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Excessive empathy, social cues and adaptive behavior evaluation

Excessive empathy, social cues and adaptive behavior evaluation



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An article by Gunnar Bartsch of Julius-Maximilians-Universität Würzburg, JMU started me on this line of inquiry.

The original source is no longer available but has been reproduced at ScienceDaily (Bartsch, n.d.)

We generally accept the concept of Compassion Fatigue and Secondary Trauma as an individual choosing to over-do it with regard to empathy and hence the recommendation of better boundaries and self care. I have many studies… saying our Aspergers and ADHD kids have problem with social skills because of low empathy what if the kid falls at the high empathy end of the spectrum?

What research is being done in psychology and/or neuroscience regarding excessive empathy and altruism as a condition and the resulting adaptive behavior patterns? I want to know more.

References

Bartsch, G. (n.d.) Excessive empathy can impair understanding of others. ScienceDaily. Retrieved from https://www.sciencedaily.com/releases/2016/04/160428094950.htm


In the Light of Evolution: Volume VII: The Human Mental Machinery (2014)

ROBERT M. SEYFARTH *&Dagger AND DOROTHY L. CHENEY &dagger

To understand the evolution of a Theory of Mind, we need to understand the selective factors that might have jump-started its initial evolution. We argue that a subconscious, reflexive appreciation of others&rsquo intentions, emotions, and perspectives is at the roots of even the most complex forms of Theory of Mind and that these abilities may have evolved because natural selection has favored individuals that are motivated to empathize with others and attend to their social interactions. These skills are adaptive because they are essential to forming strong, enduring social bonds, which in turn enhance reproductive success. We first review evidence from both humans and other animals indicating that reflexive and reflective mental state attributions are inextricably linked and play a crucial role in promoting affiliative social bonds. We next describe results from free-ranging female baboons showing that individuals who show high rates of affiliative behavior form stronger social bonds with other females. These bonds, in turn, are linked to fitness. We then provide data from three different types of social challenges (male immigration, changes in grooming behavior after the death of a close relative, and responses during playback experiments), suggesting that females who manifest high rates of affiliative behavior may also be more motivated to anticipate challenges, react adaptively to setbacks, and respond appropriately to social interactions.

Departments of * Psychology and &dagger Biology, University of Pennsylvania, Philadelphia, PA 19104. &Dagger To whom correspondence should be addressed. E-mail: [email protected]

Do animals have a Theory of Mind (ToM)? Answers to this question have tended to focus on two properties that might characterize a cognitive process. First, is an animal&rsquos recognition of other individuals&rsquo mental states reflexive, and therefore perhaps immediate and unconscious? Or is it reflective, and therefore more likely to be ruminative and conscious? Second, to what kinds of mental states are animals attentive: more rudimentary psychological states, like another individual&rsquos gaze direction or its intentions, or more complex states, like another individual&rsquos knowledge or beliefs? These distinctions are not easy to draw, even in humans, where reflective, conscious mindreading about others&rsquo knowledge and beliefs is built on and develops gradually from reflexive, unconscious recognition of, for example, another&rsquos direction of gaze (Onishi and Baillargeon, 2005 Apperly, 2012).

There is considerable evidence that many animals are reflexively attuned to other individuals&rsquo gaze, intentions, and emotions however, the degree to which they are also reflectively aware of others&rsquo knowledge and beliefs is less clear (Cheney and Seyfarth, 2007). Problems in assessment arise in part because whenever an animal behaves in ways that suggest an understanding of another&rsquos knowledge, its behavior can often also be explained by simpler mechanisms, including learned contingencies. A chimpanzee (Pan troglodytes) who takes food that a rival cannot see might do so because she understands the relation between seeing and knowing or because she has learned the behavioral rule that a rival is motivated to defend food at which he is looking. Although experiments have attempted to distinguish between these explanations (Kaminski et al., 2008 Bugnyar, 2011 Crockford et al., 2012 MacLean and Hare, 2012), results have not been easy to interpret. At the very least, they suggest that animals&rsquo understanding of others&rsquo psychological states is quite different and perhaps less subject to conscious reflection than adult humans&rsquo. Whatever the explanation, it is clear that attempting to identify precise, definitive benchmarks of mental state attribution in animals has proved to be more elusive and less productive than first hoped.

Here, we take a slightly different approach to the question of mental state attribution in animals and consider the selective factors that might have favored the evolution of a rudimentary ToM. We begin by assuming that a full-blown ToM evolved from more rudimentary, reflexive forms that were themselves adaptive in their own right. As a first step in understanding the evolution of a ToM, therefore, we need to understand the selective factors that might have jump-started these rudimentary forms. We argue that a subconscious, reflexive appreciation of others&rsquo intentions, emotions, and perspectives lies at the roots of even the most complex forms of ToM and that these abilities first evolved because natural selection favored individuals that were motivated to attend to other individu-

als&rsquo social interactions and empathize with them. These skills were favored by selection because they are essential to forming strong, enduring social bonds, which in turn have been shown to enhance reproductive success. We therefore propose that the evolution of a ToM ultimately derives from its role in facilitating the formation of social bonds.

We first review evidence from both humans and other animals indicating that reflexive and reflective mental state attributions are inextricably linked and play a crucial role in promoting affiliative social bonds. Then, using data on wild female baboons (Papio hamadryas ursinus), we suggest that individual variation in the motivation to attend to social interactions and react to social challenges is positively correlated with measures that have previously been shown to be linked to the formation of social bonds and, ultimately, enhanced reproductive success.

REFLEXIVE AND REFLECTIVE EMPATHY IN ANIMALS AND HUMANS

Any attempt to determine whether an animal does or does not understand what another individual knows or thinks is inevitably confounded by the fact that the reflective processes associated with higher levels of ToM are closely linked to&mdashand often hard to distinguish from&mdashthe more automatic, reflexive processes that underlie them (de Waal, 2012 Hecht et al., 2012). Although we are consciously aware of the distinction between our own and others&rsquo mental states, we are often unaware of the many cues on which this awareness is based. For example, although higher cortical areas, like the prefrontal cortex, are activated when a human attempts to determine whether another individual can see something, initial responses to gaze direction and goal-directed behavior also activate more primitive areas of the brain, including the superior temporal sulcus (STS) and the amygdala. In both humans and rhesus macaques (Macaca mulatta), the STS is particularly sensitive to the orientation of another individual&rsquos eyes (Jellema et al., 2000 Klein et al., 2009).

The same is true of intentional behavior. Although we have conscious access to our reflections about whether someone&rsquos actions are accidental or intentional, many of the neuronal responses that contribute to our eventual decision are more subconscious. In both humans and monkeys, mirror neurons in the inferior parietal lobule are activated when an individual both performs a specific action and he observes someone else perform that action. Significantly, many neurons begin to fire before the other individual actually performs the action, suggesting that these neurons encode not only the specific motor act but also the actor&rsquos intentions (Fogassi et al., 2005 Rizzolatti and Fabbri-Destro, 2009). Thus, our ability to recognize that gaze has informative content, or to consider whether behavior

is intentional, depends crucially on automatic, reflexive neuronal activity of which we are largely unaware.

Similar results emerge in studies of empathy. Reflective, explicit empathy involves the ability to recognize emotional states like grief or fear in others without necessarily experiencing the same emotions oneself (Hecht et al., 2012). However, reflective empathy evokes activity not just in the cortex but also more primitive areas of the brain shared with many animals, including the midbrain, the brainstem, and endocrine systems associated with reactivity, reward, and social attachment (Decety and Jackson, 2004 Decety, 2011). Although we can distinguish between our own and others&rsquo emotions, representations of emotions like pain, disgust, and shame in others also activate many of the same areas of the brain that are activated when we experience or imagine the same emotions ourselves (Rizzolatti and Fabbri-Destro, 2009). Feeling sympathy for or being nice to others is emotionally rewarding in part because it facilitates the release of dopamine, a neurotransmitter associated with personal reward (Decety, 2011). Trust, empathy, and sensitivity to others&rsquo affective states are all facilitated by neuropeptides associated with attachment, maternal behavior, and pair bonding in animals, particularly oxytocin (Carter et al., 2008 Snowdon et al., 2010). Thus, even the most reflective forms of empathy in humans are derived from and still strongly linked to more rudimentary forms.

Similarly, reflective imitation involves the ability to recognize the goals and intentions of another and to understand that, to achieve the same goal, one must copy that individual&rsquos actions. Human culture depends crucially on this ability, which is also shown to some degree by the great apes (Buttelmann et al., 2007). Even humans, however, are largely unaware of many of the behaviors in others that they routinely mimic. Like some animals, we have a reflexive, unconscious tendency to mimic the postures, mannerisms, and behavior of individuals with whom we are interacting.

As already noted, in the motor domain the same mirror neurons are activated when an individual performs a movement as when he observes another engaged in that movement. Similarly, both human and nonhuman primates reflexively follow the gaze of others (Shepherd et al., 2009), and both human and macaque neonates copy others&rsquo facial expressions (Meltzoff and Moore, 1977 Ferrari et al., 2006). The fact that such mimicking is associated with empathy is exemplified by the phenomenon of contagious yawning. It is well known that viewing others yawn can elicit spontaneous yawning in oneself. Even this apparently reflexive response, however, seems to vary according to an individual&rsquos sensitivity to more reflective behavior, including face recognition and understanding of others&rsquo mental states (Platek et al., 2003). Spontaneous yawning is rare or absent in children with autism spectrum disorder (Senju et al., 2007 Helt et al., 2010).

It also occurs at higher frequencies among kin and friends than among strangers, suggesting that contagious yawning is linked to and may also promote affiliation (Norscia and Palagi, 2011). These observations are not limited to humans: chimpanzees are also more likely to yawn in response to the yawns of familiar, as opposed to unfamiliar, individuals (Campbell and de Waal, 2011).

A variety of other observations on what has been termed the chameleon effect (Chartrand and Bargh, 1999) supports the view that reflexive mimicry is linked to the formation and maintenance of social bonds and has been favored by evolution because it promotes affiliation (Lakin et al., 2003). Experiments suggest that people unconsciously mimic others when attempting to foster rapport and increase their frequency of mimicry when they are excluded from a group (Lakin and Chartrand, 2003 Lakin et al., 2008). Being imitated increases helpful and affiliative behavior (Van Baaren et al., 2004) and activates areas in the brain associated with reward processing (Kühn et al., 2010). In contrast, not being imitated increases cortisol levels (Kouzakova et al., 2010).

Similar observations have been obtained in nonhuman primates. Captive capuchin monkeys (Cebus apella) are more willing to approach and exchange tokens with a human who mimics their actions than one who does not (Paukner et al., 2009). Male chimpanzees&rsquo long-distance pant hoots become more similar acoustically as individuals spend more time together (Mitani et al., 1999 Crockford et al., 2004), suggesting that call convergence is associated with, and may even promote, social affiliation.

In practice, it is almost impossible to distinguish reflective empathy from more reflexive forms and learned negative associations (de Waal, 2012). This problem is not surprising given neurological evidence that the two are closely linked. In an early experiment specifically designed to examine whether one monkey would respond to another&rsquos distress, rhesus macaques were trained to pull chains to obtain a food reward. The apparatus was then rigged so that a monkey in an adjacent cage received a shock each time a particular chain was pulled. Most of the monkeys soon stopped pulling the chain that delivered the shock, even though doing so deprived them of a reward. They were especially likely to avoid the chain if they had previously received shocks themselves (Masserman et al., 1964 Wechkin et al., 1964). Although the monkeys&rsquo responses might at first be interpreted as evidence for reflective empathy, it seems as likely that they became distressed when they saw the other monkey being shocked because it was linked to a negative association for themselves. However, because even the most reflective forms of human empathy also evoke activity in more reflexive, primitive brain systems, these alternative explanations may be impossible to disambiguate.

In a more recent experiment, macaques were given the option of delivering a reward to themselves, another monkey, or no one. Although subjects preferred to reward themselves over others, they nonetheless opted to reward their partner if the alternative was to reward no one. This preference was especially true if the partner was familiar (Chang et al., 2011). Significantly, the same brain areas that are activated in humans during such exchanges were also activated in monkeys (Chang et al., 2013), and again&mdashas in humans (Guastella and MacLeod, 2012)&mdashthe monkeys&rsquo vicarious reinforcement was enhanced if they first inhaled oxytocin (Chang et al., 2012).

Finally, in another experiment rats were placed in an arena with a cagemate trapped in a translucent tube (Ben-Ami Bartal et al., 2011). The free rats quickly learned how to open the tube to liberate their cagemates, and they continued to do so even when given an alternative option to open a tube containing chocolate. (In the latter case, the rat opened both tubes and shared the chocolate.) It is possible that the free rats&rsquo responses may have been provoked in part by their own elevated stress at hearing their cagemates&rsquo alarm calls. However, given neurological evidence that witnessing distress in others activates many of the same brain areas as experiencing distress oneself, this distinction becomes difficult to disambiguate.

In sum, a variety of evidence suggests that reflexive empathy and imitation in both humans and other animals have evolved because they promote affiliation and social bonding. Joint attention and joint action activate areas of the brain associated with the processing of reward, and they are facilitated by the release of oxytocin. Importantly, what seems to be rewarding to animals is not physical contact per se but the specific identity of the social partner. In socially monogamous tamarins (Saguinus oedipus), strongly bonded pairs exhibit higher oxytocin levels than more weakly bonded pairs (Snowdon et al., 2010). Among wild chimpanzees, urinary concentrations of oxytocin are higher after individuals groom with a closely bonded partner (both kin and nonkin) than with a less closely bonded partner (Crockford et al., 2013). Evidently, grooming with a close friend or relative is more emotionally rewarding than engaging in the same behavior with a less preferred partner.

If empathy and affiliation have indeed been under strong selective pressure and lie at the roots of ToM, it should be possible to link these behaviors to fitness. Indeed, there is growing evidence that such a link can be made, because empathy and affiliation help individuals to form and maintain social bonds, and these bonds promote fitness.

Strong, enduring social bonds are a distinctive and adaptive feature of many animal societies. Such bonds are not limited to those formed by heterosexual mated pairs but extend to same-sex bonds formed between both kin and nonkin. Correlations between same-sex bonds and measures of

health or reproductive success have been documented in rodents, horses, dolphins, chimpanzees, baboons, and humans (Seyfarth and Cheney, 2012). Strong bonds buffer individuals against stress and disease and perhaps as a result are correlated with longevity and offspring survival.

These observations suggest that natural selection has favored empathy and imitation, because they are part of the cognitive and emotional skills that an individual needs to recognize others&rsquo social relationships, understand their motives and intentions, and keep track of, anticipate, and react adaptively to social events and challenges. We now explore these questions in more detail, focusing on data derived from a long-term study of wild baboons living in the Okavango Delta of Botswana.

EMPATHY, SOCIAL BONDS, AND REPRODUCTIVE SUCCESS IN WILD FEMALE BABOONS

Like many other species of Old World monkey, baboons live in large social groups (

75 individuals) composed of both kin and nonkin. Males emigrate from their natal group at adulthood. Females assume dominance ranks similar to their mothers&rsquo, and the female dominance hierarchy typically remains stable for many years (Cheney and Seyfarth, 2007). Females form strong grooming relationships with a subset of other females, the strongest bonds occurring among close matrilineal kin (Silk et al., 2012).

Despite the fact that high-ranking females enjoy priority of access to resources such as food and mates, female reproductive success in baboons&mdashlike female reproductive success in humans and other animals&mdashis influenced less by a female&rsquos dominance rank than by the strength and stability of her bonds with other females. We evaluated females&rsquo bond strength using two indices of sociality. The first index, the Composite Sociality Index (CSI), measured dyadic bond strength based on females&rsquo rates of approaches, groom presents, grooming initiations, and grooming durations with other females. The second index, the Partner Stability Index (PSI), measured females&rsquo retention of their top three partners across years. Over a 17-year period, offspring survival was significantly positively correlated with the CSI (Silk et al., 2009), whereas longevity was significantly correlated with a combination of the strength and stability of females&rsquo relationships with their top partners (Silk et al., 2010). Females also experienced lower stress (as measured by fecal glucocorticoid metabolites) when their grooming network was more focused (Crockford et al., 2008). Thus, the strength and stability of females&rsquo social partners were correlated with several measures of fitness. Interestingly, however, variation in the strength of social bonds was not fully explained

by obvious demographic attributes like dominance rank or availability of kin. Although females established their closest bonds with kin, kin varied in the strength of their bonds, and some females without close kin established close bonds with others.

These observations suggest that some individuals are more motivated or skilled than others at establishing and maintaining social bonds and that variation in patterns of affiliation that are correlated with fitness may result in large part from variation in personality styles. We therefore attempted to determine whether different patterns of behavior were more or less associated with social bond strength.

Personality Styles and Social Bond Strength

We applied exploratory principal component analysis to the behavior of 45 female baboons over a 7-year period (Seyfarth et al., 2012). To construct the components that were used to identify personality dimensions, we calculated annual rates for several behaviors not considered in previous analyses of sociality. These behaviors included the frequency that females were alone, the rate at which they were friendly to other females, the rate at which they were aggressive to other females (corrected for dominance rank), and the frequency with which they grunted when approaching higher- and lower-ranking females. Among baboons, grunts serve as signals of benign intent and facilitate friendly interactions (Cheney et al., 1995). When females grunt to higher-ranking individuals, they are less likely to receive aggression. Conversely, when females grunt to lower-ranking individuals, those individuals are less likely to show submissive behavior. We were especially interested in the frequency with which females grunted to lower-ranking individuals, because such vocalizations do not benefit the signaler in any obvious way. Instead, they seem to function primarily to alleviate the anxiety of the recipient.

