Loneliness corresponds with neural representations and language use that deviate from shared cultural perceptions.

The word zeitgeist refers to common perceptions shared in a given culture. Meanwhile, a defining feature of loneliness is feeling that one's views are not shared with others. Does loneliness correspond with deviating from the zeitgeist? Across two independent brain imaging datasets, lonely participants' neural representations of well-known celebrities strayed from group-consensus neural representations in the medial prefrontal cortex-a region that encodes and retrieves social knowledge (Studies 1 A/1B: N = 40 each). Because communication fosters social connection by creating shared reality, we next asked whether lonelier participants' communication about well-known celebrities also deviates from the zeitgeist. Indeed, when a strong group consensus exists, lonelier individuals use idiosyncratic language to describe well-known celebrities (Study 2: N = 923). Collectively, results support lonely individuals' feeling that their views are not shared. This suggests loneliness may not only reflect impoverished relationships with specific individuals, but also feelings of disconnection from prevalently shared views of contemporary culture.

Individuals who see the good in the bad engage distinctive default network coordination during post-encoding rest.

Focusing on the upside of negative events often promotes resilience. Yet, the underlying mechanisms that allow some people to spontaneously see the good in the bad remain unclear. The broaden-and-build theory of positive emotion has long suggested that positive affect, including positivity in the face of negative events, is linked to idiosyncratic thought patterns (i.e., atypical cognitive responses). Yet, evidence in support of this view has been limited, in part, due to difficulty in measuring idiosyncratic cognitive processes as they unfold. To overcome this barrier, we applied Inter-Subject Representational Similarity Analysis to test whether and how idiosyncratic neural responding supports positive reactions to negative experience. We found that idiosyncratic functional connectivity patterns in the brain's default network while resting after a negative experience predicts more positive descriptions of the event. This effect persisted when controlling for connectivity 1) before and during the negative experience, 2) before, during, and after a neutral experience, and 3) between other relevant brain regions (i.e., the limbic system). The relationship between idiosyncratic default network responding and positive affect was largely driven by functional connectivity patterns between the ventromedial prefrontal cortex and the rest of the default network and occurred relatively quickly during rest. We identified post-encoding rest as a key moment and the default network as a key brain system in which idiosyncratic responses correspond with seeing the good in the bad.

The boundary between real and fictional others in the medial prefrontal cortex is blurred in lonelier individuals.

People spend much of their free time engaging with narrative fiction. Research shows that, like real-life friends, fictional characters can sometimes influence individuals' attitudes, behaviors, and self-beliefs. Moreover, for certain individuals, fictional characters can stand in for real-life friends by providing the experience of belonging. Despite these parallels between how people think of real and fictional others, it is unclear whether, and to what degree, their neural representations are similar. Does the brain treat psychologically close fictional others as it does close real-world friends, or are real others somehow privileged in their neural representation? In the present study, fans of the HBO series Game of Thrones performed a trait-evaluation task for the self, 9 real-life friends/acquaintances, and 9 fictional characters from Game of Thrones while undergoing functional magnetic resonance imaging. Using both brain decoding and representational similarity analysis, we found evidence of a categorical boundary between real and fictional others within the medial prefrontal cortex. However, the boundary between these categories was blurred in lonelier individuals. These results suggest that lonelier individuals may turn to fictional characters to meet belongingness needs, and this, in turn, alters the manner in which these categories are encoded within the social brain.

They Saw a Debate: Political Polarization Is Associated with Greater Multivariate Neural Synchrony When Viewing the Opposing Candidate Speak.

With rampant polarization in current U.S. politics, it seems as though political partisans with opposing viewpoints are living in parallel realities. Indeed, prior research shows that people's impressions/attitudes toward political candidates are intertwined with their political affiliation. The current study investigated the relationship between political affiliation and intersubject neural synchrony of multivariate patterns of activity during naturalistic viewing of a presidential debate. Before the 2016 U.S. presidential election, 20 individuals varying in political affiliation underwent functional neuroimaging while watching the first debate between candidates Hillary Clinton and Donald Trump. Pairs of participants with more polarized political affiliations were higher in neural synchrony in a system of brain regions involved in self-referential processing when viewing the opposing candidate speak compared with that candidate's supporters regardless of which extreme of the political spectrum they occupied. Moreover, pairs of political partisans matching in the candidate they supported were higher in neural synchrony when watching the candidate they opposed compared with the one they both supported. These findings suggest that political groups' shared understanding may be driven more by perceptions of outgroups than of their own party/candidates.

