Neural mechanisms of social decision-making in the primate amygdala

Social decisions require evaluation of costs and benefits to oneself and others. Long associated with emotion and vigilance, the amygdala has recently been implicated in both decision-making and social behavior. The amygdala signals reward and punishment, as well as facial expressions and the gaze of others. Amygdala damage impairs social interactions, and the social neuropeptide oxytocin (OT) influences human social decisions, in part, by altering amygdala function. Here we show in monkeys playing a modified dictator game, in which one individual can donate or withhold rewards from another, that basolateral amygdala (BLA) neurons signaled social preferences both across trials and across days. BLA neurons mirrored the value of rewards delivered to self and others when monkeys were free to choose but not when the computer made choices for them. We also found that focal infusion of OT unilaterally into BLA weakly but significantly increased both the frequency of prosocial decisions and attention to recipients for context-specific prosocial decisions, endorsing the hypothesis that OT regulates social behavior, in part, via amygdala neuromodulation. Our findings demonstrate both neurophysiological and neuroendocrinological connections between primate amygdala and social decisions.How we treat others impacts not only their well-being but our own. Human society depends on cooperation, charity, and altruism, as well as institutions to regulate selfish biases. In humans, these behaviors involve perspective-taking, empathy, and theory of mind (1, 2), and the rudiments of these capacities appear to mediate complex social behavior in animals (3). Recent research has sketched a rough outline of the neural circuits that contribute to complex social behavior (4, 5). These comprise a set of domain-general brain areas, including the ventromedial prefrontal cortex and ventral striatum, that process information about reward and punishment and contribute to decision-making, and a set of specialized areas, including the temporoparietal junction and medial prefrontal cortex, that process specifically social information (4, 6). How social and nonsocial signals in these circuits are integrated to mediate decisions with respect to others remains imperfectly understood, in part, due to the indirect nature of hemodynamic signals measured in human neuroimaging experiments that constitute the bulk of this research. Recent advances in the development of neurophysiological and neuropharmacological models of social decision-making, however, permit more direct inquiry into the neural mechanisms mediating other-regarding behavior (7–11).The amygdala, especially the basolateral division (BLA), has been implicated in both decision-making and social perception, inviting the possibility that it contributes to decision-making with respect to others (12–17). This set of nuclei is well known for contributions to emotional experience and expression, especially fear. More recent studies demonstrate activity in BLA tracks the value of rewards and punishments (18), predicts risky financial decisions (19), reflects internal motivational goals (20), and correlates with vigilance and attention (21). BLA also signals social information, such as facial expressions and the direction of gaze, and has been implicated in theory of mind and emotional empathy (22–26). Notably, oxytocin (OT), a neurohypophysial hormone that modulates many social behaviors (27), appears to do so via the amygdala in humans and nonhuman primates (28–30). Intranasal OT reliably modulates hemodynamic activity in the amygdala in healthy humans (28, 29, 31), children with autism (32), and rhesus macaques (30). These changes in amygdala activity are related to social cognition. These observations invite the hypothesis that BLA directly mediates decision-making with respect to others (24). How neurons in BLA respond during social decisions, however, remains unknown.Here, we examine this hypothesis using a modified dictator game, which we previously used to probe social information signaling by neurons in the anterior cingulate and orbitofrontal cortices (7) and the impact of inhaling OT on social decision-making (33). We previously reported that the preference to allocate reward to the other monkey is enhanced by greater familiarity between the two animals, and is abolished if the recipient is replaced with a juice collection bottle (34). We also reported that reward withholding is reduced when actor monkeys are dominant toward recipients, and the variability and the degree of preferences often depend on the identity of the recipients (34). We show, to our knowledge for the first time, that BLA neurons respond during social decisions, these responses signal the value of rewards chosen for self and others using a similar coding scheme, and these signals are correlated with social preferences. We further show that unilateral infusion of OT into BLA increases both the frequency of prosocial decisions and attention paid to the recipients of prosocial decisions. Together, these findings directly implicate the amygdala in social decision-making and constrain models of its computational role in the decision process.     

Direct and indirect punishment among strangers in the field

Many interactions in modern human societies are among strangers. Explaining cooperation in such interactions is challenging. The two most prominent explanations critically depend on individuals’ willingness to punish defectors: In models of direct punishment, individuals punish antisocial behavior at a personal cost, whereas in models of indirect reciprocity, they punish indirectly by withholding rewards. We investigate these competing explanations in a field experiment with real-life interactions among strangers. We find clear evidence of both direct and indirect punishment. Direct punishment is not rewarded by strangers and, in line with models of indirect reciprocity, is crowded out by indirect punishment opportunities. The existence of direct and indirect punishment in daily life indicates the importance of both means for understanding the evolution of cooperation.The extent of human cooperation is unique in the animal world (1). This is remarkable given that many interactions in large modern societies are one-shot encounters between strangers. Cooperation in these instances cannot be explained by the benefits that accrue from repeated encounters (1–5). The two most prominent explanations for cooperation in such instances both rely on individuals’ willingness to punish those who fail to cooperate (2, 3). The difference lies in the form punishment takes and its material consequences. The first mechanism involves the direct punishment of those behaving antisocially (6–11). Direct (or altruistic) punishment is individually costly, e.g., because it requires time and effort to enact, and the punisher bears the risk of retaliation when confronting a noncooperator (12–14). As a result, explaining how the propensity to punish directly may have evolved constitutes a major evolutionary puzzle (7, 15–20): “We seem to have replaced the problem of explaining cooperation with that of explaining [costly] punishment” (21).In contrast to models of direct punishment, cooperation in models of indirect reciprocity is supported by the threat of indirect punishment (22–26): Individuals who come across others who are known to have behaved selfishly punish them by withholding reward (27–29). The key difference is that, unlike direct punishment, indirect punishment need not be costly as individuals may gain by withholding reward. Thus, explaining its evolution is less challenging. The ability to punish indirectly, however, raises the question of how instances of direct punishment may be explained (23). Why would individuals use direct costly punishment when they can withhold reward? The typical explanation is that direct punishers are rewarded by others who value the social norm and wish to maintain it: “In reality, … most punishment actions among humans are associated with the expectation of a delayed material gain” (23). Reward may take, for example, the form of a gift, positive feedback or an offer to help. This increases the punisher’s benefit from enforcing cooperation and may help offset the associated costs (4, 5, 24). In other words, direct punishment need not be costly in net terms for the punisher. However, there is little empirical evidence that strangers reward direct punishment (30, 31). If direct punishment is not rewarded in daily life, evolutionary forces will lead cooperators to use indirect punishment (23, 25).For settling the debate on the importance of direct vs. indirect punishment for the evolution of cooperation among strangers, field experimental evidence from natural interactions is essential (2, 32, 33). From a theoretical perspective, the persistence of direct punishment is puzzling because it is assumed to be individually costly for the punisher, whereas this usually is not the case for indirect punishment. It is not obvious, however, that this holds true in daily life, in which direct punishment may be rewarded sufficiently (5, 23, 24) and in which indirect punishment by withholding reward also may involve substantial psychological or social costs (34, 35). Previous studies have explored direct punishment (9) and indirect reciprocity (36) in natural field settings, but in isolation from each other.To our knowledge, this study presents the first evidence from a natural field experiment exploring the demand for direct and indirect punishment, separately and jointly. We address the following three questions: (i) Are punishers rewarded by strangers in one-shot interactions? (ii) Do individuals punish antisocial behavior indirectly by withholding reward? (iii) How is the propensity to punish directly affected by the opportunity to withhold reward? These questions are key to understanding how the propensity to punish selfish behavior may have evolved and, subsequently, the evolution of cooperation.     

