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

Representational similarity analysis of self- versus other-processing: Effect of trait aggressiveness

In this study, using the self/other adjective judgment task, we aimed to explore how people perceive themselves in comparison to various other people, including friends, strangers, and those they dislike. Next, using representational similarity analysis, we sought to elucidate how these perceptual similarities and differences are represented in brain activity and how aggressiveness is related to these representations. Behavioral ratings show that, on average, people tend to consider themselves more like their friends than neutral strangers, and least like people they dislike. This pattern of similarity is positively correlated with neural representation in social and cognitive circuits of the brain and negatively correlated with neural representation in emotional centers that may represent emotional arousal associated with various social objects. Aggressiveness seems to predispose a person to a pattern of behavior that is the opposite of the average pattern, that is, a tendency to think of oneself as less like one's friends and more like one's enemies. This corresponds to an increase in the similarity of the behavioral representation with the representation in the emotional centers and a decrease in its similarity with the representation in the social and cognitive centers. This can be seen as evidence that in individuals prone to aggression, behavior in the social environment may depend to a greater extent on the representation of social objects in the emotional rather than social and cognitive brain circuits.

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.

Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of self versus other

Research of social neuroscience establishes that regions in the brain's default-mode network (DN) and semantic network (SN) are engaged by socio-cognitive tasks. Research of the human connectome shows that DN and SN regions are both situated at the transmodal end of a cortical gradient but differ in their loci along this gradient. Here we integrated these 2 bodies of research, used the psychological continuity of self versus other as a "test-case," and used functional magnetic resonance imaging to investigate whether these 2 networks would encode social concepts differently. We found a robust dissociation between the DN and SN-while both networks contained sufficient information for decoding broad-stroke distinction of social categories, the DN carried more generalizable information for cross-classifying across social distance and emotive valence than did the SN. We also found that the overarching distinction of self versus other was a principal divider of the representational space while social distance was an auxiliary factor (subdivision, nested within the principal dimension), and this representational landscape was more manifested in the DN than in the SN. Taken together, our findings demonstrate how insights from connectome research can benefit social neuroscience and have implications for clarifying the 2 networks' differential contributions to social cognition.

Neural substrates of rewarding and punishing self representations in depressed suicide-attempting adolescents

Adolescence is a period of plasticity in neural substrates underpinning self-processing. Such substrates are worth studying in depressed youth at risks for suicide because altered neurobiology of self-processing might partially explain differences between suicide attempting youth versus youth who contemplate but do not attempt suicide. Understanding altered substrates of self-processing among depressed adolescents with suicide attempts is critical for developing targeted prevention and treatment. Healthy youth (N = 40), youth with depression and low (N = 33) or high suicide ideation (N = 28), and youth with depression and past suicide attempt (N = 28) heard positive or negative self-descriptors during fMRI and evaluated them from their own, their mother's, classmates', and best friend's perspectives. Lower bilateral caudate activity during positive self-processing distinguished suicide attempting adolescents from all other youth. Higher bilateral caudate activity during negatively valenced self-processing tended to distinguish youth with depression. Blunted reward circuitry during positive vs. negative self-related material tended to distinguish suicide attempting youth, reflecting potentially enhanced behavioral preparedness for punishing vs. rewarding self-relevant cues.

Spatially Adjacent Regions in Posterior Cingulate Cortex Represent Familiar Faces at Different Levels of Complexity

Extensive research has shown that perceptual information of faces is processed in a network of hierarchically-organized areas within ventral temporal cortex. For familiar and famous faces, perceptual processing of faces is normally accompanied by extraction of semantic knowledge about the social status of persons. Semantic processing of familiar faces could entail progressive stages of information abstraction. However, the cortical mechanisms supporting multistage processing of familiar faces have not been characterized. Here, using an event-related fMRI experiment, familiar faces from four celebrity groups (actors, singers, politicians, and football players) and unfamiliar faces were presented to the human subjects (both males and females) while they were engaged in a face categorization task. We systematically explored the cortical representations for faces, familiar faces, subcategories of familiar faces, and familiar face identities using whole-brain univariate analysis, searchlight-based multivariate pattern analysis (MVPA), and functional connectivity analysis. Convergent evidence from all these analyses revealed a set of overlapping regions within posterior cingulate cortex (PCC) that contained decodable fMRI responses for representing different levels of semantic knowledge about familiar faces. Our results suggest a multistage pathway in PCC for processing semantic information of faces, analogous to the multistage pathway in ventral temporal cortex for processing perceptual information of faces.SIGNIFICANCE STATEMENT Recognizing familiar faces is an important component of social communications. Previous research has shown that a distributed network of brain areas is involved in processing the semantic information of familiar faces. However, it is not clear how different levels of semantic information are represented in the brain. Here, we evaluated the multivariate response patterns across the entire cortex to discover the areas that contain information for familiar faces, subcategories of familiar faces, and identities of familiar faces. The searchlight maps revealed that different levels of semantic information are represented in topographically adjacent areas within posterior cingulate cortex (PCC). The results suggest that semantic processing of faces is mediated through progressive stages of information abstraction in PCC.

