The neural representation of social networks

Similarity Among Friends Serves as a Social Prior: The Assumption That "Birds of a Feather Flock Together" Shapes Social Decisions and Relationship Beliefs

Social interactions unfold within networks of relationships. How do beliefs about others' social ties shape-and how are they shaped by-expectations about how others will behave? Here, participants joined a fictive online game-playing community and interacted with its purported members, who varied in terms of their trustworthiness and apparent relationships with one another. Participants were less trusting of partners with untrustworthy friends, even after they consistently showed themselves to be trustworthy, and were less willing to engage with them in the future. To test whether people not only expect friends to behave similarly but also expect those who behave similarly to be friends, an incidental memory test was given. Participants were exceptionally likely to falsely remember similarly behaving partners as friends. Thus, people expect friendship to predict similar behavior and vice versa. These results suggest that knowledge of social networks and others' behavioral tendencies reciprocally interact to shape social thought and behavior.

Strengths of social ties modulate brain computations for third-party punishment

Costly punishment of social norm transgressors by third-parties has been considered as a decisive stage in the evolution of human cooperation. An important facet of social relationship knowledge concerns the strength of the social ties between individuals, as measured by social distance. Yet, it is unclear how the enforcement of social norms is influenced by the social distance between a third-party and a norm violator at the behavioral and the brain system levels. Here, we investigated how social distance between punishers and norm-violators influences third-party punishment. Participants as third-party punished norm violators more severely as social distance between them increased. Using model-based fMRI, we disentangled key computations contributing to third-party punishment: inequity aversion, social distance between participant and norm violator and integration of the cost to punish with these signals. Inequity aversion increased activity in the anterior cingulate cortex and bilateral insula, and processing social distance engaged a bilateral fronto-parietal cortex brain network. These two brain signals and the cost to punish were integrated in a subjective value signal of sanctions that modulated activity in the ventromedial prefrontal cortex. Together, our results reveal the neurocomputational underpinnings of third-party punishment and how social distance modulates enforcement of social norms in humans.

Using Network Science and Psycholinguistic Megastudies to Examine the Dimensions of Phonological Similarity

Network science was used to examine different dimensions of phonological similarity in English. Data from a phonological associate task and an identification of words in noise task were used to create a phonological association network and a misperception network. These networks were compared to a network formed by a computational metric widely used to assess phonological similarity (i.e., one-phoneme metric). The phonological association network and the misperception network were topographically more similar to each other than either were to the one-phoneme metric network, but there were several network features in common between the one-phoneme metric network and the phonological association network. To assess the influence of network structure on processing, we compared the influence of degree (i.e., neighborhood density) from each of the networks on visual and auditory lexical decision reaction times obtained from two psycholinguistic megastudies. The effect of degree differed across network types and tasks. We discuss the use of each approach to determine phonological similarity and a possible direction forward for language research through the use of multiplex networks.

Neural encoding of novel social networks: evidence that perceivers prioritize others' centrality

Knowledge of someone's friendships can powerfully impact how one interacts with them. Previous research suggests that information about others' real-world social network positions-e.g. how well-connected they are (centrality), 'degrees of separation' (relative social distance)-is spontaneously encoded when encountering familiar individuals. However, many types of information covary with where someone sits in a social network. For instance, strangers' face-based trait impressions are associated with their social network centrality, and social distance and centrality are inherently intertwined with familiarity, interpersonal similarity and memories. To disentangle the encoding of the social network position from other social information, participants learned a novel social network in which the social network position was decoupled from other factors and then saw each person's image during functional magnetic resonance imaging scanning. Using representational similarity analysis, we found that social network centrality was robustly encoded in regions associated with visual attention and mentalizing. Thus, even when considering a social network in which one is not included and where centrality is unlinked from perceptual and experience-based features to which it is inextricably tied in naturalistic contexts, the brain encodes information about others' importance in that network, likely shaping future perceptions of and interactions with those individuals.

Predicting verbal reasoning from virtual community membership in a sample of Russian young adults

Predicting personality traits from social networking site profiles can help to assess individual differences in verbal reasoning without using long questionnaires. Inspired by earlier studies, which investigated whether abstract-thinking ability are predictable by social networking sites data, we used supervised machine learning to predict verbal-reasoning ability based on a proposed set of features extracted from virtual community membership. A large sample (N = 3,646) of Russian young adults aged 18-22 years approved access to the data from their social networking accounts and completed an online test on verbal reasoning. We experimented with binary classification machine-learning models for verbal-reasoning prediction. Prediction performance was tested on isolated control subsamples for men and women. The results of prediction on AUC-ROC metrics for control subsamples over 0.7 indicated reasonably good performance on predicting verbal-reasoning level. We also investigated the contribution of virtual community's genres to verbal reasoning level prediction for male and female participants. Theoretical interpretations of results stemming from both Vygotsky's sociocultural theory and behavioural genomics are discussed, including the implication that virtual communities make up a non-shared environment that can cause variance in verbal reasoning. We intend to conduct studies to explore the implications of the results further.

