Normativity vs. uniqueness: effects of social relationship strength on neural representations of others.

Understanding others involves inferring traits and intentions, a process complicated by our reliance on stereotypes and generalized information when we lack personal information. Yet, as relationships are formed, we shift toward nuanced and individualized perceptions of others. This study addresses how relationship strength influences the creation of unique or normative representations of others in key regions known to be involved in social cognition. Employing a round-robin interpersonal perception paradigm (N = 111, 20 groups of five to six people), we used functional magnetic resonance imaging to examine whether the strength of social relationships modulated the degree to which multivoxel patterns of activity that represented a specific other were similar to a normative average of all others in the study. Behaviorally, stronger social relationships were associated with more normative trait endorsements. Neural findings reveal that closer relationships lead to more unique representations in the medial prefrontal cortex and anterior insula, areas associated with mentalizing and person perception. Conversely, more generalized representations emerge in posterior regions like the posterior cingulate cortex, indicating a complex interplay between individuated and generalized processing of social information in the brain. These findings suggest that cortical regions typically associated with social cognition may compute different kinds of information when representing the distinctiveness of others.

Beyond the brain localization of complex traits: Distributed white matter markers of personality.

OBJECTIVE: Extensive work in personality neuroscience has shown mixed results in the ability to localize reliable relationships between personality traits and neuroimaging measures. However, recent work in translational neuroimaging has recognized that multifaceted psychological dispositions are not represented in discrete, highly localized brain areas. As such, standard univariate neuroimaging analyses may not be well-suited for capturing broad personality traits supported by distributed networks. METHOD: The present study uses an out-of-sample predictive modeling approach to identify multivariate signatures of Big Five personality traits within the structural integrity of white matter pathways using diffusion magnetic resonance imaging. In Study 1 (N = 491), we trained a ridge regression model to predict each of the Big Five traits and tested these models in an independent hold-out subsample. RESULTS: We found that models for both Neuroticism and Openness were significantly related to predictive accuracy in the hold-out sample. Study 2 (N = 108) applied Study 1's predictive models to an independent set of data collected on a different scanner and using a different Big Five scale. Here, we found that the model for Neuroticism remained a significant predictor of individual difference. CONCLUSION: Our findings provide evidence that this white matter signature of Neuroticism generalizes across differences in measurement and samples.

White matter connectivity in brain networks supporting social and affective processing predicts real-world social network characteristics.

Human behavior is embedded in social networks. Certain characteristics of the positions that people occupy within these networks appear to be stable within individuals. Such traits likely stem in part from individual differences in how people tend to think and behave, which may be driven by individual differences in the neuroanatomy supporting socio-affective processing. To investigate this possibility, we reconstructed the full social networks of three graduate student cohorts (N = 275; N = 279; N = 285), a subset of whom (N = 112) underwent diffusion magnetic resonance imaging. Although no single tract in isolation appears to be necessary or sufficient to predict social network characteristics, distributed patterns of white matter microstructural integrity in brain networks supporting social and affective processing predict eigenvector centrality (how well-connected someone is to well-connected others) and brokerage (how much one connects otherwise unconnected others). Thus, where individuals sit in their real-world social networks is reflected in their structural brain networks. More broadly, these results suggest that the application of data-driven methods to neuroimaging data can be a promising approach to investigate how brains shape and are shaped by individuals' positions in their real-world social networks.

Social Relationship Strength Modulates the Similarity of Brain-to-Brain Representations of Group Members.

Within our societies, humans form co-operative groups with diverse levels of relationship quality among individual group members. In establishing relationships with others, we use attitudes and beliefs about group members and the group as a whole to establish relationships with particular members of our social networks. However, we have yet to understand how brain responses to group members facilitate relationship quality between pairs of individuals. We address this here using a round-robin interpersonal perception paradigm in which each participant was both a perceiver and target for every other member of their group in a set of 20 unique groups of between 5 and 6 members in each (total N = 111). Using functional magnetic resonance imaging, we show that measures of social relationship strength modulate the brain-to-brain multivoxel similarity patterns between pairs of participants' responses when perceiving other members of their group in regions of the brain implicated in social cognition. These results provide evidence for a brain mechanism of social cognitive processes serving interpersonal relationship strength among group members.

Generalizing effects of frontostriatal structural connectivity on self-esteem using predictive modeling.