Becoming the King in the North: identification with fictional characters is associated with greater self-other neural overlap.

During narrative experiences, identification with a fictional character can alter one's attitudes and self-beliefs to be more similar to those of the character. The ventral medial prefrontal cortex (vMPFC) is a brain region that shows increased activity when introspecting about the self but also when thinking of close friends. Here, we test whether identification with fictional characters is associated with increased neural overlap between self and fictional others. Nineteen fans of the HBO series Game of Thrones performed trait evaluations for the self, 9 real-world friends and 9 fictional characters during functional neuroimaging. Overall, the participants showed a larger response in the vMPFC for self compared to friends and fictional others. However, among the participants higher in trait identification, we observed a greater neural overlap in the vMPFC between self and fictional characters. Moreover, the magnitude of this association was greater for the character that participants reported feeling closest to/liked the most as compared to those they felt least close to/liked the least. These results suggest that identification with fictional characters leads people to incorporate these characters into their self-concept: the greater the immersion into experiences of 'becoming' characters, the more accessing knowledge about characters resembles accessing knowledge about the self.

Is subjective well-being independently associated with mortality? A 14-year prospective cohort study in a representative sample of 25 139 US men and women.

OBJECTIVES: To examine whether the inverse association of subjective well-being with mortality is independent of self-rated health and socioeconomic status in healthy adults. DESIGN: A population-based prospective cohort study based on an in-person interview. Cox regression was used to examine mortality hazards for happiness alone and for a standardised summary well-being measure that included happiness, life satisfaction and negative emotions. Using prespecified analyses, we first adjusted for age and then additionally adjusted for self-rated health and then race/ethnicity, marital status, smoking and socioeconomic status. SETTING: Probability sample of adult US residents interviewed in their homes in 2001. PARTICIPANTS: 25 139 adults free of cardiovascular disease and cancer at baseline. PRIMARY OUTCOME MEASURE: All-cause mortality 14 years after the baseline interview as assessed by probabilistic matching using the National Death Index. RESULTS: Age-adjusted unhappiness was associated with mortality (HR 1.27; 95% CI 1.11 to 1.45, p=0.001) but the association attenuated after adjusting for self-rated health (HR 1.01; 95% CI 0.88 to 1.16, p=0.85). A similar pattern was seen for the summary well-being measure in fully adjusted models (HR 1.00; 95% CI 0.99 to 1.00, p=0.30). In contrast, self-rated health was strongly associated with mortality. In the fully adjusted model with the summary well-being measure the hazards for good, very good and excellent self-rated health were 0.71 (95% CI 0.62 to 0.80, p<0.001), 0.63 (95% CI 0.55 to 0.71, p<0.001) and 0.45 (95% CI 0.39 to 0.51, p<0.001), respectively. CONCLUSIONS: In this representative sample of US adults, the association between well-being and mortality was strongly attenuated by self-rated health and to a lesser extent socioeconomic status.

Decoding the neural representation of self and person knowledge with multivariate pattern analysis and data-driven approaches.

Multivariate pattern analysis and data-driven approaches to understand how the human brain encodes sensory information and higher level conceptual knowledge have become increasingly dominant in visual and cognitive neuroscience; however, it is only in recent years that these methods have been applied to the domain of social information processing. This review examines recent research in the field of social cognitive neuroscience focusing on how multivariate pattern analysis (e.g., pattern classification, representational similarity analysis) and data-driven methods (e.g., reverse correlation, intersubject correlation) have been used to decode and characterize high-level information about the self, other persons, and social groups. We begin with a review of what is known about how self-referential processing and person perception are represented in the medial prefrontal cortex based on conventional activation-based neuroimaging approaches. This is followed by a nontechnical overview of current multivariate pattern-based and data-driven neuroimaging methods designed to characterize and/or decode neural representations. The remainder of the review focuses on examining how these methods have been applied to the topic of self, person perception, and the perception of social groups. In this review, we highlight recent trends (e.g., analysis of social networks, decoding race and social groups, and the use of naturalistic stimuli) and discuss several theoretical challenges that arise from the application of these new methods to the question of how the brain represents knowledge about the self and others. This article is categorized under: Neuroscience > Cognition.