Endocannabinoid signaling mediates oxytocin-driven social reward

Marijuana exerts profound effects on human social behavior, but the neural substrates underlying such effects are unknown. Here we report that social contact increases, whereas isolation decreases, the mobilization of the endogenous marijuana-like neurotransmitter, anandamide, in the mouse nucleus accumbens (NAc), a brain structure that regulates motivated behavior. Pharmacological and genetic experiments show that anandamide mobilization and consequent activation of CB₁ cannabinoid receptors are necessary and sufficient to express the rewarding properties of social interactions, assessed using a socially conditioned place preference test. We further show that oxytocin, a neuropeptide that reinforces parental and social bonding, drives anandamide mobilization in the NAc. Pharmacological blockade of oxytocin receptors stops this response, whereas chemogenetic, site-selective activation of oxytocin neurons in the paraventricular nucleus of the hypothalamus stimulates it. Genetic or pharmacological interruption of anandamide degradation offsets the effects of oxytocin receptor blockade on both social place preference and cFos expression in the NAc. The results indicate that anandamide-mediated signaling at CB₁ receptors, driven by oxytocin, controls social reward. Deficits in this signaling mechanism may contribute to social impairment in autism spectrum disorders and might offer an avenue to treat these conditions.Human studies have shown that marijuana heightens the saliency of social interactions (1), enhances interpersonal communication (2, 3), and decreases hostile feelings within small social groups (4). The neural mechanisms underlying these prosocial effects are unclear but are likely to involve activation of CB₁ cannabinoid receptors, the main molecular target of marijuana in the human brain (5). Consistent with this idea, CB₁ receptors are highly expressed in associational cortical regions of the frontal lobe and subcortical structures that underpin human social-emotional functioning (6, 7). Moreover, the receptors and their endogenous lipid-derived ligands, anandamide and 2-arachidonoyl-sn-glycerol (2-AG) (8), have been implicated in the control of social play (9) and social anxiety (10, 11), two crucial aspects of the social experience. Another essential facet of social behavior, the adaptive reinforcement of interactions among members of a group (i.e., the reward of being social), requires the oxytocin-dependent induction of long-term synaptic plasticity at excitatory synapses of the nucleus accumbens (NAc) (12), a key region in the brain reward circuit. Because the endocannabinoid system regulates the reinforcement of various natural stimuli (13) as well as NAc neurotransmission (14), in the present study we tested the hypothesis that this signaling complex might cooperate with oxytocin to control social reward.     

Responses to social and environmental stress are attenuated by strong male bonds in wild macaques

In humans and obligatory social animals, individuals with weak social ties experience negative health and fitness consequences. The social buffering hypothesis conceptualizes one possible mediating mechanism: During stressful situations the presence of close social partners buffers against the adverse effects of increased physiological stress levels. We tested this hypothesis using data on social (rate of aggression received) and environmental (low temperatures) stressors in wild male Barbary macaques (Macaca sylvanus) in Morocco. These males form strong, enduring, and equitable affiliative relationships similar to human friendships. We tested the effect of the strength of a male’s top three social bonds on his fecal glucocorticoid metabolite (fGCM) levels as a function of the stressors’ intensity. The attenuating effect of stronger social bonds on physiological stress increased both with increasing rates of aggression received and with decreasing minimum daily temperature. Ruling out thermoregulatory and immediate effects of social interactions on fGCM levels, our results indicate that male Barbary macaques employ a tend-and-befriend coping strategy in the face of increased environmental as well as social day-to-day stressors. This evidence of a stress-ameliorating effect of social bonding among males under natural conditions and beyond the mother–offspring, kin or pair bond broadens the generality of the social buffering hypothesis.Strong affiliative social relationships exert powerful beneficial effects on an individual’s health and fitness in both humans and nonhuman animals (1–5). One well-studied mediating mechanism, conceptualized in the social buffering hypothesis, is that the presence of a close social partner attenuates the reactivity of the hypothalamic–pituitary–adrenal (HPA) axis (apart from other positive effects on physiological responses) and thus buffers against the potentially adverse effects of physiological stress (4, 6, 7). Evidence for the social buffering hypothesis rests primarily on experimental studies exposing subjects to stressful situations when a close social partner is present or absent (6–8). In that sense, previous studies on the social buffering effect captured an interaction effect of social bonding and a stressor, usually via exposure to a novel environment or, in humans, psychological stress on the stress response (4).The individual functioning as a social buffer against stress is usually a pair-bonded partner [in humans and nonhuman animals (6, 8–11)] or mother [in infant nonhuman animals (11–13)]. The “tend-and-befriend” stress-coping-mechanism (i.e., turning to close affiliates and kin), when under stress, has been linked to the attachment–caregiving system partly regulated by the oxytocinergic system (14–16). Possibly as a direct consequence of this, humans exhibit a strong sex difference in behavioral coping mechanisms to perceived stressful events; women are more likely to seek social support in stressful situations compared with men (ref. 17, but see ref. 18). Stress alleviation via social support has also been shown in nonhuman primates where females with stronger bonds or a tighter social network showed an attenuated response to stressors compared with those with weaker social ties (19, 20). For example, the death of a close female partner (catastrophic stressor), usually kin, in baboons led to increased physiological stress, and the bereaved partner attempted to alleviate this response by strengthening existing bonds (21). After a conflict event in chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) closely bonded bystanders can actively console recipients of aggression, thereby reducing behavioral measures of stress (22–24). Many nonhuman primate females live in closely interwoven matrilineal networks of mutual affiliation and support (25–27) that generate strong fitness advantages in terms of increased reproductive rates and survival (1, 28, 29).Because most males compete for opportunities to fertilize females (30) the focus of studies investigating correlates of male physiological stress have historically been on reproductive competition and hierarchical status (31–33). Nevertheless, recent and increasing evidence has shown that males of some vertebrate species also form strong social bonds that can enhance their fitness (refs. 34–38 and reviewed in ref. 39). However, to date social buffering effects on acute HPA responses in adult male vertebrates have been investigated predominantly in pair-living species (or pair-housed animals) in response to the female pair partner’s presence (reviewed in ref. 6). It remains to be shown whether the human sex difference in behavioral stress-coping mechanisms is exhibited by other mammals as well or whether males, like females, experience social buffering responses under stress when they have strong social ties to other same-sex individuals in their group.Similar to philopatric female baboons and male chimpanzees (38, 40, 41) macaque males of some species, including Barbary macaques (Macaca sylvanus), form strong social relationships with a few male partners (35, 36, 39, 42) that are stable over consecutive years and characterized by equitability in exchanges of affiliation (37). The mechanisms guiding partner selection for the formation of social bonds in male macaques are currently unknown. Parallel dispersal has been observed (43), and in large provisioned groups maternal relatedness partly drives agonistic support (44), but the strength of male social bonds is not decreased in maternally unrelated males in the wild (35). Males vary in the number and strength of social bonds they form (37), which may partly be guided by age (36, 45) and may additionally be affected by personality (46, 47).Barbary macaque males frequently experience noncatastrophic stressful situations in their daily lives that may be social or environmental. Within-group conflicts resulting in aggression represent a social stressor that is positively correlated to glucocorticoid levels (a measure of physiological stress) across many primates (19, 48–51). Within-group aggressive conflicts also vary between individuals (50, 52) and between seasons, with peaks during the mating season (36). An annually recurring environmental stressor in the study population of Barbary macaques is cold stress during the winter months. Winter survival probability was found to be predicted by the number of affiliative relationships an individual formed (53). In baboons temperature stress is associated with increased glucocorticoid levels (54, 55).Here we took advantage of this macaque system of strong male bonding and the occurrence of several stressors in an individual’s daily life to test the social buffering hypothesis in a natural situation and within the male sex. As the buffering hypothesis proposes that social support or bonding is related to well-being only during stressful situations (4), we predicted an interaction effect: As stressor intensity increases (i.e., rate of aggression received increases or minimum temperature declines), the attenuating effect of an individual''s social bond strength on faecal glucocorticoid metabolite (fGCM) levels becomes stronger. We also controlled for an alternative, not mutually exclusive, hypothesis, the “immediate effects hypothesis,” stating that affiliative social behavior directly alleviates physiological stress irrespective of the social relationship the partners feature (20, 56, 57). For this, we tested the proximate effects of rates of grooming given and received by all group members, grooming with the top three male partners, or frequency of male–infant–male triadic interactions on fGCMs.     