Reinstatement of Event Details during Episodic Simulation in the Hippocampus

According to the constructive episodic simulation hypothesis, episodic simulation (i.e., imagining specific novel future episodes) draws on some of the same neurocognitive processes that support episodic memory (i.e., recalling specific past episodes). Episodic retrieval supports the ability to simulate future experiences by providing access to episodic details (e.g., the people and locations that comprise memories) that can be recombined in new ways. In the current functional neuroimaging study, we test this hypothesis by examining whether the hippocampus, a region implicated in the reinstatement of episodic information during memory, supports reinstatement of episodic information during simulation. Employing a multivoxel pattern similarity analysis, we interrogated the similarity between hippocampal neural patterns during memory and simulation at the level of individual event details. Our findings indicate that the hippocampus supports the reinstatement of detail-specific information from episodic memory during simulation, with the level of reinstatement contributing to the subjective experience of simulated details.

Overlapping Functional Representations of Self- and Other-Related Thought are Separable Through Multivoxel Pattern Classification

Self-reflection and thinking about the thoughts and behaviors of others are important skills for humans to function in the social world. These two processes overlap in terms of the component processes involved, and share overlapping functional organizations within the human brain, in particular within the medial prefrontal cortex (MPFC). Several functional models have been proposed to explain these two processes, but none has directly explored the extent to which they are distinctly represented within different parts of the brain. This study used multivoxel pattern classification to quantify the separability of self- and other-related thought in the MPFC and expanded this question to the entire brain. Using a large-scale mega-analytic dataset, spanning three separate studies (n = 142), we find that self- and other-related thought can be reliably distinguished above chance within the MPFC, posterior cingulate cortex and temporal lobes. We highlight subcomponents of the ventral MPFC that are particularly important in representing self-related thought, and subcomponents of the orbitofrontal cortex robustly involved in representing other-related thought. Our findings indicate that representations of self- and other-related thought in the human brain are described best by a distributed pattern rather than stark localization or a purely ventral to dorsal linear gradient in the MPFC.

Computational approaches to the neuroscience of social perception

Across multiple domains of social perception-including social categorization, emotion perception, impression formation and mentalizing-multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data has permitted a more detailed understanding of how social information is processed and represented in the brain. As in other neuroimaging fields, the neuroscientific study of social perception initially relied on broad structure-function associations derived from univariate fMRI analysis to map neural regions involved in these processes. In this review, we trace the ways that social neuroscience studies using MVPA have built on these neuroanatomical associations to better characterize the computational relevance of different brain regions, and discuss how MVPA allows explicit tests of the correspondence between psychological models and the neural representation of social information. We also describe current and future advances in methodological approaches to multivariate fMRI data and their theoretical value for the neuroscience of social perception.

Neural processing of personal, relational, and collective self-worth reflected individual differences of self-esteem

INTRODUCTION

Self-esteem stems from an individual's attributes (PSE), relationships with important others (RSE), and collective membership (CSE). Our study aimed to identify neurological indicators in the processing of personal, relational, and collective self-worth, and to investigate whether these neural indicators could reflect individual differences of self-esteem.

METHODS

Fifty students underwent the evaluation of personal, relational, and collective self-worth using a self-referential paradigm while brain activities were recorded using functional-magnetic-resonance-imaging. Meanwhile, their PSE, RSE, and CSE were measured through questionnaires.

RESULTS

Conjunction analysis found self-worth processing recruited the precuneus, posterior cingulate cortex, and posterior insula. Multivariate pattern analysis showed compared to relational and collective self-worth, personal self-worth processing was distinguished by cortical-midline-structures and affective-related regions, including caudate and putamen, and that these neural patterns could reflect individual differences of PSE. Compared to personal self-worth, relational self-worth was distinguished by the neural activity of temporoparietal-junction, and this neural pattern reflected individual differences of RSE. Compared to relational self-worth, collective self-worth was distinguished by neural activity of the anterior insula, and this neural pattern reflected individual differences of CSE.

DISCUSSION

These results suggested the neurological indicators of self-worth can be recognized as an alternative way to reflect individual differences of self-esteem.