Shared neural codes for visual and semantic information about familiar faces in a common representational space

Our brain processes faces of close others differently than faces of visually familiar individuals. While both types of faces activate similar visual areas, faces of close others activate areas involved in processing social and semantic information. Here, we used between-subject linear classifiers trained on hyperaligned brain data to investigate the neural code for visual and semantic information about familiar others. The identity of both visually and personally familiar faces could be decoded across participants from brain activity in visual areas. Instead, only the identity of personally familiar faces could be decoded in areas involved in social cognition. Our results suggest that individually distinctive information associated with familiar faces is embedded in a neural code that is shared across brains.

Processes evoked by seeing a personally familiar face encompass recognition of visual appearance and activation of social and person knowledge. Whereas visual appearance is the same for all viewers, social and person knowledge may be more idiosyncratic. Using between-subject multivariate decoding of hyperaligned functional magnetic resonance imaging data, we investigated whether representations of personally familiar faces in different parts of the distributed neural system for face perception are shared across individuals who know the same people. We found that the identities of both personally familiar and merely visually familiar faces were decoded accurately across brains in the core system for visual processing, but only the identities of personally familiar faces could be decoded across brains in the extended system for processing nonvisual information associated with faces. Our results show that personal interactions with the same individuals lead to shared neural representations of both the seen and unseen features that distinguish their identities.

When and Why Did Human Brains Decrease in Size? A New Change-Point Analysis and Insights From Brain Evolution in Ants

Human brain size nearly quadrupled in the six million years since Homo last shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution of Homo and technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history of Homo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.

Computational methods in social neuroscience: recent advances, new tools and future directions

Recent years have seen a surge of exciting developments in the computational tools available to social neuroscientists. This paper highlights and synthesizes recent advances that have been enabled by the application of such tools, as well as methodological innovations likely to be of interest and utility to social neuroscientists, but that have been concentrated in other sub-fields. Papers in this special issue are emphasized—many of which contain instructive materials (e.g. tutorials and code) for researchers new to the highlighted methods. These include approaches for modeling social decisions, characterizing multivariate neural response patterns at varying spatial scales, using decoded neurofeedback to draw causal links between specific neural response patterns and psychological and behavioral phenomena, examining time-varying patterns of connectivity between brain regions, and characterizing the social networks in which social thought and behavior unfold in everyday life. By combining computational methods for characterizing participants’ rich social environments—at the levels of stimuli, paradigms and the webs of social relationships that surround people—with those for capturing the psychological processes that undergird social behavior and the wealth of information contained in neuroimaging datasets, social neuroscientists can gain new insights into how people create, understand and navigate their complex social worlds.

Mental travel in the person domain

"Mental travel" is a cognitive concept embodying the human capacity to intentionally disengage from the here and now, and mentally experience the world from different perspectives. We explored how individuals mentally "travel" to the point of view (POV) of other people in varying levels of personal closeness and from these perspectives process these people's social network. Under fMRI, participants were asked to "project" themselves to the POVs of four different people: a close other, a nonclose other, a famous-person, and their own-self, and rate the level of affiliation (closeness) to different individuals in the respective social network. Participants were always faster making judgments from their own POV compared with other POVs (self-projection effect) and for people who were personally closer to their adopted POV (social-distance effect). Brain activity at the medial prefrontal and anterior cingulate cortex in the self-POV was higher, compared with all other conditions. Activity at the right temporoparietal junction and medial parietal cortex was found to distinguish between the personally related (self, close, and nonclose others) and unrelated (famous-person) people. No difference was found between mental travel to the POVs of close and nonclose others. Regardless of POV, the precuneus, anterior cingulate cortex, prefrontal cortex, and temporoparietal junction distinguished between close and distant individuals within the different social networks. Representational similarity analysis implicated the left retrosplenial cortex as crucial for social distance processing across all POVs. These distinctions suggest several constraints regarding our ability to adopt others' POV and process not only ours but also other people's social networks and stress the importance of proximity in social cognition.NEW & NOTEWORTHY Mental-travel, the ability to mentally imagine oneself in a different place and time, is a fundamental cognitive concept. Investigation of mental-travel in the social domain under fMRI revealed that a network of brain regions, largely overlapping the default-mode-network, is responsible for "traveling" to points of view of different others; moreover, this network distinguishes between closer and less-close others, suggesting that mental-travel is a rich dynamical process, encompassing individuals in different proximities and these individuals' social network.