Our analysis identified three relatively stable personality dimensions, each characterized by a distinct suite of behaviors that could not be explained by dominance rank or availability of kin. Females scoring high on the Nice dimension were friendly to all females and often grunted to lower-ranking females, apparently to signal benign intent. Aloof females were aggressive, were less friendly, and grunted primarily to higher-ranking females. Loner females were often alone, were relatively unfriendly, and also grunted most often to higher-ranking females (Seyfarth et al., 2012). The baboons themselves apparently recognized these differences, because they approached females who scored high on Nice at high rates but approached females scoring high on Aloof and Loner at much lower rates (Seyfarth et al., 2012, table 1). Personality designations remained relatively stable over time.

Importantly, the different personality attributes were associated in different ways with measures of fitness. Females who scored high on Nice had strong social bonds (high CSI scores) and stable preferences for their top partners. Females who scored high on Aloof had lower CSI scores overall but very stable preferences with their top partners. In contrast, Loner females had significantly lower CSI scores, less stable partner preferences, and significantly higher glucocorticoid (GC) levels (Seyfarth et al., 2012, table 2).

These results suggest that there are costs and benefits associated with particular personality characteristics. For example, selection would seem to act against females scoring high on the Loner dimension, because these individuals were under more stress than others and formed weaker bonds that yielded low CSI scores and low partner stability. This observation begs the obvious question of why any female would adopt the Loner strategy. Loners were not isolated and unfriendly solely because of their subordinate status or lack of kin although these demographic factors contributed to their scores on this component, their behavior exacerbated them. Moreover, some Loners did have close kin, whereas other females who consistently scored high on Nice did not. If Loners were often the victims of circumstances, what skills or motivation allowed some individuals and not others to overcome these circumstances?

In sum, female baboons varied not only in the strength and stability of their bonds but also in the personality traits associated with these bonds&mdashparticularly the ability or motivation to interact with others.

To test whether variation in personality traits was also associated with variation in females&rsquo ability and/or motivation to keep track of, anticipate, and react adaptively to social events, we examined females&rsquo responses to three different types of social challenges. We were interested not in females&rsquo responses to adversity itself&mdashbecause we expected little individual variation in responses to real, ongoing threats&mdashbut their ability to anticipate adversity, respond adaptively to adversity after it had occurred, and keep track of social interactions that had the potential to influence their own relationships. Because previous research had shown that, as a group, most females responded positively to these challenges, we expected that any differences that did emerge would be small.

Personality Styles and Responses to Social Challenges

In the Okavango Delta, male immigrants that achieve alpha status often commit infanticide (Cheney and Seyfarth, 2007). Perhaps as a result, both immigration and instability in the alpha male position cause a sig-

nificant increase in females&rsquo GC levels. Lactating females are particularly likely to experience elevated GC levels, though during some immigration events females in all reproductive states show significant increases (Beehner et al., 2005 Engh et al., 2006b Wittig et al., 2008). These responses are associated with a decrease in sociality among females (Wittig et al., 2008), which may reflect their heightened vigilance and reactivity.

We examined increases in females&rsquo GC levels from 2 weeks before to 2 weeks after four different immigration events in 2002, 2003, 2004, and 2005. All events involved the takeover of the alpha male position. We tested whether the magnitude of the GC changes of individual females was linked to their personality styles. Importantly, by focusing on GC changes in the 2 weeks immediately after the immigration event, we were able to assess females&rsquo anticipation of the threat of infanticide rather than their responses to the actual act.

Consistent with previous results, the majority (75 percent) of individuals showed an increase in GC levels after immigration. However, some of the variation in females&rsquo GC levels also seemed to be linked to their personality scores. The correlation between percent change in GC levels and Aloof scores was weakly negative (b = &minus10.15, SE = 10.5, t = &minus0.962, P > 0.10), as was the correlation for Loner scores (b = &minus11.24, SE = 11.62, t = &minus0.968, P > 0.10) (Fig. 2.1). In contrast, the correlation between Nice scores and change in GC levels was positive, though nonsignificant (b = 5.278, SE = 10.00, t = 0.527, P > 0.10) (Fig. 2.1). There were no significant effects of reproductive state.

Thus, individuals who scored high on Nice tended to show increases in GC levels in response to male immigration, whereas those who scored high on Aloof and Loner tended to be less responsive.

Changes in Grooming Behavior After the Death of a Close Relative

Females also experience elevated GC levels after the death of a close adult female relative, probably in part because the death results in the loss of a regular grooming partner. Previous analyses have shown that, in the 3 months after this loss, bereaved females increase both grooming rates and the number of female grooming partners (Engh et al., 2006a). These responses may facilitate the repair of females&rsquo social networks through the establishment of new bonds.

To examine individual differences in response to this challenge, we compared the number of each bereaved female&rsquos different grooming partners in the 3 months after the death of a close female relative with the mean number of grooming partners for unaffected females in the group during the same period (controlling for reproductive state). (This method was chosen to control for variation in sampling rates across time.) Whether

FIGURE 2.1 Percent change in females&rsquo GC levels from 2 weeks before to 2 weeks after the immigration of a potentially infanticidal male. Only immigration events in which an immigrant attained the alpha rank were included in analysis n = 33 females present for 1&ndash3 events for a total of 64 female events. Dashed lines indicate no change solid lines indicate least-square regression (statistics and probability values given in the text). The x axis denotes females&rsquo scores on each of the three principal components (Aloof, Loner, and Nice) in the immigration year. Each point represents 1 female-year.

females had a higher or lower number of partners than unaffected females seemed to be related to their personality scores. Females scoring high on the Loner component had fewer grooming partners than unaffected females (b = &minus1.138, SE = 0.866, t = &minus1.314, P = 0.203). In contrast, correlations between the relative number of grooming partners were positive but nonsignificant for both Aloof (b = 0.366, SE = 0.624, t = 0.586, P = 0.564) and Nice (b = 0.799, SE = 0.509, t = 1.569, P = 0.132) scores (Fig. 2.2).

Thus, females who scored high on the Loner component had fewer grooming partners compared with unaffected females in the ensuing 3 months, suggesting that they were unsuccessful in rebuilding their social network. This decrease occurred despite the fact that females who scored high on the Loner component tended to show a greater increase in GC levels than other females in the 2 weeks after the death of a close relative,

particularly when that relative was a mother or adult daughter (rs = 0.771, N = 6, P > 0.10). In contrast, females who scored high on the Aloof and Nice components responded to the death of a close relative by grooming comparatively more females than unaffected individuals.

Variation in the Strength of Responses During Playback Experiments

Playback experiments are designed to test subjects&rsquo knowledge of other individuals&rsquo dominance ranks and kinship as well as their memory of recent social interactions and their participants. Consider reconciliation, for example. Baboons often grunt to their opponents after aggression, and these grunts serve to restore opponents to baseline levels of tolerance (Cheney and Seyfarth, 1997). In an experiment designed to determine

FIGURE 2.2 The relative number of a female&rsquos different grooming partners in the 3 months after the death of a close relative (mother, adult daughter, or sister) compared with the mean number of grooming partners for all other females in those months (controlled for reproductive state) n = 18 females who lost from one to three close relatives for a total sample of 24 female-years. One outlier was removed. Legend is the same as in Fig. 2.1.

whether reconciliation by kin could serve as a proxy for direct reconciliation, victims were played the grunt of the close relative of a recent opponent. Subjects were significantly more likely to approach their opponent after hearing a grunt from their opponent&rsquos relative (test condition) than after hearing a grunt from a female from a different matriline (control condition) (Wittig et al., 2007b). In so doing, subjects showed that they remembered not only the specific nature of a recent interaction and the identity of the participants but also the kinship relations (or close associates) of other females in their group. Thus, by responding more strongly during tests than control trials, subjects showed that they were not only reactive but also appropriately reactive, in the sense that they responded strongly only to relevant stimuli.

For this analysis, we considered variation in females&rsquo responses to playback stimuli in five previously conducted experiments that tested baboons&rsquo memory of recent social interactions and knowledge of other individuals&rsquo relationships (summary of the playback experiments used in the analysis is available from the authors) (Bergman et al., 2003 Engh et al., 2006c Wittig et al., 2007a,b Cheney et al., 2010). We used duration of looking toward the speaker in test compared with control trials as our dependent measure, because this response was used in all experiments. Because the strength of subjects&rsquo responses varied across experiments, we ranked each subject&rsquos duration of response in each experiment relative to response duration of other subjects. Thus, a subject who responded more strongly in the test vs. the control condition received a high positive ranking, whereas a subject that responded more strongly in the control condition received a negative ranking.

The correlations between strength of response and Aloof, Loner, and Nice scores were all positive, but only the Nice scores reached statistical significance (Aloof: b = 0.381, SE = 0.580, t = 0.657, P > 0.10 Loner: b = 0.625, SE = 0.634, t = 0.986, P > 0.10 Nice: b = 1.250, SE = 0.566, t = 2.246, P = 0.027) (Fig. 2.3). Thus, although most females responded more strongly during test than control trials, females who scored high on the Nice component were the most responsive.

Discussion: Social Challenges

Previous analyses (Seyfarth et al., 2012) showed that females scoring high on the Nice component have stronger social bonds with other females. The data presented here suggest that, by three independent measures, these individuals may also be more responsive to social challenges and more motivated to attend to social interactions within their group (Table 2.1).


Excessive empathy, social cues and adaptive behavior evaluation - Psychology

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  • Behrend, Y., Tulen, Y., Wierdsma, A., van Pelt, H., Zagoory-Sharon, O., Feldman, R., de Rijke, Y, Kushner, S., van Marle, H.J.C. (2019). Intranasal administration of oxytocin decreases task-related aggressive responses in healthy young males.Psychoneuroendocrinology, 106, 147-154
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Zeev-Wolf, M., Levy, J., Goldstein, A., Zagoory-Sharon, O., & Feldman, R. (2018).Chronic Early Stress Impairs Default Mode Network Connectivity in Preadolescents and their Mothers. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. ‏


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Results

The grand average ERPs at electrodes of interest (F3, F4, Fz, C3, C4, Cz, Pz, PO7 and PO8) and scalp topographies prior to PCA are illustrated in Figs 2 and 3A. Visual stimuli of the three categories (facial expressions, face pictures and arm pictures) elicited similar ERP components. At frontocentral sites, an N1 component was apparent, followed by a vertex positive potential (VPP), an N2 component, and finally a long lasting late positive complex (LPC). At temporo-occipital sites, posterior P1 and N170 components (see Supplementary Information) were seen.

Grand average ERPs in response to three stimulus categories under pain and no-pain conditions at frontocentral (F3, F4, Fz, C3, C4 and Cz) and parieto-occipital (Pz, PO7 and PO8) electrode sites. All stimuli elicited similar components. At frontocentral sites, an N1 component is apparent, followed by a VPP component, an N2 component, and a long lasting LPC while at temporo-occipital sites, a posterior P1 component and an N170 component are elicited. Negative amplitudes are plotted upwards. (A) ERPs in response to painful expressions (red solid lines) and neutral expressions (red broken lines). (B) ERPs in response to needle-penetrated faces (green solid lines) and Q-tip-touched faces (green broken lines). (C) ERPs in response to needle-penetrated arms (blue solid lines) and Q-tip-touched arms (blue broken lines).

Topographical maps and statistical results of ERP components. (A) Scalp topographies of N1, VPP, N2, and LPC components (from top to bottom), plotted separately for each experimental condition (from left to right: painful expressions, neutral expressions, needle-penetrated faces, Q-tip-touched faces, needle-penetrated arms and Q-tip-touched arms). Boxed plots indicate a significant difference in ERP amplitude revealed by a Bonferroni-corrected t test. (B) Post hoc comparisons on condition × category interaction effects for N1, VPP, N2, and LPC amplitudes were conducted separately. Asterisks indicate significant differences in amplitude. **P < 0.01 ***P < 0.001. Error bars represent standard errors of the mean.

Painful scenes elicited larger N1 potentials than neutral scenes, and N1 amplitudes were higher in response to face-containing pictures (i.e., facial expressions and face pictures) than to arm pictures (expressions vs. arms, P < 0.001 faces vs. arms, P < 0.001). A 3-way ANOVA on N1 amplitude revealed a significant main effect of condition [F(1, 276) = 56.18, P < 0.001, η P 2 = 0.17], stimulus category [F(2, 552) = 25.70, P < 0.001, η P 2 = 0.09], and laterality [F(2, 276) = 4.34, P = 0.014, η P 2 = 0.03], and a significant interaction between category × laterality [F(4, 552) = 5.13, P < 0.001, η P 2 = 0.04]. Post hoc analysis revealed significant differences between the needle-penetrated face and the Q-tip-touched face (P < 0.001), and between the needle-penetrated arm and the Q-tip-touched arm (P = 0.001 Fig. 3A and B). No differences were observed between painful expressions and neutral expressions (P > 0.999 Fig. 3A and B). Interestingly, when gender was taken into consideration, the early distinction between the needle-penetrated face and the Q-tip-touched face, and between the needle-penetrated arm and the Q-tip-touched arm were only found in females, but not in males, as revealed by the significant gender × condition × category interaction effect [F(1.97, 545.86) = 8.82, P = 0.005, η P 2 = 0.02].

The 3-way ANOVA on N1 latency revealed a significant main effect of stimulus category [F(1.64, 447.30) = 5.29, P = 0.009, η P 2 = 0.02]. Post hoc comparisons indicated that face-containing pictures were detected faster than arm pictures (expression vs. arm, P = 0.041 face vs. arm, P = 0.006). In addition, the condition × category interaction [F(1.99, 547.98) = 4.77, P = 0.009, η P 2 = 0.02] was significant.

The VPP showed a greater amplitude in the pain condition relative to the no-pain condition. Face-containing pictures produced marked enhancement in the amplitude of the VPP over arm pictures (expression vs. arm, P < 0.001 face vs. arm, P < 0.001). The 3-way ANOVA for the VPP amplitude yielded a significant main effect of condition [F(1, 276) = 22.37, P < 0.001, η P 2 = 0.07] and category [F(1.58, 436.79) = 130.93, P < 0.001, η P 2 = 0.32], and a significant interaction effect of condition × category [F(1.79, 493.27) = 8.62, P < 0.001, η P 2 = 0.03]. Post hoc comparisons revealed a significant difference between painful expressions and neutral expressions (P < 0.001 Fig. 3A and B). No differences were found for the other two (face pictures and arm pictures) stimulus categories (needle-penetrated face vs. Q-tip-touched face, P > 0.999 needle-penetrated arm vs. Q-tip-touched arm, P > 0.999 Fig. 3A and B).

For the VPP latency, the 3-way repeated measures ANOVA revealed a significant main effect of category [F(1.28, 291.63) = 291.63, P < 0.001, η P 2 = 0.51], and a significant condition × category interaction effect [F(1.92, 529.35) = 4.77, P < 0.001, η P 2 = 0.04). Similar to the results for the N1 component, face-containing pictures elicited shorter VPP latencies than arm pictures (expression vs. arm, P < 0.001 face vs. arm, P < 0.001 Fig. 2). In addition, there was a significant difference between painful expressions and neutral expressions (painful expression > neutral expressions, P < 0.001), whereas no differences were found for the other two (face pictures and arm pictures) stimulus categories (needle-penetrated face vs. Q-tip-touched face, P > 0.999 needle-penetrated arm vs. Q-tip-touched arm, P > 0.999).

The N2 component showed a positive shift in the pain condition compared to the no-pain condition. Facial expression pictures elicited a more positive N2 than face pictures and arm pictures (expression vs. face, P < 0.001 expression vs. arm, P < 0.001 Fig. 3). In a 3-way repeated measures ANOVA of N2 amplitude, there were significant main effects of condition [F(1, 276) = 39.93, P < 0.001, η P 2 = 0.13], category [F(1.58, 436.65) = 19.66, P < 0.001, η P 2 = 0.07], and laterality [F(2, 276) = 4.76, P = 0.009, η P 2 = 0.03], and significant interaction effects of condition × category [F(1.98, 545.41) = 28.00, P < 0.001, η P 2 = 0.09], condition × laterality [F(2, 276) = 3.43, P = 0.034, η P 2 = 0.02], category × laterality [F(3.16, 436.65) = 6.07, P < 0.001, η P 2 = 0.04], and condition × category × laterality [F(3.95, 545.41) = 3.10, P = 0.016, η P 2 = 0.02]. Post hoc comparisons indicated that N2 amplitudes were significantly different between painful expressions and neutral expressions (P < 0.001, Fig. 3B), and between needle-penetrated arms and Q-tip-touched arms (P < 0.001, Fig. 3B). No difference in N2 was observed between needle-penetrated faces and Q-tip-touched faces (P = 0.128, Fig. 3B). The pain-related N2 amplitude modulation was significant at midline and right hemisphere electrodes (both Ps < 0.001), but was not significant at left hemisphere electrodes (P = 0.463).

There was a significant main effect of category on N2 latency [F(1.80, 495.49) = 71.34, P < 0.001, η P 2 = 0.21]. The N2 latencies elicited by facial expression pictures were longer than those elicited by face pictures but shorter than those elicited by arm pictures (all Ps < 0.001).