Scaling identity connects human mobility and social interactions

Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality.Over the past few years, we have witnessed tremendous progress in uncovering patterns behind human mobility (1–7) and social networks (8–10), owing partly to the increasing availability of large-scale datasets capturing human behavior in a new level of detail, resolution, and scale (11, 12). Building on rich, fundamental literature from the social sciences (13–19), these data offer a huge opportunity for research, fueling concomitant advances in areas of both human mobility and social networks with profound consequences in broad domains. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws. Indeed, previous studies have shown that human travels adhere to spatial constraints (20), characterized by levy flights and continuous time random walk models (1, 2, 4), a scaling law that has proven to be critical in various phenomena driven by human mobility, from spread of viruses (21–23) to migrations (2, 6) and emergency response (24–26). In another related yet distinct area, there has been much empirical evidence about the geographic effect on communication patterns (20), documenting that the probability for two individuals to communicate decays with distance, following power law distributions (20, 27–30). This robust pattern plays an important role in navigating the social network (31), from routing (32, 33) to search of experts (34, 35) to spread of information (27, 36) and innovations (37). Although human movements and social interactions bear high-level similarities in the role spatial distance plays, and are often referred to as two prominent examples of spatial networks (20), they remain as largely separate lines of inquiry, lacking any known connections between their critical exponents. This is particularly perplexing given the fact that they often exploit the same datasets (5, 20, 38–40) and are treated similarly in most modeling frameworks (6, 41).In this paper, we test the hypothesis that previously observed spatial dependency captures a convolution of geographical propensity and a popularity-based heterogeneity among locations, by exploiting three large-scale mobile phone datasets from different countries across two continents (see Datasets for more details). By separating these two factors, we discovered a scaling relationship linking the critical exponents associated with the spatial effect on movement and communication patterns, effectively reducing the number of independent parameters characterizing human behavior. The uncovered scaling theory not only allows us to derive human movements from communication volumes, or vice versa, it also hints for a deeper connection that may exist among all networked systems where space plays a role, from transportations (2, 6, 42) and communications (27, 29, 30) to the internet (32, 33) and human brains (43).     

Drinking alcohol has sex-dependent effects on pair bond formation in prairie voles

Alcohol use and abuse profoundly influences a variety of behaviors, including social interactions. In some cases, it erodes social relationships; in others, it facilitates sociality. Here, we show that voluntary alcohol consumption can inhibit male partner preference (PP) formation (a laboratory proxy for pair bonding) in socially monogamous prairie voles (Microtus ochrogaster). Conversely, female PP is not inhibited, and may be facilitated by alcohol. Behavior and neurochemical analysis suggests that the effects of alcohol on social bonding are mediated by neural mechanisms regulating pair bond formation and not alcohol’s effects on mating, locomotor, or aggressive behaviors. Several neuropeptide systems involved in the regulation of social behavior (especially neuropeptide Y and corticotropin-releasing factor) are modulated by alcohol drinking during cohabitation. These findings provide the first evidence to our knowledge that alcohol has a direct impact on the neural systems involved in social bonding in a sex-specific manner, providing an opportunity to explore the mechanisms by which alcohol affects social relationships.Prairie voles are a valuable animal model of social monogamy. Males and female mates form durable bonds in the wild and in the laboratory (1, 2), and the neural mechanisms of social bonding delineated in this model species have translated with high predictive validity to humans (3, 4). In both species, social reward and drug reward show striking parallels at the behavioral and neurobiological levels (5–9). Prairie voles are now being used to explore the interactions between social relationships and drug abuse (10–19).We previously demonstrated that prairie voles voluntarily self-administer substantial amounts of alcohol (ethanol) and can influence the drinking patterns of a social partner (16–19), similar to social drinking in humans (20). Because alcohol is known to influence social bonds in humans (21–24), we asked here whether alcohol consumption can affect the formation of adult social attachments in prairie voles. Adult male and female prairie voles were paired for 24 h and simultaneously given access to alcohol (10% ethanol by volume in water) and water or only water. They were then tested in the 3-h partner preference (PP) test (PPT), which has proved to be a remarkably sensitive assay for assessing the effects of genetics (25, 26), early social environment (27), and a range of pharmacological agents on social bond formation (28, 29).     

Dopamine-associated cached values are not sufficient as the basis for action selection

Phasic dopamine transmission is posited to act as a critical teaching signal that updates the stored (or “cached”) values assigned to reward-predictive stimuli and actions. It is widely hypothesized that these cached values determine the selection among multiple courses of action, a premise that has provided a foundation for contemporary theories of decision making. In the current work we used fast-scan cyclic voltammetry to probe dopamine-associated cached values from cue-evoked dopamine release in the nucleus accumbens of rats performing cost–benefit decision-making paradigms to evaluate critically the relationship between dopamine-associated cached values and preferences. By manipulating the amount of effort required to obtain rewards of different sizes, we were able to bias rats toward preferring an option yielding a high-value reward in some sessions and toward instead preferring an option yielding a low-value reward in others. Therefore, this approach permitted the investigation of dopamine-associated cached values in a context in which reward magnitude and subjective preference were dissociated. We observed greater cue-evoked mesolimbic dopamine release to options yielding the high-value reward even when rats preferred the option yielding the low-value reward. This result identifies a clear mismatch between the ordinal utility of the available options and the rank ordering of their cached values, thereby providing robust evidence that dopamine-associated cached values cannot be the sole determinant of choices in simple economic decision making.In contemporary theories of economic decision making, values are assigned to reward-predictive states in which animals can take action to obtain rewards, and these state-action values are stored (“cached”) for the purpose of guiding future choices based upon their rank order (1–5). It is believed that these cached values are represented as synaptic weights within corticostriatal circuitry, reflected in the activity of subpopulations of striatal projection neurons (6–9), and are updated by dopamine-dependent synaptic plasticity (10–12). Indeed, a wealth of evidence suggests that the phasic activity of dopamine neurons reports instances in which current reward or expectation of future reward differs from current expectations (13–24). This pattern of activity resembles the prediction-error term from temporal-difference reinforcement-learning algorithms, which is considered the critical teaching signal for updating cached values. A notable feature of models that integrate dopamine transmission into this computational framework is that the cached value of an action is explicitly read out by the phasic dopamine response to the unexpected presentation of a cue that designates the transition into a state in which that action yields reward. Therefore, cue-evoked dopamine signaling provides a neural representation of the cached values of available actions, and if these cached values serve as the basis for action selection, then cue-evoked dopamine responses should be rank ordered in a manner that is consistent with animals’ behavioral preferences.Numerous studies that recorded cue-evoked dopamine signaling have reported correlations with the expected utility (subjective value) of actions (24–36). For example, risk-preferring rats demonstrated greater cue-evoked dopamine release for a risky option than for a certain option with equivalent objective expected value (reward magnitude times probability), whereas risk-averse rats showed greater dopamine release for the certain than for the risky option (30). Likewise, the cached values reported by dopamine neurons in macaque monkeys accounted for individual monkeys’ subjective flavor and risk preferences, with each attribute weighted according to its influence on behavioral preferences (31, 32). These observations, which are consistent across measures of dopamine neuronal activity and dopamine release, reinforce the prevailing notion that the dopamine-associated cached values could be the primary determinant of decision making (2–5, 17, 28–32) because the cue-evoked dopamine responses were rank ordered according to the animals’ subjective preferences. However, there have been some reports that other economic attributes, such as effortful response costs (35–38) or the overt aversiveness of an outcome (39), are represented inconsistently by cue-evoked dopamine responses. For example, Gan et al. (35) showed that independent manipulations of two different dimensions (reward magnitude and effort) that had equivalent effects on behavior did not have equivalent effects on dopamine release. Paralleling these findings, a recent report reached a similar conclusion that dopamine transmission preferentially encodes an appetitive dimension but is relatively insensitive to aversiveness (39).Because these cue-evoked dopamine signals represent cached values that are purported to determine action selection, their differential encoding of economic dimensions has potentially problematic implications in the context of decision making. Namely, by extrapolating from these studies (35–39), one might infer that when a decision involves the tradeoff between these economic dimensions, the rank order of the dopamine-associated cached values for each of the available options would not consistently reflect the ordinal utility of these options and therefore these cached values could not, on their own, be the basis of choices. However, this counterintuitive prediction was not tested explicitly by any of these previous studies; thus it remains a provocative notion that merits direct examination, because it is contrary to the prevailing hypothesis described above which is fundamental to contemporary theories of decision making. Therefore, we investigated interactions between dimensions that previously have been shown during independent manipulations to be weakly or strongly incorporated into these cached values. Specifically, we increased the amount of effort required to obtain a large reward so that animals instead preferred a low-effort option yielding a smaller reward, and we used fast-scan cyclic voltammetry to record cue-evoked mesolimbic dopamine release as a neurochemical proxy for each option’s cached value. These conditions permitted us to test whether the cached values reported via cue-evoked dopamine indeed align with animals’ subjective preferences across these mixed cost–benefit attributes.     

