such as the BIS are often inaccurate. They provide some true positives (we correctly perceive someone as a threat), but they evoke many false positives (we perceive someone as a threat when they are not). This leaves the question of why evolution endowed us with these threat detection systems when they are often entirely inaccurate.

From an evolutionary perspective, incorrect identification of a person as a pathogen threat when they are not is not as costly to individual fitness as incorrectly identifying a person as not a threat when they are. This system is analogous to a modern smoke detector (Haselton and Buss 2000; Nesse 2005; Neuberg and Schaller 2016). Smoke detectors are made to be highly sensitive to smoke in order to avoid missing a fire. Likewise, the BIS may work in a way to be so sensitive to threats that it is safer to assume someone is infectious when they are not, to eliminate the possibility that we miss someone who is actually infectious. By design, these systems work in a way so that the default position is to assume those in outgroups are more likely than ingroup members to pose a threat, allowing formation of biased responses to outgroups (Haselton and Buss 2000; Neuberg and Schaller 2016).

If threat detection systems did work this way, contexts accentuating pathogen threat should elevate intergroup bias. This is, however, different to more readily forming associations between outgroup members and physical or pathogen threats, which was discussed in the previous section. This is precisely what is observed. Showing participants pathogen connoting stimuli predicts increased bias to same sex attracted people compared to affectively neutral contexts in heterosexual participants (Tapias et al. 2007; Taylor 2007; Dasgupta et al. 2009; Cunningham et al. 2013; Liu et al. 2015). Most studies so far observe same sex attracted people as the “outgroup,” but this effect is also observed with ethnic outgroup members (Brown et al. 2019; Klavina et al. 2011; Marshall and Shapiro 2018). For example, Klavina et al. (2011) instructed Dutch Caucasian participants to observe either disgust inducing or affectively neutral pictures. Participants in both conditions then took an Implicit Association Test (IAT; Greenwald et al. 1998) with other Dutch Caucasians as the ingroup and Italians as the outgroup. Participants in the disgust condition had higher implicit bias scores toward the Italians than those in the neutral condition. Findings like this suggest that presenting pathogen connoting stimuli increases bias toward outgroups. These findings indicate that outgroup members increase our sensitivity to pathogens and that temporary elevation of these emotions facilitates increased intergroup bias. In this way, a positive feedback loop may be emerging where threat sensitivity to pathogen threat increases intergroup bias, which in turn cultivates the association between this threat type and outgroup members, leading to formation and proliferation of biased responses.

Collectivism and Individualism

Threat Response and Cultural Values

From the evidence we have discussed, it is clear that in order to manage the threat of pathogens, ancestral populations seem to have adopted behavioral strategies at the individual level. However, a growing literature also suggests that culture could be shaped by the need to manage pathogens. Indeed, emerging evidence suggests that intergroup bias can unfold in different ways depending on cultural norms and practices. One dimension along which cultures fall is the individualism-collectivism spectrum. Individualist cultures prioritize individual goals, including autonomy and free choice. As such, the needs of individuals take precedence over group level needs (Triandis 2005), meaning each induvial construes themselves at autonomous. Collectivist cultures instead prioritize group level needs such that social interactions are primarily characterized by shared obligation and compliance. Individuals in these cultures thus form a self-construal primarily as it relates to the group (Green et al. 2005; Schwartz 2006). Cognitive operations such as visual attention (Lin and Han 2009; McKone et al. 2010; Alotaibi et al. 2017), face processing (Blais et al. 2008; Kelly et al. 2011; Miyamoto et al. 2011; Tardif et al. 2017), and neural responses to fearful faces (Moriguchi et al. 2005; Adams Jr. et al. 2010; Adams Jr et al. 2010; Geangu et al. 2016) are all moderated by the effect of cultural orientation of individualism-collectivism.