The 3-way ANOVA of LPC revealed significant main effects of condition [F(1, 276) = 221.43, P < 0.001, η P 2 = 0.45] and category [F(1.94, 535.98) = 497.80, P < 0.001, η P 2 = 0.64], and significant interaction effects of condition × category [F(1.87, 516.39) = 55.74, P < 0.001, η P 2 = 0.17), condition × laterality [F(2, 276) = 5.15, P = 0.006, η P 2 = 0.04] and category × laterality [F(3.88, 535.98) = 3.83, P = 0.005, η P 2 = 0.03]. Post hoc analyses showed that the pain vs. no-pain difference in LPC existed in expression pictures and arm pictures (both Ps < 0.001), but not in face pictures (P = 0.058).

PCA results

The LPC component was divided into two separate subcomponents by temporospatial PCA: P3 and LPP. The microvolt rescaled factor scores of the PCA-derived P3 and LPP components are presented in Fig. 4A. Two-way ANOVAs were conducted on these components, to better illustrate the empathic process over the long lasting late component (see Fig. 4B and C).

PCA derived P3 and LPP components. (A) Virtual PCA derived P3 (left) and LPP (right) component waveforms for each experimental condition. (B) Scalp topographies of P3 (upper panel) and LPP (lower panel) components, plotted separately for each experimental condition (from left to right: painful expressions, neutral expressions, needle-penetrated faces, Q-tip-touched faces, needle-penetrated arms and Q-tip-touched arms). Boxed plots indicate a significant difference revealed by a Bonferroni-corrected t test. (C) Post hoc comparisons on condition × category interaction effects for P3 (left) and LPP (right) components. Asterisks indicate significant differences in amplitude. ***P < 0.001. Error bars represent standard errors of the mean.

The P3 amplitudes were greater in response to painful scenes than to neutral scenes, and face-containing pictures elicited greater P3 amplitudes than arm pictures (expression vs. arm, P < 0.001 face vs. arm, P = 0.035 Fig. 4B and C). The 2-way ANOVA revealed a significant main effect of condition [F(1, 30) = 42.37, P < 0.001, η P 2 = 0.59] and category [F(2, 60) = 12.03, P < 0.001, η P 2 = 0.29], and a significant interaction effect between these variables [F(2, 60) = 6.26, P = 0.003, η P 2 = 0.17]. Post hoc analysis revealed a significant pain-related difference between painful expressions and neutral expressions, and between needle-penetrated arms and Q-tip-touched arms (both Ps < 0.001 Fig. 4B and C). No significant difference was found between the needle-penetrated face and the Q-tip-touched face (P = 0.622 Fig. 4B and C).

Painful scenes elicited considerably greater LPP components than neutral scenes. Expression pictures elicited the largest LPP, while arm pictures elicited the smallest LPP (all Ps < 0.001). In the 2-way ANOVA for the LPP amplitude, there were significant main effects of condition [F(1, 30) = 15.85, P < 0.001, η P 2 = 0.35] and category [F(2, 60) = 61.02, P < 0.001, η P 2 = 0.67], and a significant condition × category interaction effect [F(2, 60) = 10.90, P < 0.001, η P 2 = 0.27]. Post hoc comparisons revealed that the pain effect only existed in the expression category (P < 0.001 Fig. 4B and C), suggesting long lasting empathic processing for pain expression.

Behavioral performance

Table 1 summarizes the mean RT and accuracy rate under each category and condition. Participants responded faster to pain pictures than neutral pictures [2-way ANOVA, condition effect: F(1, 30) = 19.52, P < 0.001, η P 2 = 0.39] and took more time to judge expression pictures than to judge face and arm pictures [all Ps < 0.001 category effect: F(2, 60) = 30.12, P < 0.001, η P 2 = 0.50].

Participants were less accurate in judging painful scenes than neutral scenes, and also less accurate in judging expressions than faces and arms (all Ps < 0.001). The 2-way repeated measures ANOVA revealed significant main effects of condition [F(1, 30) = 4.89, P = 0.035, η P 2 = 0.14] and category [F(1.37, 41.18) = 40.80, P < 0.001, η P 2 = 0.58], and a significant interaction effect of condition × category [F(1.35, 40.61) = 5.71, P = 0.014, η P 2 = 0.16].

Correlation analyses

Correlation analyses showed no associations between electrophysiological measures and any of the psychometric measures or behavioral performance.


Results

Behavioral Results

Table 1 presents the descriptive statistics for each subscale of the IRI, IRI total scores and RSQ. The results showed that no differences in PT, FS, EC, PD subscales, IRI total scores and RSQ scores were found between the social exclusion group and the social inclusion group (ps > 0.05).

Table 1. Mean scores and standard deviation for IRI and RSQ.

An independent sample t-test was conducted to compare the self-reported social exclusion and social ostracism scores (see Figure 1). As expected, both scores in the social exclusion group were significantly higher than those in the social inclusion group after the Cyberball game (social exclusion scores: t = 7.383, p < 0.001, d = 2.3 social ostracism scores: t = 7.604, p < 0.001, d = 2.503). Such reliable differences continued up to the end of the experiment (social exclusion scores: t = 3.092, p = 0.004, d = 0.943 social ostracism scores: t = 2.679, p = 0.011, d = 0.816). The results revealed that the manipulation of the social exclusion was effective.

Figure 1. Self-reported social exclusion scores (A) and social ostracism scores (B) after the Cyberball task and after the experiment. *p < 0.05, **p < 0.01, ***pπ.001. Error bars denote standard errors.

We also performed an independent sample t-test on the need questionnaires and the PANAS scores. The results showed that scores for belonging, control, self-esteem, and meaningful existence of the social exclusion group were significantly lower than those of the social inclusion group (ps < 0.001). The positive affect score of the social exclusion group was also significantly lower than that of the social inclusion group (t = 𢄤.020, p < 0.001, d = 2.249), while the negative affect score of the social exclusion group was significantly higher than that of the social inclusion group (t = 4.338, p < 0.001, d = 1.353).

Finally, a two (group: social exclusion group and social inclusion group) ൲ (stimuli: painful and neutral pictures) mixed ANOVAS was conducted on the subjective unpleasantness scores. The results showed that the main effect of stimuli was significant in self-unpleasantness [F(1,40) = 372.458, p < 0.001, ηp 2 = 0.903] and in other-unpleasantness scores [F(1,40) = 507.693, p < 0.001, ηp 2 = 0.927]. Participants rated painful pictures as more unpleasant than neutral pictures from both perspectives (ps < 0.001). No other differences were found (lowest p = 0.581). We also conducted a similar mixed ANOVAS on reaction time and response accuracy of pain categorization. The results showed a significant main effect of stimuli on reaction time [F(1,40) = 9.488, p = 0.004, ηp 2 = 0.192]. Painful pictures resulted in longer reaction time compared to neutral stimuli (p = 0.004). No other differences were found (lowest p = 0.296). The descriptive statistics of reaction time and response accuracy are presented in Table 2.

Table 2. The descriptive statistics for reaction time and response accuracy in pictures classification task (M ± SD).

ERP Results

The averaged ERPs at central and parietal regions and the voltage topographies are presented in Figure 2. Averaged parietal amplitudes within the P3 and LPP time window are illustrated in Figure 3. Figure 4 present data distribution of two groups in averaged parietal P3 and LPP amplitudes for painful pictures and neutral pictures.

Figure 2. Average ERPs in the central, and parietal regions for painful pictures and neutral pictures in both groups. The voltage topographies illustrate the scalp distribution of N2, P3, and LPP components.

Figure 3. Averaged parietal (P3, P4, Pz) amplitudes for painful pictures and neutral pictures within the (A) P3 (300� ms) and (B) LPP (450� ms) time window in each group. *p < 0.05, **p < 0.01, ***pπ.001. Error bars denote standard errors.

Figure 4. Data distribution of two groups in averaged parietal (A) P3 and (B) LPP amplitudes for painful pictures and neutral pictures. SE, social exclusion group SI, social inclusion group.

For the N2 component, a 2 (group: the social exclusion group and the social inclusion group) ൲ (stimuli: painful and neutral pictures) mixed ANOVAS was conducted. There was a marginally significant main effect of stimuli [F(1,40) = 4.094, p = 0.050, ηp 2 = 0.093] while the main effect of group was not significant [F(1,40) = 2.808, p = 0.102]. Both groups exhibited a more positive shift in N2 amplitudes when watching painful stimuli in contrast with neutral stimuli (p = 0.05). The interaction between group and stimuli was not significant (p = 0.730).

For the P3 component, a two (group: the social exclusion group and the social inclusion group) ൲ (stimuli: painful and neutral pictures) mixed ANOVAS was conducted. The results showed a significant main effect of stimuli [F(1,40) = 4.176, p = 0.048, ηp 2 = 0.095], while the main effect of group [F(1,40) = 2.978, p = 0.092] was not significant. The interaction between stimuli and group [F(1,40) = 8.23, p = 0.007, ηp 2 = 0.171] was significant. There was a reliable simple effect of stimuli in the social exclusion group [F(1,40) = 12.669, p < 0.001, ηp 2 = 0.241] with painful stimuli eliciting smaller P3 amplitudes than neutral stimuli did. This effect was not significant in the social inclusion group [F(1,40) = 0.325, p = 0.572]. In addition, simple effects of group were found significant under the pain condition [F(1,40) = 4.934, p = 0.032, ηp 2 = 0.11] but not under non-pain condition [F(1,40) = 1.411, p = 0.242]. Subsequent pairwise comparison showed that painful pictures induced significantly smaller P3 amplitudes in the social exclusion group than those in the social inclusion group (p = 0.032).

We conducted a similar ANOVAS on the average LPP amplitudes at the parietal site as we did on the average P3 amplitudes and the results showed a significant main effect of stimuli [F(1,40) = 78.817, p < 0.001, ηp 2 = 0.663], and group [F(1,40) = 6.291, p = 0.016, ηp 2 = 0.136]. There was a reliable two-way interaction between group and stimuli [F(1,40) = 9.196, p = 0.004, ηp 2 = 0.187]. A significant simple effect of stimuli was observed in the social exclusion group [F(1,40) = 17.939, p < 0.001, ηp 2 = 0.31] and in the social inclusion group [F(1,40) = 67.704, p < 0.001, ηp 2 = 0.629] with painful stimuli eliciting larger LPP amplitudes than those elicited by neutral stimuli in both groups (ps < 0.001). There was also a reliable simple effect of group under the pain condition [F(1,40) = 9.072, p = 0.004, ηp 2 = 0.185] but not under the neutral condition [F(1,40) = 3.024, p = 0.09]. Subsequent pairwise comparisons suggested that the LPP amplitudes elicited in the social exclusion group were significantly smaller than those elicited in the social inclusion group (p = 0.004).

Correlation Between Subjective Ratings and ERP Amplitudes

We also calculated the correlation between self-reported unpleasantness scores and the mean amplitudes of ERPs induced by painful pictures in each time window to explore if the subjective ratings of unpleasantness were correlated with the electrophysiological activity elicited by the painful pictures. Subjective other-unpleasantness ratings were significantly correlated with central N2 amplitudes for painful stimuli (r = 𠄰.318, p = 0.04). The correlation between self-unpleasantness scores and central N2 amplitudes for painful stimuli were marginally significant (r = 𠄰.291, p = 0.062). Subjective other-unpleasantness ratings were significantly correlated with parietal LPP amplitudes for painful stimuli (r = 0.311, p = 0.045) and marginally significantly. correlated with parietal P3 amplitudes for painful stimuli (r = 0.308, p = 0.050). However, after we corrected the alpha level for multiple comparisons by FDR (false discovery rate) we found none of these correlations were significant (lowest p = 0.093). Moreover, we also examine whether the group differences exist in these correlations. The LPP amplitudes induced by painful pictures in the parietal region were positively correlated with the subjective ratings of self-unpleasantness and other-unpleasantness in the social inclusion group (self-unpleasantness: r = 0.491, p = 0.028 other-unpleasantness: r = 0.478, p = 0.033) whereas no correlation was found in the social exclusion group (self-unpleasantness: r = 𢄠.155, p = 0.49 other-unpleasantness: r = 𢄠.038, p = 0.867). The P3 amplitudes induced by painful pictures in the parietal region were positively correlated with the subjective self-unpleasantness scores in the social inclusion group (r = 0.461, p = 0.041) whereas no correlation was found in the social exclusion group (r = 𢄠.009, p = 0.968). However, the FDR results also showed that all the corrected p value in the social inclusion group were not significant (lowest p = 0.082). Therefore, our results showed that the ERP empathic responses are not significant with behavioral self-reported pain empathy.


4 SOCIAL/EMOTIONAL SKILLS YOU CAN EASILY PRACTICE WITH TEENS

Whether you are a parent or work directly with teens, here you can read about some concrete social/emotional skills and useful activities that can help teens practice them. We will cover basic information about Listening skills, Assertiveness, Emotional awareness, and Nonverbal communication.

Why practice social/emotional skills?

Whether we call them soft skills, social/emotional skills, social/emotional intelligence or growth mindset, there is a consensus among researchers and practitioners that we need certain abilities to achieve our fullest potential at school, in our professional careers, and in our private lives. These abilities help us recognize and manage our emotions, cope with obstacles and life challenges, and enhance communication skills and good interpersonal relations (including empathy).

ONLINE STEM CAMP WHERE STUDENTS
MASTER SOCIAL/EMOTIONAL SKILLS

According to an analysis of longitudinal studies in nine OECD countries published in Skills for Social Progress: The Power of Social and Emotional Skills by OECD in 2015:

“Children’s capacity to achieve goals, work effectively with others and manage emotions will be essential to meet the challenges of the 21st century.”

Besides acknowledging the importance of social/emotional skills such as perseverance, sociability, and self-esteem, the report discusses how policy-makers, schools, and families facilitate the development of social/emotional skills through intervention programs, teaching, and parenting practices.

All these abilities are interrelated and their development starts at home and continues throughout the school years. If parents and important adults show a high level of social/emotional maturity, it will be easier for kids to acquire these abilities simply by modeling their behavior.

However, it is always useful when children and teens have a chance to practice social/emotional skills under the guidance of experienced adults. The best case scenario is when programs for enhancing social/emotional skills are an integral part of an educational system and a local community’s initiatives.

Below, we will look at some important social/emotional skills and suggest simple activities for practicing them, adjusted to teens.

1. Social communication skill – Listening

Being able to hear what people are really saying is a valuable communication skill that has a major impact on the quality of our relations with others. You’ve probably already heard about Active Listening, a skill that allows us to hear not only the words people are saying but also the emotions they are reflecting through their nonverbal behavior. Both are important in understanding the whole message being communicated.

This is a complex skill that can be practiced. In the following activity, the focus is on practicing concentration listening to the verbal message with undivided attention. You can practice this activity with a group of teens in your home, in the classroom or in a workshop.

Instruction

Firstly, ask all the participants to sit in a circle. The first person starts to tell a story (whatever he/she wants). After 3-5 sentences, say “stop” and randomly choose another participant to continue. This person now has to repeat the last sentence said and then continue making up the story. If he cannot correctly repeat the last sentence after five seconds, he is disqualified. The game continues with the same rules and the winner is the last person remaining after everybody else is disqualified.

This is the competitive version of the game. However, you can make up your own version, without disqualifications or adding new elements that you find useful.

Have a discussion

Ask participants to reflect on the game. When and how was their attention distracted? What helped them concentrate and remember the previous sentence?

2. Social communication skill – Assertiveness

Assertiveness, as a style of communication, is characterized by the ability to directly and confidently express our genuine opinion, feelings, or attitudes, such that the rights of others and social circumstances are respected.

It is proven that assertiveness affects our self-esteem and self-confidence, so there’s no doubt that practicing assertiveness is useful for teens. It is a complex skill that can be acquired through a training program led by a trained coach/therapist. However, some aspects of assertiveness can be practiced through simple exercises at home and in a school setting.

Maybe the most important point is to assure teens that it’s okay to claim their rights and to ask, to initiate, to express their opinions and feelings. That it’s okay to say NO to other people in a respectful way.

In this exercise, the focus will be on encouraging teens to initiate a conversation in which they will ask something of others and express their opinion or feelings. It can be practiced as social challenges given to teens either by their parents or teachers.

Instruction

Firstly, a list of social challenges is created, taking into consideration a teen’s age or social needs. Challenges can be written down/printed on separate cards. If given consent to take part in the challenge, a teen takes a random card and his task is to do what is required on the card in the next 24 hours or over several days, as you jointly arrange.

Challenges can be practiced once a week or according to whatever schedule you agree upon.

Examples of social challenges:

  • Give an honest compliment to someone.
  • Learn two new things about somebody from your class.
  • Share with a friend what’s been on your mind lately.
  • Call customer service at your favorite store and ask for information about some product you like.
  • Tell your best friend what you like about him/her.
  • Ask a teacher (or a coach) for clarification of a task you didn’t understand completely.

Have a discussion

After the task is accomplished, it’s important to discuss with the teen how the particular challenge made him feel. Did he find it easy, hard, awkward, or something else? What could be alternative ways to ask, to express? How did others react?
The inspiration for this activity is taken and adjusted from the Speech Bubble SLP.

3. Emotional skill – Emotional self-awareness

We have already written about self-awareness as the basic ability to understand our own inner processes and to relate adequately with others. Emotional awareness, in this context the ability to recognize our own feelings, is the foundation of emotional intelligence.

Besides helping us be aware of our emotions, these skills are important for developing emotional intelligence, according to Daniel Goleman and his bestselling book Emotional Intelligence. Understanding why we feel a certain way and knowing how to handle these feelings, including self-motivation the ability to recognize the feelings of others (empathy) and to motivate them – these skills are crucial to success and happiness in every aspect of our lives and in our relationships with others.

