SignificanceWhy do humans share information with others? Large-scale sharing is one of the most prominent social phenomena of the 21st century, with roots in the oldest forms of communication. We argue that expectations of self-related and social consequences of sharing are integrated into a domain-general value signal, representing the value of information sharing, which translates into population-level virality. We analyzed brain responses to New York Times articles in two separate groups of people to predict objectively logged sharing of those same articles around the world (virality). Converging evidence from the two studies supports a unifying, parsimonious neurocognitive framework of mechanisms underlying health news virality; these results may help advance theory, improve predictive models, and inform new approaches to effective intervention.

Humans routinely share information with others. What drives us to do so? We used neuroimaging to test an account of information selection and sharing that emphasizes inherent reward in self-reflection and connecting with others. Participants underwent fMRI while they considered personally reading and sharing New York Times articles. Activity in hypothesized neural regions involved in positive valuation, self-related processing and taking the perspective of others was significantly associated with decisions to select and share articles, and scaled with preferences to do so. Activity in all three regions was greater when participants considered sharing with others versus selecting articles to read themselves. Findings suggest that people may consider value not only to self, but also to others even when selecting news articles to consume personally. Further, sharing heightens these pathways, in line with our proposed account of humans deriving value from self-reflection and connecting to others via sharing.

Convergent processing of the world may be a factor that contributes to social connectedness. We use neuroimaging and network analysis to investigate the association between the social-network position (as measured by in-degree centrality) of first-year university students and their neural similarity while watching naturalistic audio-visual stimuli (specifically, videos). There were 119 students in the social-network study; 63 of them participated in the neuroimaging study. We show that more central individuals had similar neural responses to their peers and to each other in brain regions that are associated with high-level interpretations and social cognition (e.g., in the default mode network), whereas less-central individuals exhibited more variable responses. Self-reported enjoyment of and interest in stimuli followed a similar pattern, but accounting for these data did not change our main results. These findings show that neural processing of external stimuli is similar in highly-central individuals but is idiosyncratic in less-central individuals.

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 pursue this issue, advancing 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 implementation 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.

What differentiates sharing with few, well-defined others (narrowcasting) from sharing with loosely defined crowds (broadcasting)? One possibility involves a trade-off where broadcasting is selffocused and self-serving, and narrowcasting is based on otheroriented, altruistic motives. We present neuroimaging data consistent with a second, parallel-processes perspective. According to this account, both narrow-and broadcasting simultaneously involve self-related and social motives since these concepts are strongly intertwined both on a psychological and neural level. We recorded brain activity within regions that are meta-analytically associated with self-related and social cognition while participants made decisions to narrow-or broadcast New York Times articles on social media. Results show increased involvement of brain regions associated with both self-related and social processing in narrowand broadcasting, compared to a control condition. However, both processes were involved with higher intensity during narrowcasting, compared to broadcasting. These data help to disambiguate a theoretical discussion in communication science and clarify the neuropsychological mechanisms that drive sharing decisions in different contexts. Specifically, we highlight that narrow-and broadcasting afford differing intensities of two psychological processes that are crucial to persuasion and population-level content virality.

Information that is shared widely can profoundly shape society. Evidence from neuroimaging suggests that activity in the ventromedial prefrontal cortex (vmPFC), a core region of the brain's valuation system tracks with this sharing. However, the mechanisms linking vmPFC responses in individuals to population behavior are still unclear. We used a multilevel brain-as-predictor approach to address this gap, finding that individual differences in how closely vmPFC activity corresponded with population news article sharing related to how closely its activity tracked with social consensus about article value. Moreover, how closely vmPFC activity corresponded with population behavior was linked to daily life news experience: frequent news readers tended to show high vmPFC across all articles, whereas infrequent readers showed high vmPFC only to articles that were more broadly valued and heavily shared. Using functional connectivity analyses, we found that superior tracking of consensus value was related to decreased connectivity of vmPFC with a dorsolateral PFC region associated with controlled processing. Taken together, our results demonstrate variability in the brain's capacity to track crowd wisdom about information value, and suggest (lower levels of) stimulus experience and vmPFC-dlPFC connectivity as psychological and neural sources of this variability.

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What makes people successful at influencing others? In this review, we focus on the role of the persuader (i.e., person who attempts to influence a recipient), drawing from findings in neuroscience to highlight key drivers that contribute to persuaders' decisions to share information, and variables that distinguish successful persuaders from those who are less successful. We review evidence that people's motivations to share are guided in the brain by value-based decision making, with self-relevance and social-relevance as two key motivational inputs to the value computation. We then argue that persuaders who exhibit higher awareness of social considerations and increased recruitment of the brain's mentalizing system are more successful. We conclude by suggesting that approaches integrating social and neural networks can productively advance knowledge in this field.