Determining the generalizability of biological mechanisms supporting psychological constructs is a central goal of cognitive neuroscience. Self-esteem is a popular psychological construct that is associated with a variety of measures of mental health and life satisfaction. Recently, there has been interest in identifying biological mechanisms that support individual differences in self-esteem. Understanding the biological basis of self-esteem requires identifying predictive biomarkers of self-esteem that generalize across groups of individuals. Previous research using diffusion magnetic resonance imaging has shown that self-esteem is related to the integrity of structural connections linking frontostriatal brain systems involved in self-referential processing and reward. However, these findings were based on a small, relatively homogeneous group of participants. In the current study, we used an out-of-sample predictive modeling approach to generalize the results of the previous study to an independent sample of participants more than twice the size of the original study. We found that both linear univariate and multivariate machine learning models trained on frontostriatal integrity from the original data significantly predicted self-esteem in the independent dataset. These findings underscore the relationship between self-esteem and frontostriatal connectivity and suggest these results are robust to differences in scanning acquisition, analytic methods, and participant demographics.

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.

Large-scale functional coactivation patterns reflect the structural connectivity of the medial prefrontal cortex.

The medial prefrontal cortex (MPFC) is among the most consistently implicated brain regions in social and affective neuroscience. Yet, this region is also highly functionally heterogeneous across many domains and has diverse patterns of connectivity. The extent to which the communication of functional networks in this area is facilitated by its underlying structural connectivity fingerprint is critical for understanding how psychological phenomena are represented within this region. In the current study, we combined diffusion magnetic resonance imaging and probabilistic tractography with large-scale meta-analysis to investigate the degree to which the functional coactivation patterns of the MPFC are reflected in its underlying structural connectivity. Using unsupervised machine learning techniques, we compared parcellations between the two modalities and found congruence between parcellations at multiple spatial scales. Additionally, using connectivity and coactivation similarity analyses, we found high correspondence in voxel-to-voxel similarity between each modality across most, but not all, subregions of the MPFC. These results provide evidence that meta-analytic functional coactivation patterns are meaningfully constrained by underlying neuroanatomical connectivity and provide convergent evidence of distinct subregions within the MPFC involved in affective processing and social cognition.

The neural representation of self is recapitulated in the brains of friends: A round-robin fMRI study.

Humans continually form and update impressions of each other's identities based on the disclosure of thoughts, feelings, and beliefs. At the same time, individuals also have specific beliefs and knowledge about their own self-concept. Over a decade of social neuroscience research has shown that retrieving information about the self and about other persons recruits similar areas of the medial prefrontal cortex (MPFC), however it remains unclear if an individual's neural representation of self is reflected in the brains of well-known others or if instead the two representations share no common relationship. Here we examined this question in a tight-knit network of friends as they engaged in a round-robin trait evaluation task in which each participant was both perceiver and target for every other participant and in addition also evaluated their self. Using functional MRI and a multilevel modeling approach, we show that multivoxel brain activity patterns in the MPFC during a person's self-referential thought are correlated with those of friends when thinking of that same person. Moreover, the similarity of neural self-other patterns was itself positively associated with the similarity of self-other trait judgments ratings as measured behaviorally in a separate session. These findings suggest that accuracy in person perception may be predicated on the degree to which the brain activity pattern associated with an individual thinking about their own self-concept is similarly reflected in the brains of others. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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.

Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem.

Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem 8 months after initial scanning in a sample of 30 young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions, including depression and anxiety.

Neural Population Decoding Reveals the Intrinsic Positivity of the Self.

People are motivated to hold favorable views of themselves, which manifests as a positivity bias when evaluating their own performance and abilities. However, it remains an open question whether positive affect is an essential component of people's self-concept. Prior functional neuroimaging research demonstrated that similar regions of the brain support positive affect and self-referential processing, although a direct test of their shared representation has yet to be examined. Here we use functional magnetic resonance imaging in conjunction with multivariate pattern analysis in a cross-domain neural population decoding paradigm. We found that a multivariate pattern classifier model trained to dissociate neural responses to viewing positively and negatively valenced images can dissociate thinking about oneself from a close friend during a lexical trait-judgment task commonly used in the study of self-referential processing. Cross-domain classification accuracy was found to be highest in the ventral medial prefrontal cortex (vMPFC), a region previously implicated in both self-referential processing and positive affect. These results show that brain responses during self-referential processing can be decoded from multi-voxel activation patterns in the vMPFC when viewing positively valenced material, thereby providing evidence that positive affect may be a central component of the mental representation of the self.

Structural integrity between executive control and reward regions of the brain predicts body fat percentage in chronic dieters.