In the following activity, the focus is on getting in touch with eight emotions a teen chooses, raising awareness of how a particular emotion manifests itself, and how it affects the teen’s life. It is based on art therapy principles and is performed individually. However, it can be practiced in groups, too. You need a white paper and colored markers.

Instruction

Firstly, ask a teen to draw a circle and divide it into eight pies. Then, ask him/her to dedicate each pie to one emotion and fill in each pie with a corresponding color or images that match his/her idea of what the emotion means to him/her. It may be that a teen has a problem coming up with eight emotions. You can assist him but never choose instead of him. Don’t push if he can’t come up with eight. Work with whatever he manages to present.

Have a discussion

After the teen is done with the drawing, initiate a dialogue. You may find these questions useful: What does each image mean to you? What made you choose those particular colors? When in your life do you experience this emotion? What emotion is dominant for you nowadays? What emotion is the hardest to handle? And so on.

If a teen has a problem in coming up with emotions, you can use Plutchik’s wheel of emotion to help him recognize emotions he would like to work on.

This exercise is taken and adjusted from the Art therapy directives BlogSpot.

4. Social/emotional skills – Understanding nonverbal communication

Good understanding of nonverbal communication is a sign of social and emotional intelligence.

The ability to observe and understand nonverbal signs during communication, or any other interaction between people, gives us tremendous information about the real message being communicated. It is especially important when we notice that the verbal message and nonverbal behavior are not harmonized. It also gives us a clue about the motives of the person we are communicating with or their emotional state.

Besides what is said, it is always important to follow HOW it is said. Basic nonverbal aspects of human behavior to be aware of include eye contact, the tone of voice, facial expression, gestures, personal distance, body language, and posture.

The following activity, based on acting and improvisation methodology, focuses on recognizing the emotional state of participants exposed to simulated social situations, through observing only their nonverbal behavior. A group is needed for this activity.

Instruction

Ask a volunteer from the group to leave the room. Separate instructions are given to him/her and to the group, who stays in the room in order to prepare for the final scene. While the volunteer is outside, each individual in the group has to choose one emotion and must express this emotion only through nonverbal behavior (acting). Remind them of the different aspects of nonverbal communication.

Meanwhile, the volunteer outside is given the task of coming up with several social situations familiar to teens such as: in class during family dinner on a date at a birthday party working on homework, etc.

Finally, when the volunteer is back to the room, he sets the scene: You’re in class (for example). All members of the group act as if they are in the classroom, including expressing their chosen emotional state nonverbally. They can use their voice but only in the form of inarticulate sounds. The volunteer observes their behavior and tries to guess how they feel. If he is confused, he can put them in another social situation (or only for fun:). The game can be repeated several times with different volunteers, emotions to guess, and social situations.

Have a discussion

After it is revealed which emotion has been presented by each member of the group, a discussion follows. You may find these questions useful: What are the main nonverbal indicators of this emotion? How did you feel while acting? Did anybody have difficulties acting in the scenes (why)? What do you usually do when you feel (this particular emotion)? What do you usually do when you recognize somebody acting like this? Was there something confusing and what? – A question to the volunteer.

Depending on available time and the goal of your group work you can go even deeper into a conversation about particular emotions. If you are interested in activities useful for teen’s emotional development, you may like this article.

Do you need more advice related to the social/emotional development of your teen? You’ve come to the right place!


Materials and Methods

Subjects

Twenty-two subjects, 12 females and 10 males (Mage = 24.5 years SD = 3.53 age range from 20 to 33 years) participated in the experiment. All subjects were right-handed (Edinburgh Handedness Inventory, Oldfield, 1971), with normal or corrected-to-normal visual acuity. Exclusion criteria were neurological or psychiatric pathologies of the subjects or their close family members. Specifically, they did not show deficits related to depression (Beck Depression Inventory II, BDI, Beck, Steer, & Brown, 1996) and to anxiety (State-Trait Anxiety Inventory, STAI, Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1970): Exclusion criterion of the BDI Inventory was 19 points or lower (M = 8.95 SD = 0.46 score range from 2 to 12 points) for the STAI 39 points or lower (M = 28.45 SD = 1.03 score range from 27 to 45 points). No payment was provided for participation. Participants gave informed written consent and the research was approved by the Ethical Committee institution where the work was carried out. The experiment was conducted in accordance with the Declaration of Helsinki, and all the procedures were carried out with adequate understanding by the subjects. The Research Consent Form was submitted before participation in the study.

Stimuli

Subjects were required to view affective images depicting real interpersonal situations which represented two people who interacted in a common and familiar situation (e.g., at home, in a workplace, or on a journey). Colored images (16 cm in width and 10 cm in height) representing positive, negative, and neutral interactions were selected. Twenty-four pictures were used for each type of interaction. Positive interactions represented positive and emotionally comfortable situations (such as a handshake between two people) negative interactions represented negative and emotionally uncomfortable situations (such as a quarrel between two people) neutral pictures represented interactions without a specific emotional valence (such as two people sitting on a couch, see Figure 1 ). All images were similar in their perceptual features (i.e., their luminance, complexity, i.e., number of details in the scene, and characters’ genders: half of the actors were male and half were female).

Some examples of positive, neutral, and negative interactions.

In order to validate the image dataset, a pre-experimental procedure was adopted. Each depicted scene was evaluated by four judges on valence and arousal dimensions, using the Self-Assessment Manikin Scale (SAM) with a five-point Likert scale (Bradley & Lang, 1994, 2007). Separately for each condition (positive, negative, and neutral), ratings were averaged across all images presented. As shown by statistical analysis (two distinct repeated-measures analyses of variance [ANOVAs] applied to valence and arousal), images firstly differed in terms of valence (positive: M = 4.56, SD = 0.34 negative: M = 1.33, SD = 0.26 neutral: M = 2.75, SD = 0.37)—positive interactions were more positively rated than the other two categories, negative interactions were more negatively rated than the other two categories, neutral images were rated to be of intermediate valence between the other two categories (for all significant contrast comparisons, p ≤ .01). Secondly, with respect to arousal, the positive and negative interactions (positive: M = 4.23, SD = 0.24 negative: M = 4.72, SD = 0.25 neutral: M = 1.77, SD = 0.31) were rated as more arousing than the neutral interactions (for all significant contrast comparisons, p ≤ .01). In contrast, no significant differences were revealed between positive and negative interactions (p = .32).

Procedure

Subjects were seated in a dimly lit room, facing an LCD computer monitor that was placed at about 50 cm from the subject. The stimuli were presented using E-Prime 2.0 software (Psychology Software Tools, Inc) running on a laptop PC with a 15 in. screen (Acer TravelMate 250P). Images were presented in a random order in the center of the screen for 6 s, with an inter-stimulus interval of 8 s (see Figure 2 ).

Experimental setting with fNIRS, EEG, and autonomic measures.

Participants were required to view each stimulus during fNIRS/EEG measures recording, and they were asked to attend to the interpersonal situations during the entire time of exposition, focusing on the emotional conditions which characterized the represented human actors. Moreover, they were required to empathize with the two persons interacting with each other (“Try to put yourself into the shoes of the persons and to experience their feelings in this situation”). In order to facilitate empathizing with the depicted actors, the two actors were of about the same age as the experimental subjects.

Before scene presentations, a 2 min resting period was registered at the beginning of the experiment. Next, a familiarization phase followed, in which subjects saw and evaluated a set of images (one of each emotional category), different from the images used in the experimental phase. After the experimental phase, subjects were required to rate the pictures with the SAM on valence and arousal dimensions. As shown by statistical analysis (two repeated-measures ANOVAs for the valence and arousal measures), images differed in terms of valence (with more positive evaluations of positive than negative and neutral interactions, with more negative evaluations of negative than positive and neutral interactions, and with intermediate evaluations of neutral compared to positive and neutral interactions) and arousal (with significant differences between positive and neutral interactions, and between negative and neutral interactions, showing a higher arousal rating for positive and negative interactions). For all paired comparisons significance was assumed for an alpha level of .01 or lower.

A specific questionnaire was used in order to assess the subjects’ self-rating on key aspects of the subjective evaluation of the empathic task. The questionnaire was used in a de-briefing post-experimental section (a five-point Likert scale for each item, from low to high). The aspects examined included the degree of experienced empathy (“How much did you put yourself into the shoes of the actors and felt what they felt in the depicted situation?”), personal emotional involvement (“How much did you feel emotionally involved in the situation?”), semantic attribution of the situation (positive, negative, and neutral, “How did you classify the interpersonal situation?”), and emotional significance (high or low, 𠇍id you perceive an emotional significance of the situation?”). All subjects experienced a high sense of empathy (M = 4.11, SD = 0.26), were emotionally engaged in the task (M = 4.23, SD = 0.34), and were able to attribute a coherent emotional value to the pictures (for coherent semantic attribution of valence: M = 4.09, SD = 0.32 for emotional significance: M = 4.88, SD = 0.45).

EEG: Frequency Band Analysis

A 16-channel portable EEG-System (V-AMP, Brain Products) was used for data acquisition. An NIRS-EEG compatible ElectroCap with Ag/AgCl electrodes was used to record EEG from active scalp sites referred to earlobe (10/5 system of electrode placement). EEG activity was recorded from the following positions: AFF3, AFF4, Fz, AFp1, AFp2, C3, C4, Cz, P3, P4, Pz, T7, T8, O1, and O2 (for examples, see Figure 3 ). The cap was fixed with a chin strap to prevent shifting during the task. Additionally, one EOG electrode was placed on the lower side of the left eye.

Locations of the prefrontal measurement channels of EEG and fNIRS. For fNIRS, emitter-detector distance was 30 mm for contiguous optodes and near-infrared light of two wavelengths (760 and 850 nm) were used. NIRS optodes were attached to the subject’s head using a NIRS -EEG compatible cup, with respect to the international 10/5 system.

Data preprocessing has been conducted with BrainVision Analyzer 2 (Brainproducts). The data were recorded using a sampling rate of 500 Hz, with a notch filter of 50 Hz. The impedance of recording electrodes was monitored for each subject prior to data collection, and it was always kept below 5 kΩ (rejected epochs 4%). Blinks were also visually monitored. Ocular artefacts (eye movements and blinks) were corrected using an eye-movement correction algorithm that employs a regression analysis in combination with artefact averaging. After EOG correction and visual inspection, only artefact-free trials (not less than 22) were considered. To obtain a signal proportional to the power of the EEG frequency band, the filtered signal samples were squared and successively log-transformed (Pfurtscheller, 1992). Successively, the data were epoched, using a time window of 1 s and an average absolute power value was calculated for each electrode and condition. Artefact-free data have been used to compute power spectra for relevant EEG frequency bands by the Fast Fourier transform method (with a Hamming window of a length of 10%) that was used to obtain estimates of spectral power (μV 2 ) in 1 Hz wide frequency bins for each electrode site. Spectral power values were averaged across all epochs and were then transformed to power density values for different frequency bands. An average of the pre-experimental absolute power (2 min) was used to determine the individual power without stimulation. From this reference power value, individual power changes during stimulus viewing were determined as the relative stimulus-related decreases or increases. Digital EEG data (from all 15 active channels) were band-pass filtered in the following frequency bands: delta (0-3), theta (4-7), alpha (8-12), and beta (13-20). During data reduction, a bandpass filter was applied in the 0.01-50 Hz frequency band.

FNIRS

fNIRS measurements were conducted with the NIRScout System (NIRx Medical Technologies, LLC) using a six-channel array of optodes (four light sources/emitters and four detectors) covering the prefrontal area. Emitters were placed at AF3-AF4 and F5-F6 while detectors were placed at AFF1-AFF2 and F3-F4 (see Figure 3 ). Emitter-detector distance was 30 mm for contiguous optodes and a near-infrared light of two wavelengths (760 and 850 nm) was used. NIRS optodes were attached to the subject’s head using a NIRS-EEG compatible cup, with respect to the international 10/5 system.

With NIRStar Acquisition Software (NIRx Medical Technologies LLC), changes in the concentration of O2Hb and deoxygenated hemoglobin (HHb) were recorded from a 2 min starting baseline. Signals obtained from the six NIRS channels were measured with a sampling rate of 6.25 Hz and analyzed and transformed according to their wavelength and location, resulting in values for the changes in the concentration of O2Hb and HHb for each channel. Haemoglobin quantity is scaled in mM*mm, implying that all concentration changes depended on the path length of the NIR light in the brain.

With Nirslab Software (v2014.05 NIRx Medical Technologies LLC) the raw data of O2Hb and HHb from individual channels were digitally band-pass filtered at 0.01-0.3 Hz. Successively, the mean concentration of each channel within a subject was calculated by averaging data across the trials for 6 s from trial onset. Based on the mean concentrations in the time series, we calculated the effect size in every condition for each channel within a subject. The effect sizes (Cohen’s d) were calculated as the differences of the means of the baseline and trial divided by the SD of the baseline, d = (M1M2)/SD1. Accordingly, M1 and M2 are the mean concentration values during the baseline and trial, and SD1 the SD of the baseline. The mean concentration value of the 2 s immediately before the trial was used as a baseline. Then, the effect sizes obtained from the six channels were averaged in order to increase the signal-to-noise ratio. Although the raw data of NIRS were originally relative values and could not be averaged directly across subjects or channels, normalized data, such as the effect sizes, could be averaged regardless of the units of measurement (Matsuda & Hiraki, 2006 Schroeter, Zysset, Kruggel, & Von Cramon, 2003 Shimada & Hiraki, 2006). In fact, the effect size is not affected by differential pathlength factor (DPF, Schroeter et al., 2003). Instead of a block design, a continuous trial design was used in the present research.

Autonomic Measures

Biopac MP 150 system (Biopac Systems Inc) was used to record the autonomic activity. Electrocardiography (ECG) was recorded continuously in lead 1 from two electrodes attached to the lower wrist, with the positive pole on the left arm and the negative pole on the right arm. One more reference electrode was placed over the left ankle. The ECG signal was sampled at 1,000 Hz with the Biopac Acknowledge 3.7.1 software (Biopac Systems Inc) according to the manufacturer guidelines. ECG was converted to HR in number of beats per minute. The signal was low-pass filtered at 35 Hz and highpass filtered at 0.05 Hz for motor and ocular artefacts. For SCR, before attaching the electrodes, the skin was cleaned with alcohol and slightly abraded. The electrodes for SCR were attached to the distal phalanges of the first and second finger of the left hand. SCL was recorded using two Ag/AgCl electrodes and an isotonic gel. The signal was low-pass filtered at 10 Hz for motor, ocular, and biological artefacts. Ocular artefacts were then checked with a visual inspection to eventually eliminate specific elements. Trials with artefacts (2%) were excluded from the analysis. SCR elicited by each stimulus was registered continuously with a constant voltage. It was defined as the largest increase in conductance during emotional image presentation, with a cut-off of at least 0.3 μS in amplitude with respect to baseline (pre-stimulus) mean values. Baseline values were scored during the 2 min prior to task onset.


Definitions

Empathy definitions encompass a broad range of emotional states, including caring for other people and having a desire to help them experiencing emotions that match another person’s emotions discerning what another person is thinking or feeling and making less distinct the differences between the self and the other. It can also be understood as having the separateness of defining oneself and another a blur.

It also is the ability to feel and share another person’s emotions. Some believe that empathy involves the ability to match another’s emotions, while others believe that empathy involves being tenderhearted toward another person.

Having empathy can include having the understanding that there are many factors that go into decision making and cognitive thought processes. Past experiences have an influence on the decision making of today. Understanding this allows a person to have empathy for individuals who sometimes make illogical decisions to a problem that most individuals would respond with an obvious response. Broken homes, childhood trauma, lack of parenting and many others factors can influence the connections in the brain which a person uses to make decisions in the future.

Martin Hoffman is a psychologist who studied the development of empathy. According to Hoffman everyone is born with the capability of feeling empathy.

Compassion and sympathy are terms associated with empathy. Definitions vary, contributing to the challenge of defining empathy. Compassion is often defined as an emotion we feel when others are in need, which motivates us to help them. Sympathy is a feeling of care and understanding for someone in need. Some include in sympathy an empathic concern, a feeling of concern for another, in which some scholars include the wish to see them better off or happier.

Hugging someone who is hurt

Empathy is distinct also from pity and emotional contagion. Pity is a feeling that one feels towards others that might be in trouble or in need of help as they cannot fix their problems themselves, often described as “feeling sorry” for someone. Emotional contagion is when a person (especially an infant or a member of a mob) imitatively “catches” the emotions that others are showing without necessarily recognizing this is happening.

Since empathy involves understanding the emotional states of other people, the way it is characterized is derived from the way emotions themselves are characterized. If, for example, emotions are taken to be centrally characterized by bodily feelings, then grasping the bodily feelings of another will be central to empathy. On the other hand, if emotions are more centrally characterized by a combination of beliefs and desires, then grasping these beliefs and desires will be more essential to empathy. The ability to imagine oneself as another person is a sophisticated imaginative process. However, the basic capacity to recognize emotions is probably innate and may be achieved unconsciously. Yet it can be trained and achieved with various degrees of intensity or accuracy.

Empathy necessarily has a “more or less” quality. The paradigm case of an empathic interaction, however, involves a person communicating an accurate recognition of the significance of another person’s ongoing intentional actions, associated emotional states, and personal characteristics in a manner that the recognized person can tolerate. Recognitions that are both accurate and tolerable are central features of empathy.