Distinct dopamine neurons mediate reward signals for short- and long-term memories

Drosophila melanogaster can acquire a stable appetitive olfactory memory when the presentation of a sugar reward and an odor are paired. However, the neuronal mechanisms by which a single training induces long-term memory are poorly understood. Here we show that two distinct subsets of dopamine neurons in the fly brain signal reward for short-term (STM) and long-term memories (LTM). One subset induces memory that decays within several hours, whereas the other induces memory that gradually develops after training. They convey reward signals to spatially segregated synaptic domains of the mushroom body (MB), a potential site for convergence. Furthermore, we identified a single type of dopamine neuron that conveys the reward signal to restricted subdomains of the mushroom body lobes and induces long-term memory. Constant appetitive memory retention after a single training session thus comprises two memory components triggered by distinct dopamine neurons.Memory of a momentous event persists for a long time. Whereas some forms of long-term memory (LTM) require repetitive training (1–3), a highly relevant stimulus such as food or poison is sufficient to induce LTM in a single training session (4–7). Recent studies have revealed aspects of the molecular and cellular mechanisms of LTM formation induced by repetitive training (8–11), but how a single training induces a stable LTM is poorly understood (12).Appetitive olfactory learning in fruit flies is suited to address the question, as a presentation of a sugar reward paired with odor induces robust short-term memory (STM) and LTM (6, 7). Odor is represented by a sparse ensemble of the 2,000 intrinsic neurons, the Kenyon cells (13). A current working model suggests that concomitant reward signals from sugar ingestion cause associative plasticity in Kenyon cells that might underlie memory formation (14–20). A single activation session of a specific cluster of dopamine neurons (PAM neurons) by sugar ingestion can induce appetitive memory that is stable over 24 h (19), underscoring the importance of sugar reward to the fly.The mushroom body (MB) is composed of the three different cell types, α/β, α′/β′, and γ, which have distinct roles in different phases of appetitive memories (11, 21–25). Similar to midbrain dopamine neurons in mammals (26, 27), the structure and function of PAM cluster neurons are heterogeneous, and distinct dopamine neurons intersect unique segments of the MB lobes (19, 28–34). Further circuit dissection is thus crucial to identify candidate synapses that undergo associative modulation.By activating distinct subsets of PAM neurons for reward signaling, we found that short- and long-term memories are independently formed by two complementary subsets of PAM cluster dopamine neurons. Conditioning flies with nutritious and nonnutritious sugars revealed that the two subsets could represent different reinforcing properties: sweet taste and nutritional value of sugar. Constant appetitive memory retention after a single training session thus comprises two memory components triggered by distinct reward signals.     

Evolution in leaps: The punctuated accumulation and loss of cultural innovations

Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size.The breadth and diversity of cultural traits and their rates of accumulation have received a great deal of scholarly attention. Scientific knowledge in many fields appears to accumulate exponentially (1, 2). However, although the number of tool types in the archaeological record also seems to fit this pattern of exponential increase broadly (3), the number of tools and other cultural traits does not increase steadily and monotonically over time. Depending on the timescale studied, change in tool repertoire may appear punctuated and stepwise. Long, seemingly static, periods are interspersed between “cultural explosions,” periods of sudden cultural accumulation (3–13). Further, in some populations, there is evidence that whole suites of cultural traits, such as the ability to make tools, clothing, and fire (14–16), may be lost, defying the general trend of cultural accumulation over time (4, 7, 8).Reasons for the sudden changes in hominid material culture in the archaeological record continue to be debated; they could be related to demographic factors (17), rapid cognitive change (18–21), relatively sudden changes in hand morphology (22, 23), or dramatic climatic shifts (10, 24–28). Further, intermediate-scale environmental change or migration to a new environment also could affect the accumulation and loss of traits that are primarily useful in specific environments (29–33). In addition, the relationship between the number of cultural traits in a population and population size has been debated (4, 14, 29, 34–41); this relationship also might depend on the social learning strategies of the population (42, 43). Further, there could be a feedback process between the number of tools in a population and the population size: A larger population might be able to invent and retain more tools, but certain innovations also might support a larger population (44, 45). Finally, the distribution of traits in the population (as a result, for example, of social stratification) might affect both stochastic and environmentally mediated cultural losses.Several models of the dynamics of cultural evolution explicitly incorporate appearance, transmission, and in some cases disappearance of cultural traits (14, 35, 40, 45–53). Sudden dramatic changes in cognition, morphology, or climate are not invoked in these models as a precursor to cultural change; instead, cultural change derives from endogenous properties of the models.Most models of cultural evolution focus on the dynamics of the transmission of cultural traits (40, 50, 51), often omitting the details of the creative processes underlying the origin of these traits (e.g., refs. 14, 35, and 54). The source of cultural traits is represented as a random process occurring at a constant rate, analogous to a genetic mutation rate (40, 46, 48, 50, 51, 55). This representation has proven useful but differs from realistic human innovation (56). For example, a particular genetic mutation occurs independently of previous mutations, whereas a cultural trait’s likelihood of invention could depend on the configuration or frequency of existing traits. For example, the invention of a snaring method enabling new kinds of game hunting may lead to the invention of specialized tools for processing this novel food source. This dependence is one sense in which culture is fundamentally cumulative. A second intriguing difference is the cost of failed attempts at adaptation; although deleterious mutations are costly to the organism, the invention of a useless tool typically would not have long-lasting effects: it simply would be discarded and forgotten. A few models do not assume a constant rate of creative invention: as the existing repertoire becomes larger, they allow an increase (47, 57) or decrease (e.g., ref. 54) in the invention rate, or more subtle dependencies among particular traits (49, 52); other models allow cultural traits to influence the dynamics of cultural transmission and homophily (58–63).Large-scale cultural loss has been observed in human populations; however, most existing models lack a mechanism to account for this process. Many represent cultural loss as a Poisson process (47, 49, 51, 52, 57), but, as with cultural accumulation, this assumption of a constant rate may be an over-simplification. In reality, factors such as population size (taken into account in some of these models) and environmental change (7) likely affect the rate and nature of cultural loss. Finally, existing models also implicitly assume a uniform distribution of knowledge in the population. This assumption is unrealistic in human populations, where some knowledge may be concentrated in specific subgroups, such as medicine-women and -men who know the uses and risks of medicinal plants. We suggest that a concept of effective cultural population size as a cultural analog to effective population size in genetics could be highly useful in this context. Notably, Shennan (35) and Premo (64) have suggested the use of an effective population size in the context of cultural evolution for different reasons, stemming from the details of the transmission process or from the geographical substructure of the population.Existing models of cultural evolution cannot reproduce many features of archaeological and anthropological observations of cultural accumulation in hominids. Few models show an exponential increase in the number of cultural traits (47, 49, 57) or large-scale cultural losses (14, 45, 46), and we are unaware of any that reproduce a pattern of cultural accumulation with punctuated bursts of innovation separated by periods of relative stasis (although ref. 45 suggests the possibility of bistability: a sudden shift between two levels of cultural diversity).We suggest that the assumption that all cultural traits originate via a single process cannot generate an accurate representation of human cultural accumulation. Indeed, researchers in fields such as psychology and cognitive science often divide creativity into multiple types or processes, such as everyday and genius-level creativity (65–67, see also ref. 57). Other categorizations reflect properties of the underlying cognitive processes (68, 69). Both approaches suggest that some creative events are rare and somewhat unpredictable and others are more everyday occurrences that depend on the current environment and preexisting knowledge in a population.     