Failure to maintain a healthy body weight may reflect a long-term imbalance between the executive control and reward systems of the brain. The current study examined whether the anatomical connectivity between these two systems predicted individual variability in achieving a healthy body weight, particularly in chronic dieters. Thirty-six female chronic dieters completed a food-cue reactivity task in the scanner. Two regions-of-interest (ROIs) were defined from the reactivity task: the inferior frontal gyrus (IFG), which engages cognitive control and the orbitofrontal cortex (OFC), which represents reward value. A white matter tract connecting these two ROIs was identified across participants using diffusion tensor imaging (DTI) and probabilistic tractography. Results showed a negative relationship between body fat percentage and white matter integrity within the identified tract. This suggests that reduced structural integrity between the OFC and IFG may be related to self-regulatory problems for those who chronically diet to control body weight.

White matter correlates of psychosis-linked traits support continuity between personality and psychopathology.

The link between diagnoses of psychotic disorders and attenuated white matter connectivity is well established, but little is known about the degree to which similar white matter differences predict traits linked to psychosis-proneness in the general population. Moreover, intelligence is too rarely considered as a covariate in neural endophenotype studies, despite its known protective role against psychopathology in general and its associations with broad aspects of neural structure and function. To determine whether psychosis-linked personality traits are linearly associated with white matter microstructure, we examined white matter correlates of Psychoticism, Absorption, and Openness to Experience in a large community sample, covarying for sex, age, and IQ. Findings support our hypothesis that the white matter correlates of the shared variance of these traits overlap substantially with the frontal lobe white matter connectivity patterns characteristic of psychotic spectrum disorders. These findings provide biological support for the notion that liability to psychosis is distributed throughout the population, is evident in brain structure, and manifests as normal personality variation at subclinical levels. (PsycINFO Database Record

Individual differences in response of dorsomedial prefrontal cortex predict daily social behavior.

The capacity to accurately infer the thoughts and intentions of other people is critical for effective social interaction, and neural activity in dorsomedial prefrontal cortex (dmPFC) has long been linked with the extent to which people engage in mental state attribution. In this study, we combined functional neuroimaging and experience sampling methodologies to test the predictive value of this neural response for daily social behaviors. We found that individuals who displayed greater activity in dmPFC when viewing social scenes spent more time around other people on a daily basis. These findings suggest a specific role for the neural mechanisms that support the capacity to mentalize in guiding individuals toward situations containing valuable social outcomes.

Representational similarity of social and valence information in the medial pFC.

The human brain is remarkably adept at integrating complex information to form unified psychological representations of agents, objects, and events in the environment. Two domains in which this ability is particularly salient are the processing of social and valence information and are supported by common cortical areas in the medial pFC (MPFC). Because social information is often embedded within valenced emotional contexts, it is possible that activation patterns within the MPFC may represent both of these types of cognitive processes when presented simultaneously. The current study tested this possibility by employing a large-scale automated meta-analysis tool, together with multivoxel pattern analysis to investigate the representational similarity of social and valence information in the MPFC during fMRI. Using a representational similarity analysis, we found a high degree of representational similarity both within social dimensions and within valence dimensions, but not across them (e.g., positive social information was highly dissimilar to negative nonsocial information), in a ventral portion of the MPFC. These results were significantly correlated with a behaviorally measured similarity structure of the same stimuli, suggesting that a psychologically meaningful representation of social and valence information is reflected by multivoxel activation patterns in the ventral MPFC.

Multimodal frontostriatal connectivity underlies individual differences in self-esteem.

A heightened sense of self-esteem is associated with a reduced risk for several types of affective and psychiatric disorders, including depression, anxiety and eating disorders. However, little is known about how brain systems integrate self-referential processing and positive evaluation to give rise to these feelings. To address this, we combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) to test how frontostriatal connectivity reflects long-term trait and short-term state aspects of self-esteem. Using DTI, we found individual variability in white matter structural integrity between the medial prefrontal cortex and the ventral striatum was related to trait measures of self-esteem, reflecting long-term stability of self-esteem maintenance. Using fMRI, we found that functional connectivity of these regions during positive self-evaluation was related to current feelings of self-esteem, reflecting short-term state self-esteem. These results provide convergent anatomical and functional evidence that self-esteem is related to the connectivity of frontostriatal circuits and suggest that feelings of self-worth may emerge from neural systems integrating information about the self with positive affect and reward. This information could potentially inform the etiology of diminished self-esteem underlying multiple psychiatric conditions and inform future studies of evaluative self-referential processing.

White matter correlates of neuropsychological dysfunction in systemic lupus erythematosus.