The golden age of social science

Social science is entering a golden age, marked by the confluence of explosive growth in new data and analytic methods, interdisciplinary approaches, and a recognition that these ingredients are necessary to solve the more challenging problems facing our world. We discuss how developing a "lingua franca" can encourage more interdisciplinary research, providing two case studies (social networks and behavioral economics) to illustrate this theme. Several exemplar studies from the past 12 y are also provided. We conclude by addressing the challenges that accompany these positive trends, such as career incentives and the search for unifying frameworks, and associated best practices that can be employed in response.

The Social Neuroscience of Prejudice

The social neuroscience approach to prejudice investigates the psychology of intergroup bias by integrating models and methods of neuroscience with the social psychology of prejudice, stereotyping, and discrimination. Here, we review major contemporary lines of inquiry, including current accounts of group-based categorization; formation and updating of prejudice and stereotypes; effects of prejudice on perception, emotion, and decision making; and the self-regulation of prejudice. In each section, we discuss key social neuroscience findings, consider interpretational challenges and connections with the behavioral literature, and highlight how they advance psychological theories of prejudice. We conclude by discussing the next-generation questions that will continue to guide the social neuroscience approach toward addressing major societal issues of prejudice and discrimination.

How Does the Brain Infer Hidden Social Structures?

Many everyday thoughts and actions are shaped not only by our direct relationships with others, but also by our knowledge of relations between third-parties. Lau et al. recently demonstrated how knowledge of one type of social relation - interpersonal similarity - shapes cognition and behavior, and shed light on the neural basis of such phenomena.

Social network analysis for social neuroscientists

Although social neuroscience is concerned with understanding how the brain interacts with its social environment, prevailing research in the field has primarily considered the human brain in isolation, deprived of its rich social context. Emerging work in social neuroscience that leverages tools from network analysis has begun to advance knowledge of how the human brain influences and is influenced by the structures of its social environment. In this paper, we provide an overview of key theory and methods in network analysis (especially for social systems) as an introduction for social neuroscientists who are interested in relating individual cognition to the structures of an individual’s social environments. We also highlight some exciting new work as examples of how to productively use these tools to investigate questions of relevance to social neuroscientists. We include tutorials to help with practical implementations of the concepts that we discuss. We conclude by highlighting a broad range of exciting research opportunities for social neuroscientists who are interested in using network analysis to study social systems.

Multiple Factors Act Differently in Decision Making in the East Asian Region: Assessing Methods of Self-Construal Using Classification Tree Analysis

Cultural resemblance between Japan and Korea has been assumed, because both East Asian cultures are generally characterized by collectivism. However, subsequent investigations suggest a contrast between the two cultures in the decision-making process, concurrent with a growing call for a more elaborate model of self-construal. This study compares the diverse ways of self-construal underlying decisions regarding invitations between Japan and Korea. We conducted a scenario-based questionnaire in which 377 Japanese and Korean college students made decisions regarding whether to invite someone to an activity, to do the activity alone, or to not do the activity. Utilizing classification tree modeling to analyze multivariate categorical data, we examined the participants’ selected actions according to two factors: interpersonal relations (i.e., whether the other was a friend or an unfamiliar but favored classmate) and the locus of interest in a given situation (i.e., whether the event was of interest to the speaker, hearer, or both parties). The results revealed cultural variations in invitations. Japanese students seem to be interdependent, in that they hesitate to invite others unless they have an assured interpersonal relationship, and tend to wait until they are sure of the other’s interest, even when interested themselves. In contrast, Korean students appear more independent in considering the other’s interest and pursuing their own interest. This study highlights the complex ways of self-construal within the alleged collectivist East Asian region, and also demonstrates the applicability of classification tree analysis in differentiating rank orders of multiple factors influencing people’s decision making across cultures.

An association between biased impression updating and relationship facilitation: A behavioral and fMRI investigation

Is ingroup bias associated with any benefit for maintaining close relationships? We examined the link between biased impression updating for ingroup members (i.e., friends) and relationship maintenance, as measured by the number of friends participants reported having (Studies 1 and 2). We also investigated the underlying neural basis of this possible effect, focusing on activity in the right temporo-parietal junction (RTPJ), a region of the social brain involved in moral updating (Study 2). Specifically, we tested whether selectively discounting negative information about close others, manifested in reduced impression updating, and indexed by reduced RTPJ activity, is related to maintaining close relationships. In Study 1, after imagining a friend and a stranger performing different positive and negative behaviors, participants who were reluctant to update how close they felt to their friend (friend-closeness) reported having more friends in real life. In Study 2, participants were led to believe that a friend and a stranger gave money to them or took money away from them, while they were in the scanner. Participants who engaged in less negative updating of friends versus strangers reported having more friends. Participants who engaged in less friend-closeness updating also showed reduced RTPJ activity when their friend took money from them, and this neural pattern was associated with reports of having more friends. Together, these findings suggest that selectively discounting close others' negative behavior is linked to maintaining close relationships, indicating a potential social benefit of ingroup bias.