From the Cover: Intergenerational transmission of emotional trauma through amygdala-dependent mother-to-infant transfer of specific fear

Emotional trauma is transmitted across generations. For example, children witnessing their parent expressing fear to specific sounds or images begin to express fear to those cues. Within normal range, this is adaptive, although pathological fear, such as occurs in posttraumatic stress disorder or specific phobias, is also socially transmitted to children and is thus of clinical concern. Here, using a rodent model, we report a mother-to-infant transfer of fear to a novel peppermint odor, which is dependent on the mother expressing fear to that smell in pups’ presence. Examination of pups’ neural activity using c-Fos early gene expression and ¹⁴C 2-deoxyglucose autoradiography during mother-to-infant fear transmission revealed lateral and basal amygdala nuclei activity, with a causal role highlighted by pharmacological inactivation of pups’ amygdala preventing the fear transmission. Maternal presence was not needed for fear transmission, because an elevation of pups’ corticosterone induced by the odor of the frightened mother along with a novel peppermint odor was sufficient to produce pups’ subsequent aversion to that odor. Disruption of axonal tracts from the Grueneberg ganglion, a structure implicated in alarm chemosignaling, or blockade of pups’ alarm odor-induced corticosterone increase prevented transfer of fear. These memories are acquired at younger ages compared with amygdala-dependent odor-shock conditioning and are more enduring following minimal conditioning. Our results provide clues to understanding transmission of specific fears across generations and its dependence upon maternal induction of pups’ stress response paired with the cue to induce amygdala-dependent learning plasticity. Results are discussed within the context of caregiver emotional responses and adaptive vs. pathological fears social transmission.Children, including infants, use their parents’ emotions to guide their behavior and learn about safety and danger (1–4). The infant’s ability to regulate behavior in novel situations using the caregiver’s emotional expression is known as social referencing and occurs in humans and nonhuman primates (1). Although parental physical presence itself or particular cues indicating parental presence, such as voice, touch, or smell typically signal safety for the child, infants are especially responsive to the caregiver’s communication during threats (3–5). This social learning is critical for enhancing survival through an adaptation to the environment but also provides transmission of pathological fears, such as occurs in posttraumatic stress disorder (PTSD) or in specific phobias (3–7).Despite existing evidence that children are sensitive to parental fear and anxiety, the neurobiological mechanisms for the transmission of parental specific fear to the offspring have remained elusive (2–7). Animal studies investigating the impact of parental stress on the offspring focused on the history of parental trauma, quality of maternal care, and resultant overall behavioral alterations in the offspring (7, 8). However, to develop efficient survival strategies, progenies must learn about specific environmental threats triggering parental fear (9).Most of what we know about fear learning comes from studies using fear conditioning (FC) (10). In FC, a neutral sensory cue [conditioned stimulus (CS)] is paired with a noxious event [unconditioned stimulus (US)]. Animal studies indicate that the amygdala’s lateral and basal nuclei (LBA) play an important role in FC (10). However, FC in infant rats is naturally attenuated until postnatal day (PND) 10 due to low levels of the stress hormone corticosterone (CORT) during the stress hyporesponsive period (11–15). This fear suppression continues in older pups (until PND 16) in the mother’s presence due to social buffering (attenuation) of the shock-induced CORT increase (15).To study the intergenerational transmission of fear to specific triggers, we developed a mother-to-infant social fear learning paradigm. In social fear learning, an organism learns fear through an exposure to a conspecific expressing fear to a discrete CS. Social fear learning may thus serve as a model explaining how defense responses to specific triggers are transmitted between individuals. Social fear learning has been demonstrated in primates, including humans and in rodents, and involves the amygdala (16–19).     

The spontaneous emergence of conventions: An experimental study of cultural evolution

How do shared conventions emerge in complex decentralized social systems? This question engages fields as diverse as linguistics, sociology, and cognitive science. Previous empirical attempts to solve this puzzle all presuppose that formal or informal institutions, such as incentives for global agreement, coordinated leadership, or aggregated information about the population, are needed to facilitate a solution. Evolutionary theories of social conventions, by contrast, hypothesize that such institutions are not necessary in order for social conventions to form. However, empirical tests of this hypothesis have been hindered by the difficulties of evaluating the real-time creation of new collective behaviors in large decentralized populations. Here, we present experimental results—replicated at several scales—that demonstrate the spontaneous creation of universally adopted social conventions and show how simple changes in a population’s network structure can direct the dynamics of norm formation, driving human populations with no ambition for large scale coordination to rapidly evolve shared social conventions.Social conventions are the foundation for social and economic life (1–7), However, it remains a central question in the social, behavioral, and cognitive sciences to understand how these patterns of collective behavior can emerge from seemingly arbitrary initial conditions (2–4, 8, 9). Large populations frequently manage to coordinate on shared conventions despite a continuously evolving stream of alternatives to choose from and no a priori differences in the expected value of the options (1, 3, 4, 10). For instance, populations are able to produce linguistic conventions on accepted names for children and pets (11), on common names for colors (12), and on popular terms for novel cultural artifacts, such as referring to junk email as “SPAM” (13, 14). Similarly, economic conventions, such as bartering systems (2), beliefs about fairness (3), and consensus regarding the exchangeability of goods and services (15), emerge with clear and widespread agreement within economic communities yet vary broadly across them (3, 16).Prominent theories of social conventions suggest that institutional mechanisms—such as centralized authority (14), incentives for collective agreement (15), social leadership (16), or aggregated information (17)—can explain global coordination. However, these theories do not explain whether, or how, it is possible for conventions to emerge when social institutions are not already in place to guide the process. A compelling alternative approach comes from theories of social evolution (2, 18–20). Social evolutionary theories maintain that networks of locally interacting individuals can spontaneously self-organize to produce global coordination (21, 22). Although there is widespread interest in this approach to social norms (6, 7, 14, 18, 23–26), the complexity of the social process has prevented systematic empirical insight into the thesis that these local dynamics are sufficient to explain universally adopted conventions (27, 28).Several difficulties have limited prior empirical research in this area. The most notable of these limitations is scale. Although compelling experiments have successfully shown the creation of new social conventions in dyadic and small group interactions (29–31), the results in small group settings can be qualitatively different from the dynamics in larger groups (Model), indicating that small group experiments are insufficient for demonstrating whether or how new conventions endogenously form in larger populations (32, 33). Important progress on this issue has been made using network-based laboratory experiments on larger groups (15, 24). However, this research has been restricted to studying coordination among players presented with two or three options with known payoffs. Natural convention formation, by contrast, is significantly complicated by the capacity of individuals to continuously innovate, which endogenously expands the “ecology” of alternatives under evaluation (23, 29, 31). Moreover, prior experimental studies have typically assumed the existence of either an explicit reward for universal coordination (15) or a mechanism that aggregates and reports the collective state of the population (17, 24), which has made it impossible to evaluate the hypothesis that global coordination is the result of purely local incentives.More recently, data science approaches to studying norms have addressed many of these issues by analyzing behavior change in large online networks (34). However, these observational studies are limited by familiar problems of identification that arise from the inability to eliminate the confounding influences of institutional mechanisms. As a result, previous empirical research has been unable to identify the collective dynamics through which social conventions can spontaneously emerge (8, 34–36).We addressed these issues by adopting a web-based experimental approach. We studied the effects of social network structure on the spontaneous evolution of social conventions in populations without any resources to facilitate global coordination (9, 37). Participants in our study were rewarded for coordinating locally, however they had neither incentives nor information for achieving large scale agreement. Further, to eliminate any preexisting bias in the evolutionary process, we studied the emergence of arbitrary linguistic conventions, in which none of the options had any a priori value or advantage over the others (3, 23). In particular, we considered the prototypical problem of whether purely local interactions can trigger the emergence of a universal naming convention (38, 39).     