Patients diagnosed with Systemic Lupus Erythematosus have similar levels of neuropsychological dysfunction (i.e., 20-50%) as those with Neuropsychiatric Systemic Lupus Erythematosus (NPSLE). We hypothesized a gradient between cognition and white matter integrity, such that strongest brain-behavior relationships would emerge in NPSLE, intermediate in non-NPSLE, and minimal in controls. We studied thirty-one patients (16 non-NPSLE; 15 NPSLE), ranging in age from 18 to 59 years old (100% female), and eighteen age and gender matched healthy controls. DTI examinations were performed on a 1.5T scanner. A broad neuropsychological battery was administered, tapping attention, memory, processing speed, and executive functioning. The Total z-score consisted of the combined sum of all neuropsychological measures. In control subjects, we found no significant FA-Total z-score correlations. NPSLE, non-NPSLE, and control subjects differed significantly in terms of Total z-score (NPSLE = -2.25+/-1.77, non-NPSLE = -1.22+/-1.03, Controls = -0.10+/-.57; F = 13.2, p<.001). In non-NPSLE subjects, FA within the right external capsule was significantly correlated with Total z-score. In NPSLE subjects, the largest FA-Total z-score clusters were observed within the left anterior thalamic radiation and right superior longitudinal fasciculus. In subsequent analyses the largest number of significant voxels linked FA with the Processing Speed z-score in NPSLE. The current results reflect objective white matter correlates of neuropsychological dysfunction in both NPSLE and (to a lesser degree) in non-NPSLE. non-NPSLE and NPSLE subjects did not differ significantly in terms of depression, as measured by the GDI; thus, previous hypotheses suggesting moderating effects of depression upon neuropsychological performance do not impact the current FA results.

Diffusion tensor imaging in neuropsychiatric systemic lupus erythematosus.

BACKGROUND: Neuropsychiatric systemic lupus erythematosus (NPSLE) is associated with increased morbidity and mortality. METHODS: We used Diffusion Tensor Imaging (DTI) to assess white matter abnormalities in seventeen NPSLE patients, sixteen SLE patients without NPSLE, and twenty age- and gender-matched controls. RESULTS: NPSLE patients differed significantly from SLE and control patients in white matter integrity of the body of the corpus callosum, the left arm of the forceps major and the left anterior corona radiata. CONCLUSIONS: Several possible mechanisms of white matter injury are explored, including vascular injury, medication effects, and platelet or fibrin macro- or microembolism from Libman-Sacks endocarditis.

Neuroimaging creativity: a psychometric view.

Many studies of creative cognition with a neuroimaging component now exist; what do they say about where and how creativity arises in the brain? We reviewed 45 brain-imaging studies of creative cognition. We found little clear evidence of overlap in their results. Nearly as many different tests were used as there were studies; this test diversity makes it impossible to interpret the different findings across studies with any confidence. Our conclusion is that creativity research would benefit from psychometrically informed revision, and the addition of neuroimaging methods designed to provide greater spatial localization of function. Without such revision in the behavioral measures and study designs, it is hard to see the benefit of imaging. We set out eight suggestions in a manifesto for taking creativity research forward.

White matter integrity, creativity, and psychopathology: disentangling constructs with diffusion tensor imaging.

That creativity and psychopathology are somehow linked remains a popular but controversial idea in neuroscience research. Brain regions implicated in both psychosis-proneness and creative cognition include frontal projection zones and association fibers. In normal subjects, we have previously demonstrated that a composite measure of divergent thinking (DT) ability exhibited significant inverse relationships in frontal lobe areas with both cortical thickness and metabolite concentration of N-acetyl-aspartate (NAA). These findings support the idea that creativity may reside upon a continuum with psychopathology. Here we examine whether white matter integrity, assessed by Fractional Anisotropy (FA), is related to two measures of creativity (Divergent Thinking and Openness to Experience). Based on previous findings, we hypothesize inverse correlations within fronto-striatal circuits. Seventy-two healthy, young adult (18-29 years) subjects were scanned on a 3 Tesla scanner with Diffusion Tensor Imaging. DT measures were scored by four raters (alpha = .81) using the Consensual Assessment Technique, from which a composite creativity index (CCI) was derived. We found that the CCI was significantly inversely related to FA within the left inferior frontal white matter (t = 5.36, p = .01), and Openness was inversely related to FA within the right inferior frontal white matter (t = 4.61, p = .04). These findings demonstrate an apparent overlap in specific white matter architecture underlying the normal variance of divergent thinking, openness, and psychotic-spectrum traits, consistent with the idea of a continuum.