The human capacity to recognize the bodily feelings of another is related to one’s imitative capacities, and seems to be grounded in an innate capacity to associate the bodily movements and facial expressions one sees in another with the proprioceptive feelings of producing those corresponding movements or expressions oneself. Humans seem to make the same immediate connection between the tone of voice and other vocal expressions and inner feeling.

In the field of positive psychology, empathy has also been compared with altruism and egotism. Altruism is behavior that is aimed at benefitting another person, while egotism is a behavior that is acted out for personal gain. Sometimes, when someone is feeling empathetic towards another person, acts of altruism occur. However, many question whether or not these acts of altruism are motivated by egotistical gains. According to positive psychologists, people can be adequately moved by their empathies to be altruistic, and there are others who consider the wrong moral leaning perspectives and having empathy can lead to polarization, ignite violence and motivate dysfunctional behavior in relationships.


Materials and Methods

Subjects

Twenty-two subjects, 12 females and 10 males (Mage = 24.5 years SD = 3.53 age range from 20 to 33 years) participated in the experiment. All subjects were right-handed (Edinburgh Handedness Inventory, Oldfield, 1971), with normal or corrected-to-normal visual acuity. Exclusion criteria were neurological or psychiatric pathologies of the subjects or their close family members. Specifically, they did not show deficits related to depression (Beck Depression Inventory II, BDI, Beck, Steer, & Brown, 1996) and to anxiety (State-Trait Anxiety Inventory, STAI, Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1970): Exclusion criterion of the BDI Inventory was 19 points or lower (M = 8.95 SD = 0.46 score range from 2 to 12 points) for the STAI 39 points or lower (M = 28.45 SD = 1.03 score range from 27 to 45 points). No payment was provided for participation. Participants gave informed written consent and the research was approved by the Ethical Committee institution where the work was carried out. The experiment was conducted in accordance with the Declaration of Helsinki, and all the procedures were carried out with adequate understanding by the subjects. The Research Consent Form was submitted before participation in the study.

Stimuli

Subjects were required to view affective images depicting real interpersonal situations which represented two people who interacted in a common and familiar situation (e.g., at home, in a workplace, or on a journey). Colored images (16 cm in width and 10 cm in height) representing positive, negative, and neutral interactions were selected. Twenty-four pictures were used for each type of interaction. Positive interactions represented positive and emotionally comfortable situations (such as a handshake between two people) negative interactions represented negative and emotionally uncomfortable situations (such as a quarrel between two people) neutral pictures represented interactions without a specific emotional valence (such as two people sitting on a couch, see Figure 1 ). All images were similar in their perceptual features (i.e., their luminance, complexity, i.e., number of details in the scene, and characters’ genders: half of the actors were male and half were female).

Some examples of positive, neutral, and negative interactions.

In order to validate the image dataset, a pre-experimental procedure was adopted. Each depicted scene was evaluated by four judges on valence and arousal dimensions, using the Self-Assessment Manikin Scale (SAM) with a five-point Likert scale (Bradley & Lang, 1994, 2007). Separately for each condition (positive, negative, and neutral), ratings were averaged across all images presented. As shown by statistical analysis (two distinct repeated-measures analyses of variance [ANOVAs] applied to valence and arousal), images firstly differed in terms of valence (positive: M = 4.56, SD = 0.34 negative: M = 1.33, SD = 0.26 neutral: M = 2.75, SD = 0.37)—positive interactions were more positively rated than the other two categories, negative interactions were more negatively rated than the other two categories, neutral images were rated to be of intermediate valence between the other two categories (for all significant contrast comparisons, p ≤ .01). Secondly, with respect to arousal, the positive and negative interactions (positive: M = 4.23, SD = 0.24 negative: M = 4.72, SD = 0.25 neutral: M = 1.77, SD = 0.31) were rated as more arousing than the neutral interactions (for all significant contrast comparisons, p ≤ .01). In contrast, no significant differences were revealed between positive and negative interactions (p = .32).

Procedure

Subjects were seated in a dimly lit room, facing an LCD computer monitor that was placed at about 50 cm from the subject. The stimuli were presented using E-Prime 2.0 software (Psychology Software Tools, Inc) running on a laptop PC with a 15 in. screen (Acer TravelMate 250P). Images were presented in a random order in the center of the screen for 6 s, with an inter-stimulus interval of 8 s (see Figure 2 ).

Experimental setting with fNIRS, EEG, and autonomic measures.

Participants were required to view each stimulus during fNIRS/EEG measures recording, and they were asked to attend to the interpersonal situations during the entire time of exposition, focusing on the emotional conditions which characterized the represented human actors. Moreover, they were required to empathize with the two persons interacting with each other (“Try to put yourself into the shoes of the persons and to experience their feelings in this situation”). In order to facilitate empathizing with the depicted actors, the two actors were of about the same age as the experimental subjects.

Before scene presentations, a 2 min resting period was registered at the beginning of the experiment. Next, a familiarization phase followed, in which subjects saw and evaluated a set of images (one of each emotional category), different from the images used in the experimental phase. After the experimental phase, subjects were required to rate the pictures with the SAM on valence and arousal dimensions. As shown by statistical analysis (two repeated-measures ANOVAs for the valence and arousal measures), images differed in terms of valence (with more positive evaluations of positive than negative and neutral interactions, with more negative evaluations of negative than positive and neutral interactions, and with intermediate evaluations of neutral compared to positive and neutral interactions) and arousal (with significant differences between positive and neutral interactions, and between negative and neutral interactions, showing a higher arousal rating for positive and negative interactions). For all paired comparisons significance was assumed for an alpha level of .01 or lower.

A specific questionnaire was used in order to assess the subjects’ self-rating on key aspects of the subjective evaluation of the empathic task. The questionnaire was used in a de-briefing post-experimental section (a five-point Likert scale for each item, from low to high). The aspects examined included the degree of experienced empathy (“How much did you put yourself into the shoes of the actors and felt what they felt in the depicted situation?”), personal emotional involvement (“How much did you feel emotionally involved in the situation?”), semantic attribution of the situation (positive, negative, and neutral, “How did you classify the interpersonal situation?”), and emotional significance (high or low, 𠇍id you perceive an emotional significance of the situation?”). All subjects experienced a high sense of empathy (M = 4.11, SD = 0.26), were emotionally engaged in the task (M = 4.23, SD = 0.34), and were able to attribute a coherent emotional value to the pictures (for coherent semantic attribution of valence: M = 4.09, SD = 0.32 for emotional significance: M = 4.88, SD = 0.45).

EEG: Frequency Band Analysis

A 16-channel portable EEG-System (V-AMP, Brain Products) was used for data acquisition. An NIRS-EEG compatible ElectroCap with Ag/AgCl electrodes was used to record EEG from active scalp sites referred to earlobe (10/5 system of electrode placement). EEG activity was recorded from the following positions: AFF3, AFF4, Fz, AFp1, AFp2, C3, C4, Cz, P3, P4, Pz, T7, T8, O1, and O2 (for examples, see Figure 3 ). The cap was fixed with a chin strap to prevent shifting during the task. Additionally, one EOG electrode was placed on the lower side of the left eye.

Locations of the prefrontal measurement channels of EEG and fNIRS. For fNIRS, emitter-detector distance was 30 mm for contiguous optodes and near-infrared light of two wavelengths (760 and 850 nm) were used. NIRS optodes were attached to the subject’s head using a NIRS -EEG compatible cup, with respect to the international 10/5 system.

Data preprocessing has been conducted with BrainVision Analyzer 2 (Brainproducts). The data were recorded using a sampling rate of 500 Hz, with a notch filter of 50 Hz. The impedance of recording electrodes was monitored for each subject prior to data collection, and it was always kept below 5 kΩ (rejected epochs 4%). Blinks were also visually monitored. Ocular artefacts (eye movements and blinks) were corrected using an eye-movement correction algorithm that employs a regression analysis in combination with artefact averaging. After EOG correction and visual inspection, only artefact-free trials (not less than 22) were considered. To obtain a signal proportional to the power of the EEG frequency band, the filtered signal samples were squared and successively log-transformed (Pfurtscheller, 1992). Successively, the data were epoched, using a time window of 1 s and an average absolute power value was calculated for each electrode and condition. Artefact-free data have been used to compute power spectra for relevant EEG frequency bands by the Fast Fourier transform method (with a Hamming window of a length of 10%) that was used to obtain estimates of spectral power (μV 2 ) in 1 Hz wide frequency bins for each electrode site. Spectral power values were averaged across all epochs and were then transformed to power density values for different frequency bands. An average of the pre-experimental absolute power (2 min) was used to determine the individual power without stimulation. From this reference power value, individual power changes during stimulus viewing were determined as the relative stimulus-related decreases or increases. Digital EEG data (from all 15 active channels) were band-pass filtered in the following frequency bands: delta (0-3), theta (4-7), alpha (8-12), and beta (13-20). During data reduction, a bandpass filter was applied in the 0.01-50 Hz frequency band.

FNIRS

fNIRS measurements were conducted with the NIRScout System (NIRx Medical Technologies, LLC) using a six-channel array of optodes (four light sources/emitters and four detectors) covering the prefrontal area. Emitters were placed at AF3-AF4 and F5-F6 while detectors were placed at AFF1-AFF2 and F3-F4 (see Figure 3 ). Emitter-detector distance was 30 mm for contiguous optodes and a near-infrared light of two wavelengths (760 and 850 nm) was used. NIRS optodes were attached to the subject’s head using a NIRS-EEG compatible cup, with respect to the international 10/5 system.

With NIRStar Acquisition Software (NIRx Medical Technologies LLC), changes in the concentration of O2Hb and deoxygenated hemoglobin (HHb) were recorded from a 2 min starting baseline. Signals obtained from the six NIRS channels were measured with a sampling rate of 6.25 Hz and analyzed and transformed according to their wavelength and location, resulting in values for the changes in the concentration of O2Hb and HHb for each channel. Haemoglobin quantity is scaled in mM*mm, implying that all concentration changes depended on the path length of the NIR light in the brain.

With Nirslab Software (v2014.05 NIRx Medical Technologies LLC) the raw data of O2Hb and HHb from individual channels were digitally band-pass filtered at 0.01-0.3 Hz. Successively, the mean concentration of each channel within a subject was calculated by averaging data across the trials for 6 s from trial onset. Based on the mean concentrations in the time series, we calculated the effect size in every condition for each channel within a subject. The effect sizes (Cohen’s d) were calculated as the differences of the means of the baseline and trial divided by the SD of the baseline, d = (M1M2)/SD1. Accordingly, M1 and M2 are the mean concentration values during the baseline and trial, and SD1 the SD of the baseline. The mean concentration value of the 2 s immediately before the trial was used as a baseline. Then, the effect sizes obtained from the six channels were averaged in order to increase the signal-to-noise ratio. Although the raw data of NIRS were originally relative values and could not be averaged directly across subjects or channels, normalized data, such as the effect sizes, could be averaged regardless of the units of measurement (Matsuda & Hiraki, 2006 Schroeter, Zysset, Kruggel, & Von Cramon, 2003 Shimada & Hiraki, 2006). In fact, the effect size is not affected by differential pathlength factor (DPF, Schroeter et al., 2003). Instead of a block design, a continuous trial design was used in the present research.

Autonomic Measures

Biopac MP 150 system (Biopac Systems Inc) was used to record the autonomic activity. Electrocardiography (ECG) was recorded continuously in lead 1 from two electrodes attached to the lower wrist, with the positive pole on the left arm and the negative pole on the right arm. One more reference electrode was placed over the left ankle. The ECG signal was sampled at 1,000 Hz with the Biopac Acknowledge 3.7.1 software (Biopac Systems Inc) according to the manufacturer guidelines. ECG was converted to HR in number of beats per minute. The signal was low-pass filtered at 35 Hz and highpass filtered at 0.05 Hz for motor and ocular artefacts. For SCR, before attaching the electrodes, the skin was cleaned with alcohol and slightly abraded. The electrodes for SCR were attached to the distal phalanges of the first and second finger of the left hand. SCL was recorded using two Ag/AgCl electrodes and an isotonic gel. The signal was low-pass filtered at 10 Hz for motor, ocular, and biological artefacts. Ocular artefacts were then checked with a visual inspection to eventually eliminate specific elements. Trials with artefacts (2%) were excluded from the analysis. SCR elicited by each stimulus was registered continuously with a constant voltage. It was defined as the largest increase in conductance during emotional image presentation, with a cut-off of at least 0.3 μS in amplitude with respect to baseline (pre-stimulus) mean values. Baseline values were scored during the 2 min prior to task onset.


Definitions

Empathy definitions encompass a broad range of emotional states, including caring for other people and having a desire to help them experiencing emotions that match another person’s emotions discerning what another person is thinking or feeling and making less distinct the differences between the self and the other. It can also be understood as having the separateness of defining oneself and another a blur.

It also is the ability to feel and share another person’s emotions. Some believe that empathy involves the ability to match another’s emotions, while others believe that empathy involves being tenderhearted toward another person.

Having empathy can include having the understanding that there are many factors that go into decision making and cognitive thought processes. Past experiences have an influence on the decision making of today. Understanding this allows a person to have empathy for individuals who sometimes make illogical decisions to a problem that most individuals would respond with an obvious response. Broken homes, childhood trauma, lack of parenting and many others factors can influence the connections in the brain which a person uses to make decisions in the future.

Martin Hoffman is a psychologist who studied the development of empathy. According to Hoffman everyone is born with the capability of feeling empathy.

Compassion and sympathy are terms associated with empathy. Definitions vary, contributing to the challenge of defining empathy. Compassion is often defined as an emotion we feel when others are in need, which motivates us to help them. Sympathy is a feeling of care and understanding for someone in need. Some include in sympathy an empathic concern, a feeling of concern for another, in which some scholars include the wish to see them better off or happier.

Hugging someone who is hurt

Empathy is distinct also from pity and emotional contagion. Pity is a feeling that one feels towards others that might be in trouble or in need of help as they cannot fix their problems themselves, often described as “feeling sorry” for someone. Emotional contagion is when a person (especially an infant or a member of a mob) imitatively “catches” the emotions that others are showing without necessarily recognizing this is happening.

Since empathy involves understanding the emotional states of other people, the way it is characterized is derived from the way emotions themselves are characterized. If, for example, emotions are taken to be centrally characterized by bodily feelings, then grasping the bodily feelings of another will be central to empathy. On the other hand, if emotions are more centrally characterized by a combination of beliefs and desires, then grasping these beliefs and desires will be more essential to empathy. The ability to imagine oneself as another person is a sophisticated imaginative process. However, the basic capacity to recognize emotions is probably innate and may be achieved unconsciously. Yet it can be trained and achieved with various degrees of intensity or accuracy.

Empathy necessarily has a “more or less” quality. The paradigm case of an empathic interaction, however, involves a person communicating an accurate recognition of the significance of another person’s ongoing intentional actions, associated emotional states, and personal characteristics in a manner that the recognized person can tolerate. Recognitions that are both accurate and tolerable are central features of empathy.

The human capacity to recognize the bodily feelings of another is related to one’s imitative capacities, and seems to be grounded in an innate capacity to associate the bodily movements and facial expressions one sees in another with the proprioceptive feelings of producing those corresponding movements or expressions oneself. Humans seem to make the same immediate connection between the tone of voice and other vocal expressions and inner feeling.

In the field of positive psychology, empathy has also been compared with altruism and egotism. Altruism is behavior that is aimed at benefitting another person, while egotism is a behavior that is acted out for personal gain. Sometimes, when someone is feeling empathetic towards another person, acts of altruism occur. However, many question whether or not these acts of altruism are motivated by egotistical gains. According to positive psychologists, people can be adequately moved by their empathies to be altruistic, and there are others who consider the wrong moral leaning perspectives and having empathy can lead to polarization, ignite violence and motivate dysfunctional behavior in relationships.


4 SOCIAL/EMOTIONAL SKILLS YOU CAN EASILY PRACTICE WITH TEENS

Whether you are a parent or work directly with teens, here you can read about some concrete social/emotional skills and useful activities that can help teens practice them. We will cover basic information about Listening skills, Assertiveness, Emotional awareness, and Nonverbal communication.

Why practice social/emotional skills?

Whether we call them soft skills, social/emotional skills, social/emotional intelligence or growth mindset, there is a consensus among researchers and practitioners that we need certain abilities to achieve our fullest potential at school, in our professional careers, and in our private lives. These abilities help us recognize and manage our emotions, cope with obstacles and life challenges, and enhance communication skills and good interpersonal relations (including empathy).

ONLINE STEM CAMP WHERE STUDENTS
MASTER SOCIAL/EMOTIONAL SKILLS

According to an analysis of longitudinal studies in nine OECD countries published in Skills for Social Progress: The Power of Social and Emotional Skills by OECD in 2015:

“Children’s capacity to achieve goals, work effectively with others and manage emotions will be essential to meet the challenges of the 21st century.”

Besides acknowledging the importance of social/emotional skills such as perseverance, sociability, and self-esteem, the report discusses how policy-makers, schools, and families facilitate the development of social/emotional skills through intervention programs, teaching, and parenting practices.

All these abilities are interrelated and their development starts at home and continues throughout the school years. If parents and important adults show a high level of social/emotional maturity, it will be easier for kids to acquire these abilities simply by modeling their behavior.

However, it is always useful when children and teens have a chance to practice social/emotional skills under the guidance of experienced adults. The best case scenario is when programs for enhancing social/emotional skills are an integral part of an educational system and a local community’s initiatives.

Below, we will look at some important social/emotional skills and suggest simple activities for practicing them, adjusted to teens.