Childhood bullying involvement predicts low-grade systemic inflammation into adulthood

Bullying is a common childhood experience that involves repeated mistreatment to improve or maintain one’s status. Victims display long-term social, psychological, and health consequences, whereas bullies display minimal ill effects. The aim of this study is to test how this adverse social experience is biologically embedded to affect short- or long-term levels of C-reactive protein (CRP), a marker of low-grade systemic inflammation. The prospective population-based Great Smoky Mountains Study (n = 1,420), with up to nine waves of data per subject, was used, covering childhood/adolescence (ages 9–16) and young adulthood (ages 19 and 21). Structured interviews were used to assess bullying involvement and relevant covariates at all childhood/adolescent observations. Blood spots were collected at each observation and assayed for CRP levels. During childhood and adolescence, the number of waves at which the child was bullied predicted increasing levels of CRP. Although CRP levels rose for all participants from childhood into adulthood, being bullied predicted greater increases in CRP levels, whereas bullying others predicted lower increases in CRP compared with those uninvolved in bullying. This pattern was robust, controlling for body mass index, substance use, physical and mental health status, and exposures to other childhood psychosocial adversities. A child’s role in bullying may serve as either a risk or a protective factor for adult low-grade inflammation, independent of other factors. Inflammation is a physiological response that mediates the effects of both social adversity and dominance on decreases in health.The social and psychological effects of bullying involvement are independent of other childhood experiences, pleiotropic, and long lasting, with the worst effects for those who are both victims and bullies (e.g., refs. 1–4). To date, the primary focus of bullying research has been on such psychosocial outcomes. Bullied children, however, also have adverse physical health functioning (1, 5–7), including a broad range of somatic issues, such as sleep problems, abdominal pain, appetite suppression, headaches, and frequency of illnesses. In contrast, there is evidence to suggest that those who perpetrate only, pure bullies, may be healthier than their peers, emotionally and physically (6, 8). Little is known about how this social adversity becomes biologically embedded to influence health status.One potential mechanism is chronic systemic low-grade inflammation (9). Inflammation is activated similarly by a diverse range of health risk behaviors (poor diet, lack of exercise, and sleep disturbance) and environmental challenges [low socioeconomic status (SES), psychosocial stress] (10–14). Elevated inflammation markers are part of the phenomenology of common psychological disorders (particularly depression) across the lifespan (for reviews, refs. 15, 16). One marker of inflammation, C-reactive protein (CRP), has been the focus of extensive epidemiologic investigation because of the association of elevated plasma CRP levels (>3 mg/L) with cardiovascular risk (17, 18) and aspects of metabolic syndrome (19–21). Subclinical levels of inflammation may be a nonspecific marker for a broad range of organismic challenges, but they have not been studied as a mechanism for the social adversity of bullying involvement on health.The aim of this study was to use a prospective, longitudinal study that has followed a sample of 1,420 children up to nine times to test whether involvement in childhood bullying affects low-grade inflammation as measured by CRP levels short term within childhood/adolescence (ages 9–16) and long term into adulthood (ages 19 and 21). Chronic victims and bully/victims display the worst health and psychosocial outcomes (1, 2, 4). It is hypothesized that both these groups will have more systemic inflammation because of the social strain of victimization. Almost no attention has been paid to the biological consequences to bullying itself in the absence of being a victim. Children may use bullying techniques in efforts to elevate their social status (22). In adults, such elevated social status, measured by income or education level, is associated with lower levels of inflammatory markers (23–25). The role of elevated social status inflammatory markers has not yet been tested, but we expected that pure bullies would display lower levels of CRP than those uninvolved in bullying.     

Unconscious discrimination of social cues from eye whites in infants

Human eyes serve two key functions in face-to-face social interactions: they provide cues about a person’s emotional state and attentional focus (gaze direction). Both functions critically rely on the morphologically unique human sclera and have been shown to operate even in the absence of conscious awareness in adults. However, it is not known whether the ability to respond to social cues from scleral information without conscious awareness exists early in human ontogeny and can therefore be considered a foundational feature of human social functioning. In the current study, we used event-related brain potentials (ERPs) to show that 7-mo-old infants discriminate between fearful and nonfearful eyes (experiment 1) and between direct and averted gaze (experiment 2), even when presented below the perceptual threshold. These effects were specific to the human sclera and not seen in response to polarity-inverted eyes. Our results suggest that early in ontogeny the human brain detects social cues from scleral information even in the absence of conscious awareness. The current findings support the view that the human eye with its prominent sclera serves critical communicative functions during human social interactions.Eyes play a key role in human social encounters, as they are critically involved in perceiving others as having minds (1), in attributing mental states to others (2), and in social coordination during face-to-face interactions (3). The presence of eyes has also been shown to increase cooperative behavior in laboratory and in real-world contexts (2, 4–7). The human eye is unique in that it is characterized by a prominent white sclera several times larger than that of other primates (8, 9), which allows for the efficient communication and detection of social information. It is thought that the human sclera is adapted to facilitate interpersonal communication and cooperative interactions among humans (10). When humans observe others’ faces, eyes are typically the first features that are scanned for information (11), and, compared with other primates, humans show a stronger focus on the eye region than on other parts of the face when scanning faces (12, 13). Conversely, failure to devote special attention to the eye region during face perception has been linked to severe social deficits that can, for instance, be observed in autism spectrum disorder (14).One reason why human eyes have such prime importance is that emotion perception, as a vital part of any social interaction, heavily relies on information from the eye region (14). This is especially important for the detection of fear in others, as one of the most basic forms of identifying threatening situations. Fear detection has been observed in response to eyes alone (15, 16). This mechanism operates exceptionally fast (17) and occurs irrespective of conscious awareness (15). On a neural level, the processing of fearful eyes critically depends on the amygdala. Depending on the context (18, 19), fearful eyes can elicit an enhanced activation of the amygdala (20), even if not perceived consciously (15). Patients with bilateral amygdala lesions show deficits in recognizing fear, which disappear when they are instructed to focus on the eye region (21). Furthermore, there is recent evidence to show that the amygdala is involved in reflexively directing attention to the eyes and in predicting gaze to fearful eyes (22, 23).Another important social cue conveyed by the eye is the direction of gaze. Eye gaze can inform us about another person’s attentional focus, thereby providing clues about future behavior (24). Critically, eye gaze and emotion perception have been shown to powerfully interact. For example, fearful eyes elicit stronger behavioral and neural responses when averted from than when directed at an observer (25, 26). This presumably relates to the fact that averted fearful eyes inform an observer about a potential danger in the environment (clear threat), whereas directed fearful eyes signal fear of the observer (ambiguous threat). At the brain level, this also relies on the amygdala, as reflected in a differential activation for direct compared with averted gaze (25, 27). Furthermore, behavioral studies suggest that similar to emotion processing, eye gaze discrimination operates even in the absence of conscious awareness (28).Attending and responding to eyes is thought to play a vital role in the early development of social skills (29). From birth, infants respond sensitively to human eyes: Newborns prefer direct gaze faces over averted gaze faces (30) and even show a rudimentary form of gaze following (31). Newborns’ sensitivity to eyes has been shown to be specific to the human sclera, as behavioral preferences disappear when the contrast polarity of the eye is reversed (32). Nevertheless, the ability to attend to the eyes and follow gaze improves considerably over the course of the first year of life and is viewed as an important marker of healthy social development (33, 34). Indeed, orienting to the eyes is present early in infancy but declines between 2 and 6 mo in infants later diagnosed with autism (29). With respect to responding to emotional information, newborns also show a basic sensitivity to (familiar) emotional facial expressions for which they may also use eye cues (30, 35, 36). However, it is not until the age of 7 mo that they show a robust attentional bias to fear, as reflected in their neural and behavioral responses (37–41). The developmental emergence of this fear bias has been linked to the maturation of frontolimbic circuits (42–45) and occurs at a point in development when infants begin to first experience fear themselves (46, 47). Despite our growing understanding of the developmental origins of emotion and gaze processing in humans, some fundamental questions concerning the exact nature of this ability remain unanswered.In the present study we therefore addressed two key questions, which are essential to understanding the mechanisms that underpin sensitive responding to human eyes in infants. First, we asked whether infants’ detection of social cues such as fear and gaze from eyes occurs in the absence of conscious awareness. Second, we examined whether the detection of these social cues can be seen in response to scleral information alone. To address these questions, we conducted two experiments, based on an established paradigm from adult literature (15), which investigated whether the infant brain can discriminate between fearful and nonfearful eyes (experiment 1) and between direct and averted fearful eyes (experiment 2), even if the stimuli are not perceived consciously. We hypothesized that if the eyes indeed serve a critical function in human social communication, then the unconscious detection of social cues from scleral information should be evident early in ontogeny. Specifically, according to our hypothesis, using event-related brain potentials (ERPs), we expected infants to show evidence for neural discrimination between fearful and nonfearful human eyes (experiment 1) and direct and averted gaze (experiment 2).     