Given these cultural differences in the cognitive processing, it follows that members of individualist-collectivist cultures could respond differently to pathogen threats. Kim et al. (2016) examined how the threat of Ebola was differentially processed across people from collectivistic and individualistic cultures. Specifically, they assessed “perceptions of vulnerability to Ebola” (Kim et al. 2016, p. 935), “ability to protect one’s self” (Kim et al. 2016, p. 935) from Ebola, and “xenophobic tendencies” (Kim et al. 2016, p. 935). They found that people higher in collectivist orientations had higher scores on perceived vulnerability to Ebola than those with individualist orientations. Results such as these suggest that individuals from collectivist-individualistic cultures could respond differently to pathogen connoting stimuli. As such, it is unlikely that threats and bias are likely to be perceived and carried out uniformly across cultures.

Adoption of Collectivist Behaviors Serving a Pathogen-Protective Function

Research suggests that insofar as people perceive themselves to be vulnerable to pathogens, they typically adopt attitudes which serve as behavioral buffers to pathogen transmission (i.e., attitudes that are typical of collectivist cultures; Tybur et al. 2016). Consistent with this, collectivist cultures are more likely to emerge in areas with an increased historical prevalence of infectious disease (Clay et al. 2012; Fincher et al. 2008). This would seem to be due to collectivistic behaviors serving a protective function against pathogens. Evidence for this comes in the form of cross-national data suggesting a strong association between historical pathogen prevalence and adoption of collectivist values (Chiao and Blizinsky 2010; Fincher et al. 2008; Thornhill et al. 2010). Members of collectivist cultures also show less openness to experience and extraversion (Schaller and Murray 2008; Thornhill et al. 2010), heightened family and religious loyalty (Thornhill et al. 2010), and higher conformity (Fincher et al. 2008; Murray et al. 2011). This suggests that behaviors typical of collectivist cultures serve to increase conformity and ingroup cohesiveness, allowing more effectiveness in deterring novel outgroup pathogens. For example, Tybur et al. (2016) found that across 30 nations (n = > 11,000), the prevalence of pathogens predicted adoption of behaviors that lower the likelihood of pathogen transmission (e.g., traditionalism, an aspect of social conservatism which relates to adherence to group norms; Tybur et al. 2016). They also found that higher sensitivity to disgust predicted stronger endorsement of traditionalism between individuals. These findings suggest that norms such as social compliance, higher ingroup loyalty, and hierarchical norms prevalent in collectivist cultures may have arisen due to their effectiveness in warding off pathogens. These behaviors are thus adaptive insofar as members of the culture work collectively to mitigate existing threats in the local ecology. As such, it follows that collectivist cultures could adopt different behaviors to outgroups perceived to offer a risk of pathogens. In this way, pathogens may help shape cultural norms, which in turn affect how individualism these cultures respond to perceived pathogen threat.

Collectivism-Individualism and Intergroup Bias

It is proposed that a byproduct of the increased ingroup conformity present in collectivist cultures that pathogen connoting cues would increase intergroup bias more for members of collectivist cultures. However, extant literature testing these hypotheses carries mixed results. Some research finds collectivism can be predictive of intergroup bias (Fujimoto and Härtel 2004; Fischer and Derham 2016; Gouveia 2011; Kim et al. 2016), whereas it also finds that individualist cultures can be more predictive of intergroup bias (Cashdan and Steele 2013; Jasielska et al. 2018). Cashdan and Steele (2013) suggested that cultures in pathogen dense localities typically socialize children according to more collectivist values but found no evidence of a link between pathogen prevalence and intergroup bias. Kim et al. (2016) assessed how individual orientation toward collectivism-individualism might predict prejudice as a response to Ebola. They found that higher trait-level vulnerability to disease predicted more xenophobic attitudes, and this was moderated by collectivism-individualism. In other words, the relationship between increased vulnerability was more apparent in participants with higher individualism scores and lower collectivism scores. In turn, this relationship was mediated by the extent to which people felt protected from the threat of Ebola. This effect was mimicked at state level collectivism levels (the first set of results was at the individual differences level).