1. Social communication skill – Listening

Being able to hear what people are really saying is a valuable communication skill that has a major impact on the quality of our relations with others. You’ve probably already heard about Active Listening, a skill that allows us to hear not only the words people are saying but also the emotions they are reflecting through their nonverbal behavior. Both are important in understanding the whole message being communicated.

This is a complex skill that can be practiced. In the following activity, the focus is on practicing concentration listening to the verbal message with undivided attention. You can practice this activity with a group of teens in your home, in the classroom or in a workshop.

Instruction

Firstly, ask all the participants to sit in a circle. The first person starts to tell a story (whatever he/she wants). After 3-5 sentences, say “stop” and randomly choose another participant to continue. This person now has to repeat the last sentence said and then continue making up the story. If he cannot correctly repeat the last sentence after five seconds, he is disqualified. The game continues with the same rules and the winner is the last person remaining after everybody else is disqualified.

This is the competitive version of the game. However, you can make up your own version, without disqualifications or adding new elements that you find useful.

Have a discussion

Ask participants to reflect on the game. When and how was their attention distracted? What helped them concentrate and remember the previous sentence?

2. Social communication skill – Assertiveness

Assertiveness, as a style of communication, is characterized by the ability to directly and confidently express our genuine opinion, feelings, or attitudes, such that the rights of others and social circumstances are respected.

It is proven that assertiveness affects our self-esteem and self-confidence, so there’s no doubt that practicing assertiveness is useful for teens. It is a complex skill that can be acquired through a training program led by a trained coach/therapist. However, some aspects of assertiveness can be practiced through simple exercises at home and in a school setting.

Maybe the most important point is to assure teens that it’s okay to claim their rights and to ask, to initiate, to express their opinions and feelings. That it’s okay to say NO to other people in a respectful way.

In this exercise, the focus will be on encouraging teens to initiate a conversation in which they will ask something of others and express their opinion or feelings. It can be practiced as social challenges given to teens either by their parents or teachers.

Instruction

Firstly, a list of social challenges is created, taking into consideration a teen’s age or social needs. Challenges can be written down/printed on separate cards. If given consent to take part in the challenge, a teen takes a random card and his task is to do what is required on the card in the next 24 hours or over several days, as you jointly arrange.

Challenges can be practiced once a week or according to whatever schedule you agree upon.

Examples of social challenges:

  • Give an honest compliment to someone.
  • Learn two new things about somebody from your class.
  • Share with a friend what’s been on your mind lately.
  • Call customer service at your favorite store and ask for information about some product you like.
  • Tell your best friend what you like about him/her.
  • Ask a teacher (or a coach) for clarification of a task you didn’t understand completely.

Have a discussion

After the task is accomplished, it’s important to discuss with the teen how the particular challenge made him feel. Did he find it easy, hard, awkward, or something else? What could be alternative ways to ask, to express? How did others react?
The inspiration for this activity is taken and adjusted from the Speech Bubble SLP.

3. Emotional skill – Emotional self-awareness

We have already written about self-awareness as the basic ability to understand our own inner processes and to relate adequately with others. Emotional awareness, in this context the ability to recognize our own feelings, is the foundation of emotional intelligence.

Besides helping us be aware of our emotions, these skills are important for developing emotional intelligence, according to Daniel Goleman and his bestselling book Emotional Intelligence. Understanding why we feel a certain way and knowing how to handle these feelings, including self-motivation the ability to recognize the feelings of others (empathy) and to motivate them – these skills are crucial to success and happiness in every aspect of our lives and in our relationships with others.

In the following activity, the focus is on getting in touch with eight emotions a teen chooses, raising awareness of how a particular emotion manifests itself, and how it affects the teen’s life. It is based on art therapy principles and is performed individually. However, it can be practiced in groups, too. You need a white paper and colored markers.

Instruction

Firstly, ask a teen to draw a circle and divide it into eight pies. Then, ask him/her to dedicate each pie to one emotion and fill in each pie with a corresponding color or images that match his/her idea of what the emotion means to him/her. It may be that a teen has a problem coming up with eight emotions. You can assist him but never choose instead of him. Don’t push if he can’t come up with eight. Work with whatever he manages to present.

Have a discussion

After the teen is done with the drawing, initiate a dialogue. You may find these questions useful: What does each image mean to you? What made you choose those particular colors? When in your life do you experience this emotion? What emotion is dominant for you nowadays? What emotion is the hardest to handle? And so on.

If a teen has a problem in coming up with emotions, you can use Plutchik’s wheel of emotion to help him recognize emotions he would like to work on.

This exercise is taken and adjusted from the Art therapy directives BlogSpot.

4. Social/emotional skills – Understanding nonverbal communication

Good understanding of nonverbal communication is a sign of social and emotional intelligence.

The ability to observe and understand nonverbal signs during communication, or any other interaction between people, gives us tremendous information about the real message being communicated. It is especially important when we notice that the verbal message and nonverbal behavior are not harmonized. It also gives us a clue about the motives of the person we are communicating with or their emotional state.

Besides what is said, it is always important to follow HOW it is said. Basic nonverbal aspects of human behavior to be aware of include eye contact, the tone of voice, facial expression, gestures, personal distance, body language, and posture.

The following activity, based on acting and improvisation methodology, focuses on recognizing the emotional state of participants exposed to simulated social situations, through observing only their nonverbal behavior. A group is needed for this activity.

Instruction

Ask a volunteer from the group to leave the room. Separate instructions are given to him/her and to the group, who stays in the room in order to prepare for the final scene. While the volunteer is outside, each individual in the group has to choose one emotion and must express this emotion only through nonverbal behavior (acting). Remind them of the different aspects of nonverbal communication.

Meanwhile, the volunteer outside is given the task of coming up with several social situations familiar to teens such as: in class during family dinner on a date at a birthday party working on homework, etc.

Finally, when the volunteer is back to the room, he sets the scene: You’re in class (for example). All members of the group act as if they are in the classroom, including expressing their chosen emotional state nonverbally. They can use their voice but only in the form of inarticulate sounds. The volunteer observes their behavior and tries to guess how they feel. If he is confused, he can put them in another social situation (or only for fun:). The game can be repeated several times with different volunteers, emotions to guess, and social situations.

Have a discussion

After it is revealed which emotion has been presented by each member of the group, a discussion follows. You may find these questions useful: What are the main nonverbal indicators of this emotion? How did you feel while acting? Did anybody have difficulties acting in the scenes (why)? What do you usually do when you feel (this particular emotion)? What do you usually do when you recognize somebody acting like this? Was there something confusing and what? – A question to the volunteer.

Depending on available time and the goal of your group work you can go even deeper into a conversation about particular emotions. If you are interested in activities useful for teen’s emotional development, you may like this article.

Do you need more advice related to the social/emotional development of your teen? You’ve come to the right place!


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Excessive empathy, social cues and adaptive behavior evaluation - Psychology

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Results

Behavioral Results

Table 1 presents the descriptive statistics for each subscale of the IRI, IRI total scores and RSQ. The results showed that no differences in PT, FS, EC, PD subscales, IRI total scores and RSQ scores were found between the social exclusion group and the social inclusion group (ps > 0.05).

Table 1. Mean scores and standard deviation for IRI and RSQ.

An independent sample t-test was conducted to compare the self-reported social exclusion and social ostracism scores (see Figure 1). As expected, both scores in the social exclusion group were significantly higher than those in the social inclusion group after the Cyberball game (social exclusion scores: t = 7.383, p < 0.001, d = 2.3 social ostracism scores: t = 7.604, p < 0.001, d = 2.503). Such reliable differences continued up to the end of the experiment (social exclusion scores: t = 3.092, p = 0.004, d = 0.943 social ostracism scores: t = 2.679, p = 0.011, d = 0.816). The results revealed that the manipulation of the social exclusion was effective.

Figure 1. Self-reported social exclusion scores (A) and social ostracism scores (B) after the Cyberball task and after the experiment. *p < 0.05, **p < 0.01, ***pπ.001. Error bars denote standard errors.

We also performed an independent sample t-test on the need questionnaires and the PANAS scores. The results showed that scores for belonging, control, self-esteem, and meaningful existence of the social exclusion group were significantly lower than those of the social inclusion group (ps < 0.001). The positive affect score of the social exclusion group was also significantly lower than that of the social inclusion group (t = 𢄤.020, p < 0.001, d = 2.249), while the negative affect score of the social exclusion group was significantly higher than that of the social inclusion group (t = 4.338, p < 0.001, d = 1.353).

Finally, a two (group: social exclusion group and social inclusion group) ൲ (stimuli: painful and neutral pictures) mixed ANOVAS was conducted on the subjective unpleasantness scores. The results showed that the main effect of stimuli was significant in self-unpleasantness [F(1,40) = 372.458, p < 0.001, ηp 2 = 0.903] and in other-unpleasantness scores [F(1,40) = 507.693, p < 0.001, ηp 2 = 0.927]. Participants rated painful pictures as more unpleasant than neutral pictures from both perspectives (ps < 0.001). No other differences were found (lowest p = 0.581). We also conducted a similar mixed ANOVAS on reaction time and response accuracy of pain categorization. The results showed a significant main effect of stimuli on reaction time [F(1,40) = 9.488, p = 0.004, ηp 2 = 0.192]. Painful pictures resulted in longer reaction time compared to neutral stimuli (p = 0.004). No other differences were found (lowest p = 0.296). The descriptive statistics of reaction time and response accuracy are presented in Table 2.

Table 2. The descriptive statistics for reaction time and response accuracy in pictures classification task (M ± SD).

ERP Results

The averaged ERPs at central and parietal regions and the voltage topographies are presented in Figure 2. Averaged parietal amplitudes within the P3 and LPP time window are illustrated in Figure 3. Figure 4 present data distribution of two groups in averaged parietal P3 and LPP amplitudes for painful pictures and neutral pictures.

Figure 2. Average ERPs in the central, and parietal regions for painful pictures and neutral pictures in both groups. The voltage topographies illustrate the scalp distribution of N2, P3, and LPP components.

Figure 3. Averaged parietal (P3, P4, Pz) amplitudes for painful pictures and neutral pictures within the (A) P3 (300� ms) and (B) LPP (450� ms) time window in each group. *p < 0.05, **p < 0.01, ***pπ.001. Error bars denote standard errors.

Figure 4. Data distribution of two groups in averaged parietal (A) P3 and (B) LPP amplitudes for painful pictures and neutral pictures. SE, social exclusion group SI, social inclusion group.

For the N2 component, a 2 (group: the social exclusion group and the social inclusion group) ൲ (stimuli: painful and neutral pictures) mixed ANOVAS was conducted. There was a marginally significant main effect of stimuli [F(1,40) = 4.094, p = 0.050, ηp 2 = 0.093] while the main effect of group was not significant [F(1,40) = 2.808, p = 0.102]. Both groups exhibited a more positive shift in N2 amplitudes when watching painful stimuli in contrast with neutral stimuli (p = 0.05). The interaction between group and stimuli was not significant (p = 0.730).

For the P3 component, a two (group: the social exclusion group and the social inclusion group) ൲ (stimuli: painful and neutral pictures) mixed ANOVAS was conducted. The results showed a significant main effect of stimuli [F(1,40) = 4.176, p = 0.048, ηp 2 = 0.095], while the main effect of group [F(1,40) = 2.978, p = 0.092] was not significant. The interaction between stimuli and group [F(1,40) = 8.23, p = 0.007, ηp 2 = 0.171] was significant. There was a reliable simple effect of stimuli in the social exclusion group [F(1,40) = 12.669, p < 0.001, ηp 2 = 0.241] with painful stimuli eliciting smaller P3 amplitudes than neutral stimuli did. This effect was not significant in the social inclusion group [F(1,40) = 0.325, p = 0.572]. In addition, simple effects of group were found significant under the pain condition [F(1,40) = 4.934, p = 0.032, ηp 2 = 0.11] but not under non-pain condition [F(1,40) = 1.411, p = 0.242]. Subsequent pairwise comparison showed that painful pictures induced significantly smaller P3 amplitudes in the social exclusion group than those in the social inclusion group (p = 0.032).

We conducted a similar ANOVAS on the average LPP amplitudes at the parietal site as we did on the average P3 amplitudes and the results showed a significant main effect of stimuli [F(1,40) = 78.817, p < 0.001, ηp 2 = 0.663], and group [F(1,40) = 6.291, p = 0.016, ηp 2 = 0.136]. There was a reliable two-way interaction between group and stimuli [F(1,40) = 9.196, p = 0.004, ηp 2 = 0.187]. A significant simple effect of stimuli was observed in the social exclusion group [F(1,40) = 17.939, p < 0.001, ηp 2 = 0.31] and in the social inclusion group [F(1,40) = 67.704, p < 0.001, ηp 2 = 0.629] with painful stimuli eliciting larger LPP amplitudes than those elicited by neutral stimuli in both groups (ps < 0.001). There was also a reliable simple effect of group under the pain condition [F(1,40) = 9.072, p = 0.004, ηp 2 = 0.185] but not under the neutral condition [F(1,40) = 3.024, p = 0.09]. Subsequent pairwise comparisons suggested that the LPP amplitudes elicited in the social exclusion group were significantly smaller than those elicited in the social inclusion group (p = 0.004).

Correlation Between Subjective Ratings and ERP Amplitudes

We also calculated the correlation between self-reported unpleasantness scores and the mean amplitudes of ERPs induced by painful pictures in each time window to explore if the subjective ratings of unpleasantness were correlated with the electrophysiological activity elicited by the painful pictures. Subjective other-unpleasantness ratings were significantly correlated with central N2 amplitudes for painful stimuli (r = 𠄰.318, p = 0.04). The correlation between self-unpleasantness scores and central N2 amplitudes for painful stimuli were marginally significant (r = 𠄰.291, p = 0.062). Subjective other-unpleasantness ratings were significantly correlated with parietal LPP amplitudes for painful stimuli (r = 0.311, p = 0.045) and marginally significantly. correlated with parietal P3 amplitudes for painful stimuli (r = 0.308, p = 0.050). However, after we corrected the alpha level for multiple comparisons by FDR (false discovery rate) we found none of these correlations were significant (lowest p = 0.093). Moreover, we also examine whether the group differences exist in these correlations. The LPP amplitudes induced by painful pictures in the parietal region were positively correlated with the subjective ratings of self-unpleasantness and other-unpleasantness in the social inclusion group (self-unpleasantness: r = 0.491, p = 0.028 other-unpleasantness: r = 0.478, p = 0.033) whereas no correlation was found in the social exclusion group (self-unpleasantness: r = 𢄠.155, p = 0.49 other-unpleasantness: r = 𢄠.038, p = 0.867). The P3 amplitudes induced by painful pictures in the parietal region were positively correlated with the subjective self-unpleasantness scores in the social inclusion group (r = 0.461, p = 0.041) whereas no correlation was found in the social exclusion group (r = 𢄠.009, p = 0.968). However, the FDR results also showed that all the corrected p value in the social inclusion group were not significant (lowest p = 0.082). Therefore, our results showed that the ERP empathic responses are not significant with behavioral self-reported pain empathy.


In the Light of Evolution: Volume VII: The Human Mental Machinery (2014)

ROBERT M. SEYFARTH *&Dagger AND DOROTHY L. CHENEY &dagger

To understand the evolution of a Theory of Mind, we need to understand the selective factors that might have jump-started its initial evolution. We argue that a subconscious, reflexive appreciation of others&rsquo intentions, emotions, and perspectives is at the roots of even the most complex forms of Theory of Mind and that these abilities may have evolved because natural selection has favored individuals that are motivated to empathize with others and attend to their social interactions. These skills are adaptive because they are essential to forming strong, enduring social bonds, which in turn enhance reproductive success. We first review evidence from both humans and other animals indicating that reflexive and reflective mental state attributions are inextricably linked and play a crucial role in promoting affiliative social bonds. We next describe results from free-ranging female baboons showing that individuals who show high rates of affiliative behavior form stronger social bonds with other females. These bonds, in turn, are linked to fitness. We then provide data from three different types of social challenges (male immigration, changes in grooming behavior after the death of a close relative, and responses during playback experiments), suggesting that females who manifest high rates of affiliative behavior may also be more motivated to anticipate challenges, react adaptively to setbacks, and respond appropriately to social interactions.

Departments of * Psychology and &dagger Biology, University of Pennsylvania, Philadelphia, PA 19104. &Dagger To whom correspondence should be addressed. E-mail: [email protected]

Do animals have a Theory of Mind (ToM)? Answers to this question have tended to focus on two properties that might characterize a cognitive process. First, is an animal&rsquos recognition of other individuals&rsquo mental states reflexive, and therefore perhaps immediate and unconscious? Or is it reflective, and therefore more likely to be ruminative and conscious? Second, to what kinds of mental states are animals attentive: more rudimentary psychological states, like another individual&rsquos gaze direction or its intentions, or more complex states, like another individual&rsquos knowledge or beliefs? These distinctions are not easy to draw, even in humans, where reflective, conscious mindreading about others&rsquo knowledge and beliefs is built on and develops gradually from reflexive, unconscious recognition of, for example, another&rsquos direction of gaze (Onishi and Baillargeon, 2005 Apperly, 2012).

