Neural connections foster social connections: a diffusion-weighted imaging study of social networks

Interactions between neural representations of the social and spatial environment

Even in our highly interconnected modern world, geographic factors play an important role in human social connections. Similarly, social relationships influence how and where we travel, and how we think about our spatial world. Here, we review the growing body of neuroscience research that is revealing multiple interactions between social and spatial processes in both humans and non-human animals. We review research on the cognitive and neural representation of spatial and social information, and highlight recent findings suggesting that underlying mechanisms might be common to both. We discuss how spatial factors can influence social behaviour, and how social concepts modify representations of space. In so doing, this review elucidates not only how neural representations of social and spatial information interact but also similarities in how the brain represents and operates on analogous information about its social and spatial surroundings.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Social network size, empathy, and white matter: A diffusion tensor imaging (DTI) study

Social networks are fundamental for social interactions, with the social brain hypothesis positing that the size of the neocortex evolved to meet social demands. However, the role of fractional anisotropy (FA) in white matter (WM) tracts relevant to mentalizing, empathy, and social networks remains unclear. In this study, we investigated the relationships between FA in brain regions associated with social cognition (superior longitudinal fasciculus (SLF), cingulum (CING), uncinate fasciculus, inferior fronto-occipital fasciculus), social network characteristics (diversity, size, complexity), and empathy (cognitive, affective). We employed diffusion tensor imaging, tract-based spatial statistics, and mediation analyses to examine these associations. Our findings revealed that increased social network size was positively correlated with FA in the left SLF. Further, our mediation analysis showed that lower FA in left CING was associated with increased social network size, mediated by cognitive empathy. In summary, our findings suggest that WM tracts involved in social cognition play distinct roles in social network size and empathy, potentially implicating affective brain regions. In conclusion, our findings offer new perspectives on the cognitive mechanisms involved in understanding others' mental states and experiencing empathy within supportive social networks, with potential implications for understanding individual differences in social behavior and mental health.

A framework for integrating neural development and social networks in adolescence

Adolescence is a developmental period characterized by increasingly complex and influential peer contexts. Concurrently, developmental changes in neural circuits, particularly those related to social cognition, affective salience, and cognitive control, contribute to individuals' social interactions and behaviors. However, while adolescents' behaviors and overall outcomes are influenced by the entirety of their social environments, insights from developmental and social neuroscience often come from studies of individual relationships or specific social actors. By capturing information about both adolescents' individual relations and their larger social contexts, social network analysis offers a powerful opportunity to enhance our understanding of how social factors interact with adolescent development. In this review, we highlight the relevant features of adolescent social and neural development that should be considered when integrating social network analysis and neuroimaging methods. We focus on broad themes of adolescent development, including identity formation, peer sensitivity, and the pursuit of social goals, that serve as potential mechanisms for the relations between neural processes and social network features. With these factors in mind, we review the current research and propose future applications of these methods and theories.

Face recognition's practical relevance: Social bonds, not social butterflies

Research on individual differences in face recognition has provided important foundational insights: their broad range, cognitive specificity, strong heritability, and resilience to change. Elusive, however, has been the key issue of practical relevance: do these individual differences correlate with aspects of life that go beyond the recognition of faces, per se? Though often assumed, especially in social realms, such correlates remain largely theoretical, without empirical support. Here, we investigate an array of potential social correlates of face recognition. We establish social relationship quality as a reproducible correlate. This link generalises across face recognition tasks and across independent samples. In contrast, we detect no robust association with the sheer quantity of social connections, whether measured directly via number of social contacts or indirectly via extraversion-related personality indices. These findings document the existence of a key social correlate of face recognition and provide some of the first evidence to support its practical relevance. At the same time, they challenge the naive assumption that face recognition relates equally to all social outcomes. In contrast, they suggest a focused link of face recognition to the quality, not quantity, of one's social connections.

Shared and distinct structural brain networks related to childhood maltreatment and social support: connectome-based predictive modeling

Childhood maltreatment (CM) has been associated with changes in structural brain connectivity even in the absence of mental illness. Social support, an important protective factor in the presence of childhood maltreatment, has been positively linked to white matter integrity. However, the shared effects of current social support and CM and their association with structural connectivity remain to be investigated. They might shed new light on the neurobiological basis of the protective mechanism of social support. Using connectome-based predictive modeling (CPM), we analyzed structural connectomes of N = 904 healthy adults derived from diffusion-weighted imaging. CPM predicts phenotypes from structural connectivity through a cross-validation scheme. Distinct and shared networks of white matter tracts predicting childhood trauma questionnaire scores and the social support questionnaire were identified. Additional analyses were applied to assess the stability of the results. CM and social support were predicted significantly from structural connectome data (all rs ≥ 0.119, all ps ≤ 0.016). Edges predicting CM and social support were inversely correlated, i.e., positively correlated with CM and negatively with social support, and vice versa, with a focus on frontal and temporal regions including the insula and superior temporal lobe. CPM reveals the predictive value of the structural connectome for CM and current social support. Both constructs are inversely associated with connectivity strength in several brain tracts. While this underlines the interconnectedness of these experiences, it suggests social support acts as a protective factor following adverse childhood experiences, compensating for brain network alterations. Future longitudinal studies should focus on putative moderating mechanisms buffering these adverse experiences.