Automated measurement of mouse social behaviors using depth sensing,video tracking,and machine learning

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body “pose” of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.Social behaviors are critical for animals to survive and reproduce. Although many social behaviors are innate, they must also be dynamic and flexible to allow adaptation to a rapidly changing environment. The study of social behaviors in model organisms requires accurate detection and quantification of such behaviors (1–3). Although automated systems for behavioral scoring in rodents are available (4–8), they are generally limited to single-animal assays, and their capabilities are restricted either to simple tracking or to specific behaviors that are measured using a dedicated apparatus (6–11) (e.g., elevated plus maze, light-dark box, etc.). By contrast, rodent social behaviors are typically scored manually. This is slow, highly labor-intensive, and subjective, resulting in analysis bottlenecks as well as inconsistencies between different human observers. These issues limit progress toward understanding the function of neural circuits and genes controlling social behaviors and their dysfunction in disorders such as autism (1, 12). In principle, these obstacles could be overcome through the development of automated systems for detecting and measuring social behaviors.Automating tracking and behavioral measurements during social interactions pose a number of challenges not encountered in single-animal assays, however, especially in the home cage environment (2). During many social behaviors, such as aggression or mating, two animals are in close proximity and often cross or touch each other, resulting in partial occlusion. This makes tracking body positions, distinguishing each mouse, and detecting behaviors particularly difficult. This is compounded by the fact that such social interactions are typically measured in the animals’ home cage, where bedding, food pellets, and other moveable items can make tracking difficult. Nevertheless a home-cage environment is important for studying social behaviors, because it avoids the stress imposed by an unfamiliar testing environment.Recently several techniques have been developed to track social behaviors in animals with rigid exoskeletons, such as the fruit fly Drosophila, which have relatively few degrees of freedom in their movements (13–23). These techniques have had a transformative impact on the study of social behaviors in that species (2). Accordingly, the development of similar methods for mammalian animal models, such as the mouse, could have a similar impact as well. However, endoskeletal animals exhibit diverse and flexible postures, and their actions during any one social behavior, such as aggression, are much less stereotyped than in flies. This presents a dual challenge to automated behavior classification: first, to accurately extract a representation of an animal’s posture from observed data, and second, to map that representation to the correct behavior (24–27). Current machine vision algorithms that track social interactions in mice mainly use the relative positions of two animals (25, 28–30); this approach generally cannot discriminate social interactions that involve close proximity and vigorous physical activity, or identify specific behaviors such as aggression and mounting. In addition, existing algorithms that measure social interactions use a set of hardcoded, “hand-crafted” (i.e., predefined) parameters that make them difficult to adapt to new experimental setups and conditions (25, 31).In this study, we combined 3D tracking and machine learning in an integrated system that can automatically detect, classify, and quantify distinct social behaviors, including those involving close and dynamic contacts between two mice in their home cage. To do this, we designed a hardware setup that synchronizes acquisition of video and depth camera recordings and developed software that registers data between the cameras and depth sensor to produce an accurate representation and segmentation of individual animals. We then developed a computer vision tool that extracts a representation of the location and body pose (orientation, posture, etc.) of individual animals and used this representation to train a supervised machine learning algorithm to detect specific social behaviors. We found that our learning algorithm was able to accurately classify several social behaviors between two animals with distinct coat colors, including aggression, mating, and close social investigation. We then evaluated the robustness of our social behavior classifier in different experimental conditions and examined how genetic backgrounds influence social behavior. The highly flexible, multistep approach presented here allows different users to train new customized behavior classifiers according to their needs and to analyze a variety of behaviors in diverse experimental setups.     

Oxytocin modulates fMRI responses to facial expression in macaques

Increasing evidence has shown that oxytocin (OT), a mammalian hormone, modifies the way social stimuli are perceived and the way they affect behavior. Thus, OT may serve as a treatment for psychiatric disorders, many of which are characterized by dysfunctional social behavior. To explore the neural mechanisms mediating the effects of OT in macaque monkeys, we investigated whether OT would modulate functional magnetic resonance imaging (fMRI) responses in face-responsive regions (faces vs. blank screen) evoked by the perception of various facial expressions (neutral, fearful, aggressive, and appeasing). In the placebo condition, we found significantly increased activation for emotional (mainly fearful and appeasing) faces compared with neutral faces across the face-responsive regions. OT selectively, and differentially, altered fMRI responses to emotional expressions, significantly reducing responses to both fearful and aggressive faces in face-responsive regions while leaving responses to appeasing as well as neutral faces unchanged. We also found that OT administration selectively reduced functional coupling between the amygdala and areas in the occipital and inferior temporal cortex during the viewing of fearful and aggressive faces, but not during the viewing of neutral or appeasing faces. Taken together, our results indicate homologies between monkeys and humans in the neural circuits mediating the effects of OT. Thus, the monkey may be an ideal animal model to explore the development of OT-based pharmacological strategies for treating patients with dysfunctional social behavior.In the last decade, oxytocin (OT), a mammalian hormone, has become one of the most studied peptides of the neuroendocrine system. In humans, accumulating evidence has demonstrated that OT affects a wide range of social behavior and cognition, including perception, recognition and memory of social stimuli (1–5), socially reinforced learning (6), and more complex sociocognitive behaviors [e.g., trust (7, 8), cooperation (9), generosity (10), and empathy (6, but see ref. 11)]. Therefore, it has been proposed that OT may serve as a treatment for various disorders with dysfunctional social behavior, such as autism spectrum disorders, antisocial personality disorder, and schizophrenia (for review, see ref. 12). A recent study found that OT enhances brain activity for socially meaningful stimuli but attenuates activity for nonsocially meaningful stimuli in children with autism spectrum disorders (13). Although these studies suggest very promising prospects of OT for clinical use, the neural mechanisms underlying OT’s modulatory effects remain elusive. To understand these mechanisms, it is important to investigate the effect of OT on brain activity, especially in regions involved in social behavior and cognition.Functional magnetic resonance imaging (fMRI) has been the major approach to investigating altered brain activation patterns in response to OT in humans. OT may affect the perception of social stimuli, and thus mediate subsequent social information processing (e.g., learning and memory, etc.) (14). Many fMRI studies have examined the effects of OT on brain activity during the perception of social stimuli to probe the brain regions that underlie OT’s modulatory effects. Emotional stimuli, which are crucial for social communication and interaction, have been mainly used. For example, Kirsch et al. showed that OT reduces activation in response to fear-inducing stimuli in the amygdala, a key brain region involved in emotional regulation (15). Subsequently, a series of studies examined the effects of OT on responses to facial expressions (3, 16), to conditioned facial expressions (17), and to threatening scenes (18). These studies showed that activity evoked by emotional stimuli, especially negative stimuli (e.g., fearful faces, but see refs. 3 and 16 for happy faces), is systematically altered within an interconnected network of brain regions after OT administration.Because of the limitation of experimental approaches with human subjects, animal models are essential not only for investigating the neural mechanisms underlying the effects of OT but also for exploring OT-based therapeutic strategies for individuals with dysfunctional social behavior. Given the similarities between monkeys and humans in the neural circuitry underlying social cognition (19), the rhesus macaque could be an ideal animal model to examine the effects of OT. To date, only a few studies have investigated the behavioral consequences of OT administration in monkeys (20–25). Consistent with the human literature, these studies have found that intranasal administration of OT affects social behavior and cognition in monkeys, including vicarious as well as self-reinforcement (20), social vigilance (22), socially reinforced learning (26), and attention to facial features and expressions (21, 24). However, how OT exerts its effects on brain activity in monkeys remains unclear. To explore the neural mechanisms mediating the effects of OT in macaque monkeys, in the present study, we investigated whether OT would modulate fMRI responses evoked by the perception of facial expressions, an effect mainly studied in humans thus far.We scanned monkeys while they viewed images of monkey faces with four different expressions: neutral, fearful, aggressive, and appeasing. Scanning was conducting under two different conditions: placebo control (saline) and intranasal OT. We predicted that in the placebo condition, emotional faces (especially fearful) would evoke enhanced activation compared with neutral faces, that is, they would show a valence effect; that, as in humans, OT administration would reduce this valence effect in monkeys; and that OT administration would alter functional coupling among those brain regions showing a valence effect.     