Activation of Person Knowledge in Medial Prefrontal Cortex during the Encoding of New Lifelike Events

Our knowledge about people can help us predict how they will behave in particular situations and interpret their actions. In this study, we investigated the cognitive and neural effects of person knowledge on the encoding and retrieval of novel life-like events. Healthy human participants learnt about two characters over a week by watching 6 episodes of one of two situation comedies, which were both centered on a young couple. In the scanner, they watched and then silently recalled 20 new scenes from both shows that were all set in unfamiliar locations: 10 from their trained show and 10 from the untrained show. After scanning, participants' recognition memory was better for scenes from the trained show. The functional magnetic resonance imaging (fMRI) patterns of brain activity when watching the videos were reinstated during recall, but this effect was not modulated by training. However, person knowledge boosted the similarity in fMRI patterns of activity in the medial prefrontal cortex (MPFC) when watching the new events involving familiar characters. Our findings identify a role for the MPFC in the representation of schematic person knowledge during the encoding of novel, lifelike events.

Multivariable pattern classification differentiates relational self-esteem from personal self-esteem

Relational self-esteem (RSE) refers to one’s sense of self-worth based on the relationship with significant others, such as family and best friends. Although previous neuroimaging research has investigated the neural processes of RSE, it is less clear how RSE is represented in multivariable neural patterns. Being able to identify a stable RSE signature could contribute to knowledge about relational self-worth. Here, using multivariate pattern classification to differentiate RSE from personal self-esteem (PSE), which pertains to self-worth derived from personal attributes, we obtained a stable diagnostic signature of RSE relative to PSE. We found that multivariable neural activities in the superior/middle temporal gyrus, precuneus, posterior cingulate cortex, dorsal medial Prefrontal Cortex (dmPFC) and temporo-parietal junction were responsible for diagnosis of RSE, suggesting that the evaluation of RSE involves the retrieval of relational episodic memory, perspective-taking and value calculation. Further, these diagnostic neural signatures were able to sensitively decode neural activities related to RSE in another independent test sample, indicating the reliability of the brain state represented. By providing a reliable multivariate brain pattern for RSE relative to PSE, our results informed more cognitively prominent processing of RSE than that of PSE and enriched our knowledge about how relational self-worth is generated in the brain.

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.

Self-Other Representation in the Social Brain Reflects Social Connection

Social connection is critical to well-being, yet how the brain reflects our attachment to other people remains largely unknown. We combined univariate and multivariate brain imaging analyses to assess whether and how the brain organizes representations of others based on how connected they are to our own identity. During an fMRI scan, female and male human participants (N = 43) completed a self- and other-reflection task for 16 targets: the self, five close others, five acquaintances, and five celebrities. In addition, they reported their subjective closeness to each target and their own trait loneliness. We examined neural responses to the self and others in a brain region that has been associated with self-representation (mPFC) and across the whole brain. The structure of self-other representation in the mPFC and across the social brain appeared to cluster targets into three social categories: the self, social network members (including close others and acquaintances), and celebrities. Moreover, both univariate activation in mPFC and multivariate self-other similarity in mPFC and across the social brain increased with subjective self-other closeness ratings. Critically, participants who were less socially connected (i.e., lonelier) showed altered self-other mapping in social brain regions. Most notably, in mPFC, loneliness was associated with reduced representational similarity between the self and others. The social brain apparently maintains information about broad social categories as well as closeness to the self. Moreover, these results point to the possibility that feelings of chronic social disconnection may be mirrored by a "lonelier" neural self-representation.SIGNIFICANCE STATEMENT Social connection is critical to well-being, yet how the brain reflects our attachment to people remains unclear. We found that the social brain stratifies neural representations of people based on our subjective connection to them, separately clustering people who are and are not in our social network. Moreover, the people we feel closest to are represented most closely to ourselves. Finally, lonelier individuals also appeared to have a "lonelier" neural self-representation in the mPFC, as loneliness attenuated the similarity between self and other neural representations in this region. The social brain appears to map our interpersonal ties, and alterations in this map may help explain why lonely individuals endorse statements such as "people are around me but not with me."

A Guide to Representational Similarity Analysis for Social Neuroscience

Representational similarity analysis (RSA) is a computational technique that uses pairwise comparisons of stimuli to reveal their representation in higher-order space. In the context of neuroimaging, mass-univariate analyses and other multivariate analyses can provide information on what and where information is represented but have limitations in their ability to address how information is represented. Social neuroscience is a field that can particularly benefit from incorporating RSA techniques to explore hypotheses regarding the representation of multidimensional data, how representations can predict behavior, how representations differ between groups and how multimodal data can be compared to inform theories. The goal of this paper is to provide a practical as well as theoretical guide to implementing RSA in social neuroscience studies.

Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

Theoretical neuroscience investigation shows valuable information on the mechanism for recognizing the biological movements in the mammalian visual system. This involves many different fields of researches such as psychological, neurophysiology, neuro-psychological, computer vision, and artificial intelligence (AI). The research on these areas provided massive information and plausible computational models. Here, a review on this subject is presented. This paper describes different perspective to look at this task including action perception, computational and knowledge based modeling, psychological, and neuroscience approaches.