There is considerable evidence that many animals are reflexively attuned to other individuals&rsquo gaze, intentions, and emotions however, the degree to which they are also reflectively aware of others&rsquo knowledge and beliefs is less clear (Cheney and Seyfarth, 2007). Problems in assessment arise in part because whenever an animal behaves in ways that suggest an understanding of another&rsquos knowledge, its behavior can often also be explained by simpler mechanisms, including learned contingencies. A chimpanzee (Pan troglodytes) who takes food that a rival cannot see might do so because she understands the relation between seeing and knowing or because she has learned the behavioral rule that a rival is motivated to defend food at which he is looking. Although experiments have attempted to distinguish between these explanations (Kaminski et al., 2008 Bugnyar, 2011 Crockford et al., 2012 MacLean and Hare, 2012), results have not been easy to interpret. At the very least, they suggest that animals&rsquo understanding of others&rsquo psychological states is quite different and perhaps less subject to conscious reflection than adult humans&rsquo. Whatever the explanation, it is clear that attempting to identify precise, definitive benchmarks of mental state attribution in animals has proved to be more elusive and less productive than first hoped.

Here, we take a slightly different approach to the question of mental state attribution in animals and consider the selective factors that might have favored the evolution of a rudimentary ToM. We begin by assuming that a full-blown ToM evolved from more rudimentary, reflexive forms that were themselves adaptive in their own right. As a first step in understanding the evolution of a ToM, therefore, we need to understand the selective factors that might have jump-started these rudimentary forms. We argue that a subconscious, reflexive appreciation of others&rsquo intentions, emotions, and perspectives lies at the roots of even the most complex forms of ToM and that these abilities first evolved because natural selection favored individuals that were motivated to attend to other individu-

als&rsquo social interactions and empathize with them. These skills were favored by selection because they are essential to forming strong, enduring social bonds, which in turn have been shown to enhance reproductive success. We therefore propose that the evolution of a ToM ultimately derives from its role in facilitating the formation of social bonds.

We first review evidence from both humans and other animals indicating that reflexive and reflective mental state attributions are inextricably linked and play a crucial role in promoting affiliative social bonds. Then, using data on wild female baboons (Papio hamadryas ursinus), we suggest that individual variation in the motivation to attend to social interactions and react to social challenges is positively correlated with measures that have previously been shown to be linked to the formation of social bonds and, ultimately, enhanced reproductive success.

REFLEXIVE AND REFLECTIVE EMPATHY IN ANIMALS AND HUMANS

Any attempt to determine whether an animal does or does not understand what another individual knows or thinks is inevitably confounded by the fact that the reflective processes associated with higher levels of ToM are closely linked to&mdashand often hard to distinguish from&mdashthe more automatic, reflexive processes that underlie them (de Waal, 2012 Hecht et al., 2012). Although we are consciously aware of the distinction between our own and others&rsquo mental states, we are often unaware of the many cues on which this awareness is based. For example, although higher cortical areas, like the prefrontal cortex, are activated when a human attempts to determine whether another individual can see something, initial responses to gaze direction and goal-directed behavior also activate more primitive areas of the brain, including the superior temporal sulcus (STS) and the amygdala. In both humans and rhesus macaques (Macaca mulatta), the STS is particularly sensitive to the orientation of another individual&rsquos eyes (Jellema et al., 2000 Klein et al., 2009).

The same is true of intentional behavior. Although we have conscious access to our reflections about whether someone&rsquos actions are accidental or intentional, many of the neuronal responses that contribute to our eventual decision are more subconscious. In both humans and monkeys, mirror neurons in the inferior parietal lobule are activated when an individual both performs a specific action and he observes someone else perform that action. Significantly, many neurons begin to fire before the other individual actually performs the action, suggesting that these neurons encode not only the specific motor act but also the actor&rsquos intentions (Fogassi et al., 2005 Rizzolatti and Fabbri-Destro, 2009). Thus, our ability to recognize that gaze has informative content, or to consider whether behavior

is intentional, depends crucially on automatic, reflexive neuronal activity of which we are largely unaware.

Similar results emerge in studies of empathy. Reflective, explicit empathy involves the ability to recognize emotional states like grief or fear in others without necessarily experiencing the same emotions oneself (Hecht et al., 2012). However, reflective empathy evokes activity not just in the cortex but also more primitive areas of the brain shared with many animals, including the midbrain, the brainstem, and endocrine systems associated with reactivity, reward, and social attachment (Decety and Jackson, 2004 Decety, 2011). Although we can distinguish between our own and others&rsquo emotions, representations of emotions like pain, disgust, and shame in others also activate many of the same areas of the brain that are activated when we experience or imagine the same emotions ourselves (Rizzolatti and Fabbri-Destro, 2009). Feeling sympathy for or being nice to others is emotionally rewarding in part because it facilitates the release of dopamine, a neurotransmitter associated with personal reward (Decety, 2011). Trust, empathy, and sensitivity to others&rsquo affective states are all facilitated by neuropeptides associated with attachment, maternal behavior, and pair bonding in animals, particularly oxytocin (Carter et al., 2008 Snowdon et al., 2010). Thus, even the most reflective forms of empathy in humans are derived from and still strongly linked to more rudimentary forms.

Similarly, reflective imitation involves the ability to recognize the goals and intentions of another and to understand that, to achieve the same goal, one must copy that individual&rsquos actions. Human culture depends crucially on this ability, which is also shown to some degree by the great apes (Buttelmann et al., 2007). Even humans, however, are largely unaware of many of the behaviors in others that they routinely mimic. Like some animals, we have a reflexive, unconscious tendency to mimic the postures, mannerisms, and behavior of individuals with whom we are interacting.

As already noted, in the motor domain the same mirror neurons are activated when an individual performs a movement as when he observes another engaged in that movement. Similarly, both human and nonhuman primates reflexively follow the gaze of others (Shepherd et al., 2009), and both human and macaque neonates copy others&rsquo facial expressions (Meltzoff and Moore, 1977 Ferrari et al., 2006). The fact that such mimicking is associated with empathy is exemplified by the phenomenon of contagious yawning. It is well known that viewing others yawn can elicit spontaneous yawning in oneself. Even this apparently reflexive response, however, seems to vary according to an individual&rsquos sensitivity to more reflective behavior, including face recognition and understanding of others&rsquo mental states (Platek et al., 2003). Spontaneous yawning is rare or absent in children with autism spectrum disorder (Senju et al., 2007 Helt et al., 2010).

It also occurs at higher frequencies among kin and friends than among strangers, suggesting that contagious yawning is linked to and may also promote affiliation (Norscia and Palagi, 2011). These observations are not limited to humans: chimpanzees are also more likely to yawn in response to the yawns of familiar, as opposed to unfamiliar, individuals (Campbell and de Waal, 2011).

A variety of other observations on what has been termed the chameleon effect (Chartrand and Bargh, 1999) supports the view that reflexive mimicry is linked to the formation and maintenance of social bonds and has been favored by evolution because it promotes affiliation (Lakin et al., 2003). Experiments suggest that people unconsciously mimic others when attempting to foster rapport and increase their frequency of mimicry when they are excluded from a group (Lakin and Chartrand, 2003 Lakin et al., 2008). Being imitated increases helpful and affiliative behavior (Van Baaren et al., 2004) and activates areas in the brain associated with reward processing (Kühn et al., 2010). In contrast, not being imitated increases cortisol levels (Kouzakova et al., 2010).

Similar observations have been obtained in nonhuman primates. Captive capuchin monkeys (Cebus apella) are more willing to approach and exchange tokens with a human who mimics their actions than one who does not (Paukner et al., 2009). Male chimpanzees&rsquo long-distance pant hoots become more similar acoustically as individuals spend more time together (Mitani et al., 1999 Crockford et al., 2004), suggesting that call convergence is associated with, and may even promote, social affiliation.

In practice, it is almost impossible to distinguish reflective empathy from more reflexive forms and learned negative associations (de Waal, 2012). This problem is not surprising given neurological evidence that the two are closely linked. In an early experiment specifically designed to examine whether one monkey would respond to another&rsquos distress, rhesus macaques were trained to pull chains to obtain a food reward. The apparatus was then rigged so that a monkey in an adjacent cage received a shock each time a particular chain was pulled. Most of the monkeys soon stopped pulling the chain that delivered the shock, even though doing so deprived them of a reward. They were especially likely to avoid the chain if they had previously received shocks themselves (Masserman et al., 1964 Wechkin et al., 1964). Although the monkeys&rsquo responses might at first be interpreted as evidence for reflective empathy, it seems as likely that they became distressed when they saw the other monkey being shocked because it was linked to a negative association for themselves. However, because even the most reflective forms of human empathy also evoke activity in more reflexive, primitive brain systems, these alternative explanations may be impossible to disambiguate.

In a more recent experiment, macaques were given the option of delivering a reward to themselves, another monkey, or no one. Although subjects preferred to reward themselves over others, they nonetheless opted to reward their partner if the alternative was to reward no one. This preference was especially true if the partner was familiar (Chang et al., 2011). Significantly, the same brain areas that are activated in humans during such exchanges were also activated in monkeys (Chang et al., 2013), and again&mdashas in humans (Guastella and MacLeod, 2012)&mdashthe monkeys&rsquo vicarious reinforcement was enhanced if they first inhaled oxytocin (Chang et al., 2012).

Finally, in another experiment rats were placed in an arena with a cagemate trapped in a translucent tube (Ben-Ami Bartal et al., 2011). The free rats quickly learned how to open the tube to liberate their cagemates, and they continued to do so even when given an alternative option to open a tube containing chocolate. (In the latter case, the rat opened both tubes and shared the chocolate.) It is possible that the free rats&rsquo responses may have been provoked in part by their own elevated stress at hearing their cagemates&rsquo alarm calls. However, given neurological evidence that witnessing distress in others activates many of the same brain areas as experiencing distress oneself, this distinction becomes difficult to disambiguate.

In sum, a variety of evidence suggests that reflexive empathy and imitation in both humans and other animals have evolved because they promote affiliation and social bonding. Joint attention and joint action activate areas of the brain associated with the processing of reward, and they are facilitated by the release of oxytocin. Importantly, what seems to be rewarding to animals is not physical contact per se but the specific identity of the social partner. In socially monogamous tamarins (Saguinus oedipus), strongly bonded pairs exhibit higher oxytocin levels than more weakly bonded pairs (Snowdon et al., 2010). Among wild chimpanzees, urinary concentrations of oxytocin are higher after individuals groom with a closely bonded partner (both kin and nonkin) than with a less closely bonded partner (Crockford et al., 2013). Evidently, grooming with a close friend or relative is more emotionally rewarding than engaging in the same behavior with a less preferred partner.

If empathy and affiliation have indeed been under strong selective pressure and lie at the roots of ToM, it should be possible to link these behaviors to fitness. Indeed, there is growing evidence that such a link can be made, because empathy and affiliation help individuals to form and maintain social bonds, and these bonds promote fitness.

Strong, enduring social bonds are a distinctive and adaptive feature of many animal societies. Such bonds are not limited to those formed by heterosexual mated pairs but extend to same-sex bonds formed between both kin and nonkin. Correlations between same-sex bonds and measures of

health or reproductive success have been documented in rodents, horses, dolphins, chimpanzees, baboons, and humans (Seyfarth and Cheney, 2012). Strong bonds buffer individuals against stress and disease and perhaps as a result are correlated with longevity and offspring survival.

These observations suggest that natural selection has favored empathy and imitation, because they are part of the cognitive and emotional skills that an individual needs to recognize others&rsquo social relationships, understand their motives and intentions, and keep track of, anticipate, and react adaptively to social events and challenges. We now explore these questions in more detail, focusing on data derived from a long-term study of wild baboons living in the Okavango Delta of Botswana.

EMPATHY, SOCIAL BONDS, AND REPRODUCTIVE SUCCESS IN WILD FEMALE BABOONS

Like many other species of Old World monkey, baboons live in large social groups (

75 individuals) composed of both kin and nonkin. Males emigrate from their natal group at adulthood. Females assume dominance ranks similar to their mothers&rsquo, and the female dominance hierarchy typically remains stable for many years (Cheney and Seyfarth, 2007). Females form strong grooming relationships with a subset of other females, the strongest bonds occurring among close matrilineal kin (Silk et al., 2012).

Despite the fact that high-ranking females enjoy priority of access to resources such as food and mates, female reproductive success in baboons&mdashlike female reproductive success in humans and other animals&mdashis influenced less by a female&rsquos dominance rank than by the strength and stability of her bonds with other females. We evaluated females&rsquo bond strength using two indices of sociality. The first index, the Composite Sociality Index (CSI), measured dyadic bond strength based on females&rsquo rates of approaches, groom presents, grooming initiations, and grooming durations with other females. The second index, the Partner Stability Index (PSI), measured females&rsquo retention of their top three partners across years. Over a 17-year period, offspring survival was significantly positively correlated with the CSI (Silk et al., 2009), whereas longevity was significantly correlated with a combination of the strength and stability of females&rsquo relationships with their top partners (Silk et al., 2010). Females also experienced lower stress (as measured by fecal glucocorticoid metabolites) when their grooming network was more focused (Crockford et al., 2008). Thus, the strength and stability of females&rsquo social partners were correlated with several measures of fitness. Interestingly, however, variation in the strength of social bonds was not fully explained

by obvious demographic attributes like dominance rank or availability of kin. Although females established their closest bonds with kin, kin varied in the strength of their bonds, and some females without close kin established close bonds with others.

These observations suggest that some individuals are more motivated or skilled than others at establishing and maintaining social bonds and that variation in patterns of affiliation that are correlated with fitness may result in large part from variation in personality styles. We therefore attempted to determine whether different patterns of behavior were more or less associated with social bond strength.

Personality Styles and Social Bond Strength

We applied exploratory principal component analysis to the behavior of 45 female baboons over a 7-year period (Seyfarth et al., 2012). To construct the components that were used to identify personality dimensions, we calculated annual rates for several behaviors not considered in previous analyses of sociality. These behaviors included the frequency that females were alone, the rate at which they were friendly to other females, the rate at which they were aggressive to other females (corrected for dominance rank), and the frequency with which they grunted when approaching higher- and lower-ranking females. Among baboons, grunts serve as signals of benign intent and facilitate friendly interactions (Cheney et al., 1995). When females grunt to higher-ranking individuals, they are less likely to receive aggression. Conversely, when females grunt to lower-ranking individuals, those individuals are less likely to show submissive behavior. We were especially interested in the frequency with which females grunted to lower-ranking individuals, because such vocalizations do not benefit the signaler in any obvious way. Instead, they seem to function primarily to alleviate the anxiety of the recipient.

Our analysis identified three relatively stable personality dimensions, each characterized by a distinct suite of behaviors that could not be explained by dominance rank or availability of kin. Females scoring high on the Nice dimension were friendly to all females and often grunted to lower-ranking females, apparently to signal benign intent. Aloof females were aggressive, were less friendly, and grunted primarily to higher-ranking females. Loner females were often alone, were relatively unfriendly, and also grunted most often to higher-ranking females (Seyfarth et al., 2012). The baboons themselves apparently recognized these differences, because they approached females who scored high on Nice at high rates but approached females scoring high on Aloof and Loner at much lower rates (Seyfarth et al., 2012, table 1). Personality designations remained relatively stable over time.

Importantly, the different personality attributes were associated in different ways with measures of fitness. Females who scored high on Nice had strong social bonds (high CSI scores) and stable preferences for their top partners. Females who scored high on Aloof had lower CSI scores overall but very stable preferences with their top partners. In contrast, Loner females had significantly lower CSI scores, less stable partner preferences, and significantly higher glucocorticoid (GC) levels (Seyfarth et al., 2012, table 2).

These results suggest that there are costs and benefits associated with particular personality characteristics. For example, selection would seem to act against females scoring high on the Loner dimension, because these individuals were under more stress than others and formed weaker bonds that yielded low CSI scores and low partner stability. This observation begs the obvious question of why any female would adopt the Loner strategy. Loners were not isolated and unfriendly solely because of their subordinate status or lack of kin although these demographic factors contributed to their scores on this component, their behavior exacerbated them. Moreover, some Loners did have close kin, whereas other females who consistently scored high on Nice did not. If Loners were often the victims of circumstances, what skills or motivation allowed some individuals and not others to overcome these circumstances?

In sum, female baboons varied not only in the strength and stability of their bonds but also in the personality traits associated with these bonds&mdashparticularly the ability or motivation to interact with others.

To test whether variation in personality traits was also associated with variation in females&rsquo ability and/or motivation to keep track of, anticipate, and react adaptively to social events, we examined females&rsquo responses to three different types of social challenges. We were interested not in females&rsquo responses to adversity itself&mdashbecause we expected little individual variation in responses to real, ongoing threats&mdashbut their ability to anticipate adversity, respond adaptively to adversity after it had occurred, and keep track of social interactions that had the potential to influence their own relationships. Because previous research had shown that, as a group, most females responded positively to these challenges, we expected that any differences that did emerge would be small.

Personality Styles and Responses to Social Challenges

In the Okavango Delta, male immigrants that achieve alpha status often commit infanticide (Cheney and Seyfarth, 2007). Perhaps as a result, both immigration and instability in the alpha male position cause a sig-

nificant increase in females&rsquo GC levels. Lactating females are particularly likely to experience elevated GC levels, though during some immigration events females in all reproductive states show significant increases (Beehner et al., 2005 Engh et al., 2006b Wittig et al., 2008). These responses are associated with a decrease in sociality among females (Wittig et al., 2008), which may reflect their heightened vigilance and reactivity.

We examined increases in females&rsquo GC levels from 2 weeks before to 2 weeks after four different immigration events in 2002, 2003, 2004, and 2005. All events involved the takeover of the alpha male position. We tested whether the magnitude of the GC changes of individual females was linked to their personality styles. Importantly, by focusing on GC changes in the 2 weeks immediately after the immigration event, we were able to assess females&rsquo anticipation of the threat of infanticide rather than their responses to the actual act.