These results suggest that collectivist norms at the individual and group level may make people less biased toward outgroups in disease salient contexts due to the increased feeling of safety offered by increased ingroup cohesion. Perhaps collectivist cultures, given their cultural propensity to protect from the threat of pathogens, are more susceptible to pathogen connoting cues, but due to the perceived protection their ingroup offers, there is no need for increased wariness toward outgroups. Conversely, it could be that collectivism only protects from intergroup bias insofar as collectivist practices make people feel protected from the pathogen threat. Future research should compare these hypotheses and also compare how threat cues (such as pathogen and physical danger cues) proliferate an increased bias for ingroup members or an increased dislike of outgroup members. For example, researchers could compare how individuals from collectivist and individualist cultures show differences in neural activity in response to pathogen cues, and the degree to which this is predictive ingroup love or outgroup derogation (see Fig. 3).

Fig. 3
figure 3

Example of possible relationships between threat type, individualism-collectivism, and ingroup love outgroup hate

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Summary and Future Directions

There is much scope for future neuroscientific research to assess how individualist-collectivist norms (at the individual and group level) may be differentially impacted by threat types. First, future studies could assess how the feeling of closeness and identification with one’s group (i.e., ingroup identification and identity identification—how much they identify with their culture vs how close they feel to their ethnic identity) affect intergroup bias under threat-salient circumstances. Previous studies do not reliably inform whether greater identification with one’s cultural or ethnic group is impacted by individualism-collectivism and how this is impacted by ecological threats. Moreover, it does not inform how such threats then affect downstream processes such as intergroup bias. Second, as acknowledged by Kim et al. (2016), the current literature does not inform on the causal direction between endorsement of collectivism-individualism and response to pathogen threat. In other words, it remains unknown whether people identify more with collectivist values in threat-salient contexts or do collectivists respond more readily to threat-salient contexts. Finally, future studies should use physiological measures to parse the relationship between physiological responses (whether it be arousal or brain activation patterns) and explicit bias. In the studies discussed so far, questionnaires are typically used to measure bias. This does not help to identify the causal direction between threat type, physiological response, and intergroup bias (see Fig. 4). Physiological measures of intergroup bias such as EEG, fMRI, and EMG could all be used to parse which physiological processes are associated with different intergroup processes and how these processes are impacted by top-down cognitive processes such as self-construal.

Fig. 4
figure 4

Proposed model for neuroscientific research to test relationship between threat type, the neural/physiological response to the threat, and the degree to which this facilitates or predicts subsequent bias

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Conclusion

Utilizing social neuroscience has yielded considerable insight into the neural correlates of intergroup bias. However, such insight can only take us so far. Here we reviewed the literature of neuroscientific methods for investigating intergroup bias. We then reviewed a literature which suggests intergroup bias emerged due to individual and fitness related threats in ancestral populations. We then suggested that future researchers should (1) use neuroscientific methods to assess how threats such as pathogen salience influence neural markers of intergroup bias and (2) compare this between collectivist and individual cultures due to their evolving in unique ecologies. Future researchers should more seriously consider the mutual influence of evolutionary selective pressures, consequent cultural evolution of individualism-collectivism, and biological mechanisms pertaining to intergroup bias. Doing so may yield many novel hypotheses which will allow a fuller account of the selective pressures driving the development of intergroup bias and its biological underpinnings. For example, researchers could test the extent to which members of collectivist cultures show activation in the insula cortex (an area strongly associated with felt and observed disgust; Jabbi et al. 2008; Uddin et al. 2017; Wicker et al. 2003) in response to pathogen connoting cues compared to members of individualist cultures. Researchers could then compare the extent to which neural activity in the insula predicts measurements of intergroup bias. This would test the pathogen prevalence theory of collectivism and the idea of a behavioral immune system that drives intergroup bias. Understanding yielded for such research could have implications in policy, educational, and clinical settings.