Focus on the success of others leads to selfish behavior

It has often been argued that the spectacular cognitive capacities of humans are the result of selection for the ability to gather, process, and use information about other people. Recent studies show that humans strongly and consistently differ in what type of social information they are interested in. Although some individuals mainly attend to what the majority is doing (frequency-based learning), others focus on the success that their peers achieve with their behavior (success-based learning). Here, we show that such differences in social learning have important consequences for the outcome of social interactions. We report on a decision-making experiment in which individuals were first classified as frequency- and success-based learners and subsequently grouped according to their learning strategy. When confronted with a social dilemma situation, groups of frequency-based learners cooperated considerably more than groups of success-based learners. A detailed analysis of the decision-making process reveals that these differences in cooperation are a direct result of the differences in information use. Our results show that individual differences in social learning strategies are crucial for understanding social behavior.Acquiring information about others is a prominent feature of the human behavioral repertoire (1–3). Observing the behavior of others can allow individuals to improve their own knowledge and skills, but it can also be instrumental in anticipating how others will behave in future social interactions. Clues that help to predict how others will behave can allow for better coordination, or for being able to outsmart others for personal gain (4, 5). Indeed, the ability to keep a mental tab about the past actions of others has been put forward as one of the main mechanisms that allowed for the evolution of cooperation in humans (6, 7).This focus on social information comes with a spectacular capacity to imitate. Imitation and other forms of social learning govern the spread of information between individuals and are therefore at the basis of cultural change. Indeed, it has been argued that these mechanisms of transmission underlie a process of cultural evolution, which is in many ways analogous to genetic evolution (8–10). Social learning has allowed humans to rapidly adapt to all kinds of environmental circumstances and is ultimately responsible for the wide variety of languages, habits, forms of organization, and social norms that are found across cultures (11–14). Because of this, social learning and its group-level consequences have been the object of considerable scientific scrutiny. Laboratory studies and theoretical models have gone hand-in-hand in respectively identifying the social learning strategies that people use (15–18) and determining how these different strategies are shaped by selection (19–21) and affect the outcome of cultural evolution (22–26). The framework of cultural evolution has been successfully applied for a range of purposes, such as understanding the spread and the loss of technologies in human societies (27, 28) and inferring the ancestry of cultural traits such as language and political organization (29–31).Although there has been extensive focus on identifying the rules that humans use to learn from each other, the possibility that people may differ in the way they learn from others has long been ignored. Only recently, several studies (32–36) have suggested that there is substantial individual variation in how much social information people use, and in the type of information they are interested in. Some focus on information about the success of others (paying attention to both their decisions and the associated payoffs), whereas others are only interested in the frequencies with which behaviors occur in their social group (disregarding information about the payoffs others obtained). Moreover, individuals tend to use the same social learning strategy across different (social and nonsocial) contexts (35). However, it is unclear how the focus on different types of social information might affect the outcome of social interactions.In this study, we examine the consequences of individual variation in human social learning strategies on the outcome of cooperative interactions. For this, we conducted a decision-making experiment that consisted of two parts that took place 1 month apart. In part 1, subjects were divided in groups and confronted with a number of different interaction settings. In each interaction round, they were allowed to view a limited amount of information about their peers’ previous behavior and earnings. In part 2, we assorted the same subjects in groups based on the social learning strategies they had used in part 1, creating groups of success-based learners and frequency-based learners. These groups were confronted with a cooperation setting, in which each subject had to decide between a selfish option and an option that benefitted the group. We analyze the outcome of the interactions in these groups and investigate whether, and to what extent, differences in cooperation can be traced back to differences in social learning style.     

Dopamine prediction error responses integrate subjective value from different reward dimensions

Prediction error signals enable us to learn through experience. These experiences include economic choices between different rewards that vary along multiple dimensions. Therefore, an ideal way to reinforce economic choice is to encode a prediction error that reflects the subjective value integrated across these reward dimensions. Previous studies demonstrated that dopamine prediction error responses reflect the value of singular reward attributes that include magnitude, probability, and delay. Obviously, preferences between rewards that vary along one dimension are completely determined by the manipulated variable. However, it is unknown whether dopamine prediction error responses reflect the subjective value integrated from different reward dimensions. Here, we measured the preferences between rewards that varied along multiple dimensions, and as such could not be ranked according to objective metrics. Monkeys chose between rewards that differed in amount, risk, and type. Because their choices were complete and transitive, the monkeys chose “as if” they integrated different rewards and attributes into a common scale of value. The prediction error responses of single dopamine neurons reflected the integrated subjective value inferred from the choices, rather than the singular reward attributes. Specifically, amount, risk, and reward type modulated dopamine responses exactly to the extent that they influenced economic choices, even when rewards were vastly different, such as liquid and food. This prediction error response could provide a direct updating signal for economic values.Prediction errors represent the difference between predicted and realized outcomes. As such they are an ideal way to learn through everyday experiences (1). These experiences include making value-based (economic) choices between different rewards and evaluating the outcome of such decisions. Some of the most common economic decisions we face are between rewards that lack a common quality for comparison. To facilitate consistent choices between them, such rewards should be evaluated on a common scale of value (2–4). Thus, an ideal way to facilitate and reinforce economic decisions is to encode the prediction error directly in terms of subjective value. Midbrain dopamine neurons encode a reward prediction error (5–7) that is sufficient to cause learning (8, 9). These neurons receive inputs from several brain areas that encode subjective value and project axons to every brain structure implicated in economic choice (10–21). Therefore, dopamine neurons are ideally positioned to broadcast a teaching signal that directly updates economic values.Economic preferences between alternatives that vary in one attribute are easily determined by the magnitude of the attribute (22). For instance, larger rewards are preferred over smaller ones, high reward probability is preferred over low reward probability, and reward delivered after a short delay is preferred over the same reward delivered after a long delay. Subjective preferences can only be isolated from the underlying reward attributes for rewards that vary in more than one dimension. Although previous studies showed that dopamine responses reflected magnitude, probability, and delay (23–25), it remained unclear how dopamine responses would reflect individuals’ subjective preferences among rewards that vary along multiple dimensions. These rewards cannot be ordered according to objective metrics; rather, the subjective rankings of such rewards can only be inferred by observing an individual’s choices (26). If those choices are complete and transitive, then the individual behaved as if she was maximizing subjective value (26). Completeness demonstrates that the individual had preferences (or was indifferent) between all of the rewards, whereas the transitive property provides strong evidence that different reward attributes were integrated onto a common scale, and that choices were made by selecting the highest rank on that scale (27). Therefore, the activity of neurons that encode subjective value should reflect the transitive ordering of rewards that vary in more than one attribute.Here, we varied the amount, risk, and type of rewards and used different behavioral economic paradigms to infer the subjective value of these rewards from monkeys’ choices. These tests provided a means to quantify the influence of singular reward attributes on a common value scale. In close correspondence to the behaviorally defined reward value, the dopamine prediction error response reflected the integrated subjective value derived from different rewards rather than distinguishing between their attributes.