Consistent with previous results, the majority (75 percent) of individuals showed an increase in GC levels after immigration. However, some of the variation in females&rsquo GC levels also seemed to be linked to their personality scores. The correlation between percent change in GC levels and Aloof scores was weakly negative (b = &minus10.15, SE = 10.5, t = &minus0.962, P > 0.10), as was the correlation for Loner scores (b = &minus11.24, SE = 11.62, t = &minus0.968, P > 0.10) (Fig. 2.1). In contrast, the correlation between Nice scores and change in GC levels was positive, though nonsignificant (b = 5.278, SE = 10.00, t = 0.527, P > 0.10) (Fig. 2.1). There were no significant effects of reproductive state.

Thus, individuals who scored high on Nice tended to show increases in GC levels in response to male immigration, whereas those who scored high on Aloof and Loner tended to be less responsive.

Changes in Grooming Behavior After the Death of a Close Relative

Females also experience elevated GC levels after the death of a close adult female relative, probably in part because the death results in the loss of a regular grooming partner. Previous analyses have shown that, in the 3 months after this loss, bereaved females increase both grooming rates and the number of female grooming partners (Engh et al., 2006a). These responses may facilitate the repair of females&rsquo social networks through the establishment of new bonds.

To examine individual differences in response to this challenge, we compared the number of each bereaved female&rsquos different grooming partners in the 3 months after the death of a close female relative with the mean number of grooming partners for unaffected females in the group during the same period (controlling for reproductive state). (This method was chosen to control for variation in sampling rates across time.) Whether

FIGURE 2.1 Percent change in females&rsquo GC levels from 2 weeks before to 2 weeks after the immigration of a potentially infanticidal male. Only immigration events in which an immigrant attained the alpha rank were included in analysis n = 33 females present for 1&ndash3 events for a total of 64 female events. Dashed lines indicate no change solid lines indicate least-square regression (statistics and probability values given in the text). The x axis denotes females&rsquo scores on each of the three principal components (Aloof, Loner, and Nice) in the immigration year. Each point represents 1 female-year.

females had a higher or lower number of partners than unaffected females seemed to be related to their personality scores. Females scoring high on the Loner component had fewer grooming partners than unaffected females (b = &minus1.138, SE = 0.866, t = &minus1.314, P = 0.203). In contrast, correlations between the relative number of grooming partners were positive but nonsignificant for both Aloof (b = 0.366, SE = 0.624, t = 0.586, P = 0.564) and Nice (b = 0.799, SE = 0.509, t = 1.569, P = 0.132) scores (Fig. 2.2).

Thus, females who scored high on the Loner component had fewer grooming partners compared with unaffected females in the ensuing 3 months, suggesting that they were unsuccessful in rebuilding their social network. This decrease occurred despite the fact that females who scored high on the Loner component tended to show a greater increase in GC levels than other females in the 2 weeks after the death of a close relative,

particularly when that relative was a mother or adult daughter (rs = 0.771, N = 6, P > 0.10). In contrast, females who scored high on the Aloof and Nice components responded to the death of a close relative by grooming comparatively more females than unaffected individuals.

Variation in the Strength of Responses During Playback Experiments

Playback experiments are designed to test subjects&rsquo knowledge of other individuals&rsquo dominance ranks and kinship as well as their memory of recent social interactions and their participants. Consider reconciliation, for example. Baboons often grunt to their opponents after aggression, and these grunts serve to restore opponents to baseline levels of tolerance (Cheney and Seyfarth, 1997). In an experiment designed to determine

FIGURE 2.2 The relative number of a female&rsquos different grooming partners in the 3 months after the death of a close relative (mother, adult daughter, or sister) compared with the mean number of grooming partners for all other females in those months (controlled for reproductive state) n = 18 females who lost from one to three close relatives for a total sample of 24 female-years. One outlier was removed. Legend is the same as in Fig. 2.1.

whether reconciliation by kin could serve as a proxy for direct reconciliation, victims were played the grunt of the close relative of a recent opponent. Subjects were significantly more likely to approach their opponent after hearing a grunt from their opponent&rsquos relative (test condition) than after hearing a grunt from a female from a different matriline (control condition) (Wittig et al., 2007b). In so doing, subjects showed that they remembered not only the specific nature of a recent interaction and the identity of the participants but also the kinship relations (or close associates) of other females in their group. Thus, by responding more strongly during tests than control trials, subjects showed that they were not only reactive but also appropriately reactive, in the sense that they responded strongly only to relevant stimuli.

For this analysis, we considered variation in females&rsquo responses to playback stimuli in five previously conducted experiments that tested baboons&rsquo memory of recent social interactions and knowledge of other individuals&rsquo relationships (summary of the playback experiments used in the analysis is available from the authors) (Bergman et al., 2003 Engh et al., 2006c Wittig et al., 2007a,b Cheney et al., 2010). We used duration of looking toward the speaker in test compared with control trials as our dependent measure, because this response was used in all experiments. Because the strength of subjects&rsquo responses varied across experiments, we ranked each subject&rsquos duration of response in each experiment relative to response duration of other subjects. Thus, a subject who responded more strongly in the test vs. the control condition received a high positive ranking, whereas a subject that responded more strongly in the control condition received a negative ranking.

The correlations between strength of response and Aloof, Loner, and Nice scores were all positive, but only the Nice scores reached statistical significance (Aloof: b = 0.381, SE = 0.580, t = 0.657, P > 0.10 Loner: b = 0.625, SE = 0.634, t = 0.986, P > 0.10 Nice: b = 1.250, SE = 0.566, t = 2.246, P = 0.027) (Fig. 2.3). Thus, although most females responded more strongly during test than control trials, females who scored high on the Nice component were the most responsive.

Discussion: Social Challenges

Previous analyses (Seyfarth et al., 2012) showed that females scoring high on the Nice component have stronger social bonds with other females. The data presented here suggest that, by three independent measures, these individuals may also be more responsive to social challenges and more motivated to attend to social interactions within their group (Table 2.1).


Results

The grand average ERPs at electrodes of interest (F3, F4, Fz, C3, C4, Cz, Pz, PO7 and PO8) and scalp topographies prior to PCA are illustrated in Figs 2 and 3A. Visual stimuli of the three categories (facial expressions, face pictures and arm pictures) elicited similar ERP components. At frontocentral sites, an N1 component was apparent, followed by a vertex positive potential (VPP), an N2 component, and finally a long lasting late positive complex (LPC). At temporo-occipital sites, posterior P1 and N170 components (see Supplementary Information) were seen.

Grand average ERPs in response to three stimulus categories under pain and no-pain conditions at frontocentral (F3, F4, Fz, C3, C4 and Cz) and parieto-occipital (Pz, PO7 and PO8) electrode sites. All stimuli elicited similar components. At frontocentral sites, an N1 component is apparent, followed by a VPP component, an N2 component, and a long lasting LPC while at temporo-occipital sites, a posterior P1 component and an N170 component are elicited. Negative amplitudes are plotted upwards. (A) ERPs in response to painful expressions (red solid lines) and neutral expressions (red broken lines). (B) ERPs in response to needle-penetrated faces (green solid lines) and Q-tip-touched faces (green broken lines). (C) ERPs in response to needle-penetrated arms (blue solid lines) and Q-tip-touched arms (blue broken lines).

Topographical maps and statistical results of ERP components. (A) Scalp topographies of N1, VPP, N2, and LPC components (from top to bottom), plotted separately for each experimental condition (from left to right: painful expressions, neutral expressions, needle-penetrated faces, Q-tip-touched faces, needle-penetrated arms and Q-tip-touched arms). Boxed plots indicate a significant difference in ERP amplitude revealed by a Bonferroni-corrected t test. (B) Post hoc comparisons on condition × category interaction effects for N1, VPP, N2, and LPC amplitudes were conducted separately. Asterisks indicate significant differences in amplitude. **P < 0.01 ***P < 0.001. Error bars represent standard errors of the mean.

Painful scenes elicited larger N1 potentials than neutral scenes, and N1 amplitudes were higher in response to face-containing pictures (i.e., facial expressions and face pictures) than to arm pictures (expressions vs. arms, P < 0.001 faces vs. arms, P < 0.001). A 3-way ANOVA on N1 amplitude revealed a significant main effect of condition [F(1, 276) = 56.18, P < 0.001, η P 2 = 0.17], stimulus category [F(2, 552) = 25.70, P < 0.001, η P 2 = 0.09], and laterality [F(2, 276) = 4.34, P = 0.014, η P 2 = 0.03], and a significant interaction between category × laterality [F(4, 552) = 5.13, P < 0.001, η P 2 = 0.04]. Post hoc analysis revealed significant differences between the needle-penetrated face and the Q-tip-touched face (P < 0.001), and between the needle-penetrated arm and the Q-tip-touched arm (P = 0.001 Fig. 3A and B). No differences were observed between painful expressions and neutral expressions (P > 0.999 Fig. 3A and B). Interestingly, when gender was taken into consideration, the early distinction between the needle-penetrated face and the Q-tip-touched face, and between the needle-penetrated arm and the Q-tip-touched arm were only found in females, but not in males, as revealed by the significant gender × condition × category interaction effect [F(1.97, 545.86) = 8.82, P = 0.005, η P 2 = 0.02].

The 3-way ANOVA on N1 latency revealed a significant main effect of stimulus category [F(1.64, 447.30) = 5.29, P = 0.009, η P 2 = 0.02]. Post hoc comparisons indicated that face-containing pictures were detected faster than arm pictures (expression vs. arm, P = 0.041 face vs. arm, P = 0.006). In addition, the condition × category interaction [F(1.99, 547.98) = 4.77, P = 0.009, η P 2 = 0.02] was significant.

The VPP showed a greater amplitude in the pain condition relative to the no-pain condition. Face-containing pictures produced marked enhancement in the amplitude of the VPP over arm pictures (expression vs. arm, P < 0.001 face vs. arm, P < 0.001). The 3-way ANOVA for the VPP amplitude yielded a significant main effect of condition [F(1, 276) = 22.37, P < 0.001, η P 2 = 0.07] and category [F(1.58, 436.79) = 130.93, P < 0.001, η P 2 = 0.32], and a significant interaction effect of condition × category [F(1.79, 493.27) = 8.62, P < 0.001, η P 2 = 0.03]. Post hoc comparisons revealed a significant difference between painful expressions and neutral expressions (P < 0.001 Fig. 3A and B). No differences were found for the other two (face pictures and arm pictures) stimulus categories (needle-penetrated face vs. Q-tip-touched face, P > 0.999 needle-penetrated arm vs. Q-tip-touched arm, P > 0.999 Fig. 3A and B).

For the VPP latency, the 3-way repeated measures ANOVA revealed a significant main effect of category [F(1.28, 291.63) = 291.63, P < 0.001, η P 2 = 0.51], and a significant condition × category interaction effect [F(1.92, 529.35) = 4.77, P < 0.001, η P 2 = 0.04). Similar to the results for the N1 component, face-containing pictures elicited shorter VPP latencies than arm pictures (expression vs. arm, P < 0.001 face vs. arm, P < 0.001 Fig. 2). In addition, there was a significant difference between painful expressions and neutral expressions (painful expression > neutral expressions, P < 0.001), whereas no differences were found for the other two (face pictures and arm pictures) stimulus categories (needle-penetrated face vs. Q-tip-touched face, P > 0.999 needle-penetrated arm vs. Q-tip-touched arm, P > 0.999).

The N2 component showed a positive shift in the pain condition compared to the no-pain condition. Facial expression pictures elicited a more positive N2 than face pictures and arm pictures (expression vs. face, P < 0.001 expression vs. arm, P < 0.001 Fig. 3). In a 3-way repeated measures ANOVA of N2 amplitude, there were significant main effects of condition [F(1, 276) = 39.93, P < 0.001, η P 2 = 0.13], category [F(1.58, 436.65) = 19.66, P < 0.001, η P 2 = 0.07], and laterality [F(2, 276) = 4.76, P = 0.009, η P 2 = 0.03], and significant interaction effects of condition × category [F(1.98, 545.41) = 28.00, P < 0.001, η P 2 = 0.09], condition × laterality [F(2, 276) = 3.43, P = 0.034, η P 2 = 0.02], category × laterality [F(3.16, 436.65) = 6.07, P < 0.001, η P 2 = 0.04], and condition × category × laterality [F(3.95, 545.41) = 3.10, P = 0.016, η P 2 = 0.02]. Post hoc comparisons indicated that N2 amplitudes were significantly different between painful expressions and neutral expressions (P < 0.001, Fig. 3B), and between needle-penetrated arms and Q-tip-touched arms (P < 0.001, Fig. 3B). No difference in N2 was observed between needle-penetrated faces and Q-tip-touched faces (P = 0.128, Fig. 3B). The pain-related N2 amplitude modulation was significant at midline and right hemisphere electrodes (both Ps < 0.001), but was not significant at left hemisphere electrodes (P = 0.463).

There was a significant main effect of category on N2 latency [F(1.80, 495.49) = 71.34, P < 0.001, η P 2 = 0.21]. The N2 latencies elicited by facial expression pictures were longer than those elicited by face pictures but shorter than those elicited by arm pictures (all Ps < 0.001).

The 3-way ANOVA of LPC revealed significant main effects of condition [F(1, 276) = 221.43, P < 0.001, η P 2 = 0.45] and category [F(1.94, 535.98) = 497.80, P < 0.001, η P 2 = 0.64], and significant interaction effects of condition × category [F(1.87, 516.39) = 55.74, P < 0.001, η P 2 = 0.17), condition × laterality [F(2, 276) = 5.15, P = 0.006, η P 2 = 0.04] and category × laterality [F(3.88, 535.98) = 3.83, P = 0.005, η P 2 = 0.03]. Post hoc analyses showed that the pain vs. no-pain difference in LPC existed in expression pictures and arm pictures (both Ps < 0.001), but not in face pictures (P = 0.058).

PCA results

The LPC component was divided into two separate subcomponents by temporospatial PCA: P3 and LPP. The microvolt rescaled factor scores of the PCA-derived P3 and LPP components are presented in Fig. 4A. Two-way ANOVAs were conducted on these components, to better illustrate the empathic process over the long lasting late component (see Fig. 4B and C).

PCA derived P3 and LPP components. (A) Virtual PCA derived P3 (left) and LPP (right) component waveforms for each experimental condition. (B) Scalp topographies of P3 (upper panel) and LPP (lower panel) components, plotted separately for each experimental condition (from left to right: painful expressions, neutral expressions, needle-penetrated faces, Q-tip-touched faces, needle-penetrated arms and Q-tip-touched arms). Boxed plots indicate a significant difference revealed by a Bonferroni-corrected t test. (C) Post hoc comparisons on condition × category interaction effects for P3 (left) and LPP (right) components. Asterisks indicate significant differences in amplitude. ***P < 0.001. Error bars represent standard errors of the mean.

The P3 amplitudes were greater in response to painful scenes than to neutral scenes, and face-containing pictures elicited greater P3 amplitudes than arm pictures (expression vs. arm, P < 0.001 face vs. arm, P = 0.035 Fig. 4B and C). The 2-way ANOVA revealed a significant main effect of condition [F(1, 30) = 42.37, P < 0.001, η P 2 = 0.59] and category [F(2, 60) = 12.03, P < 0.001, η P 2 = 0.29], and a significant interaction effect between these variables [F(2, 60) = 6.26, P = 0.003, η P 2 = 0.17]. Post hoc analysis revealed a significant pain-related difference between painful expressions and neutral expressions, and between needle-penetrated arms and Q-tip-touched arms (both Ps < 0.001 Fig. 4B and C). No significant difference was found between the needle-penetrated face and the Q-tip-touched face (P = 0.622 Fig. 4B and C).

Painful scenes elicited considerably greater LPP components than neutral scenes. Expression pictures elicited the largest LPP, while arm pictures elicited the smallest LPP (all Ps < 0.001). In the 2-way ANOVA for the LPP amplitude, there were significant main effects of condition [F(1, 30) = 15.85, P < 0.001, η P 2 = 0.35] and category [F(2, 60) = 61.02, P < 0.001, η P 2 = 0.67], and a significant condition × category interaction effect [F(2, 60) = 10.90, P < 0.001, η P 2 = 0.27]. Post hoc comparisons revealed that the pain effect only existed in the expression category (P < 0.001 Fig. 4B and C), suggesting long lasting empathic processing for pain expression.

Behavioral performance

Table 1 summarizes the mean RT and accuracy rate under each category and condition. Participants responded faster to pain pictures than neutral pictures [2-way ANOVA, condition effect: F(1, 30) = 19.52, P < 0.001, η P 2 = 0.39] and took more time to judge expression pictures than to judge face and arm pictures [all Ps < 0.001 category effect: F(2, 60) = 30.12, P < 0.001, η P 2 = 0.50].

Participants were less accurate in judging painful scenes than neutral scenes, and also less accurate in judging expressions than faces and arms (all Ps < 0.001). The 2-way repeated measures ANOVA revealed significant main effects of condition [F(1, 30) = 4.89, P = 0.035, η P 2 = 0.14] and category [F(1.37, 41.18) = 40.80, P < 0.001, η P 2 = 0.58], and a significant interaction effect of condition × category [F(1.35, 40.61) = 5.71, P = 0.014, η P 2 = 0.16].

Correlation analyses

Correlation analyses showed no associations between electrophysiological measures and any of the psychometric measures or behavioral performance.