Four errors and a fallacy: pitfalls for the unwary in comparative brain analyses

Comparative analyses are the backbone of evolutionary analysis. However, their record in producing a consensus has not always been good. This is especially true of attempts to understand the factors responsible for the evolution of large brains, which have been embroiled in an increasingly polarised debate over the past three decades. We argue that most of these disputes arise from a number of conceptual errors and associated logical fallacies that are the result of a failure to adopt a biological systems-based approach to hypothesis-testing. We identify four principal classes of error: a failure to heed Tinbergen's Four Questions when testing biological hypotheses, misapplying Dobzhansky's Dictum when testing hypotheses of evolutionary adaptation, poorly chosen behavioural proxies for underlying hypotheses, and the use of inappropriate statistical methods. In the interests of progress, we urge a more careful and considered approach to comparative analyses, and the adoption of a broader, rather than a narrower, taxonomic perspective.

Neural signatures of social inferences predict the number of real-life social contacts and autism severity

We regularly infer other people's thoughts and feelings from observing their actions, but how this ability contributes to successful social behavior and interactions remains unknown. We show that neural activation patterns during social inferences obtained in the laboratory predict the number of social contacts in the real world, as measured by the social network index, in three neurotypical samples (total n = 126) and one sample of autistic adults (n = 23). We also show that brain patterns during social inference generalize across individuals in these groups. Cross-validated associations between brain activations and social inference localize selectively to the right posterior superior temporal sulcus and were specific for social, but not nonsocial, inference. Activation within this same brain region also predicts autism-like trait scores from questionnaires and autism symptom severity. Thus, neural activations produced while thinking about other people's mental states predict variance in multiple indices of social functioning in the real world.

Structural connectivity and its association with social connectedness in early adolescence

Adolescence is a critical period of social and neural development. Brain regions which process social information develop throughout adolescence as young people learn to navigate social environments. Studies investigating brain structural connectivity (indexed by white matter (WM) integrity), and social connectedness in adolescents have been limited until recently, with literature stemming mostly from adult samples, broad age ranges within adolescence or based on social network characteristics as opposed to social connectedness. This cross-sectional study of 12-year-olds (N = 73) explored the relationship between social connectedness (SCS) and structural connectivity in early adolescence, to gauge how this snapshot of WM development is associated with social behaviour. Whole brain voxel-wise diffusion tensor imaging was undertaken to determine correlations between SCS and fractional anisotropy (FA), radial (RD) and axial (AD) diffusivity of clusters within WM tracts. Significant negative relationships between FA and SCS scores were found in clusters within 11 WM tracts, with significant positive correlations between SCS and both RD and AD across clusters within 13 and 8 clusters, respectively. Clusters within the genu of the corpus callosum (CCgn) showed strong correlations for all three metrics, and regression models that included gender, age, and psychological distress, revealed SCS to be the only significant predictor of CCgn FA, RD and AD values. Overall, these findings suggest that those with lower social connectedness had a WM profile suggestive of reduced axonal density and/or coherence. Longitudinal research is needed to track such WM profiles during adolescent development and determine the associations with mental health and well-being outcomes.

Connecting the dots: social networks in the classroom and white matter connections in the brain

BACKGROUND

Peer connections in school classrooms play an important role in social-emotional development and mental health. However, research on the association between children's peer relationships and white matter connections in the brain is scarce. We studied associations between peer relationships in the classroom and white matter structural connectivity in a pediatric population-based sample.

METHODS

Bullying and victimization, as well as rejection and acceptance, were assessed in classrooms in 634 children at age 7. White matter microstructure (fractional anisotropy (FA), mean diffusivity (MD)) was measured with diffusion tensor imaging at age 10. We examined global metrics of white matter microstructure and used Tract-Based Spatial Statistics (TBSS) for voxel-wise associations.

RESULTS

Peer victimization was associated with higher global FA and lower global MD and peer rejection was associated with lower global MD; however, these associations did not remain after multiple testing correction. Voxel-wise TBSS results for peer victimization and rejection were in line with global metrics both in terms of direction and spatial extent of the associations, with associated voxels (p_FWE  <.05) observed throughout the brain (including corpus callosum, corona radiata, sagittal stratum and superior longitudinal fasciculi).

CONCLUSIONS

Although based only on cross-sectional data, the findings could indicate accelerated white matter microstructure maturation in certain brain areas of children who are victimized or rejected more often. However, repeated measurements are essential to unravel this complex interplay of peer connections, maturation and brain development over time.

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.

Amygdala but not hippocampal damage associated with smaller social network size

Social network size has been associated with complex socio-cognitive processes (e.g., memory, perspective taking). Supporting this idea, recent neuroimaging studies in healthy adults have reported a relationship between social network size and brain volumes in regions related to memory and social cognition (e.g., hippocampus, amygdala). Lesion-deficit studies in neurological patients are rare and have been inconclusive due to differences in participant sampling and measurement. The present study uses a multiple case study approach. We investigated patients with focal damage to the hippocampus and/or amygdala (two neural structures thought to be critical for social networks), and examined the patients' social network size, loneliness, and life satisfaction relative to a non-injured comparison group. Patients with amygdalar damage had smaller social networks and reported higher levels of loneliness and lower life satisfaction, on average, than comparison participants. Patients with damage to the hippocampus reported more friends than the comparison participants, but did not differ in their ratings of loneliness or life satisfaction. This lesion study offers new evidence that the amygdala is critical for social networks, life satisfaction, and reduced loneliness.

Altered effective connectivity from the pregenual anterior cingulate cortex to the laterobasal amygdala mediates the relationship between internet gaming disorder and loneliness

BACKGROUND

Individual with internet gaming disorder (IGD) often experience a high level of loneliness, and neuroimaging studies have demonstrated that amygdala function is associated with both IGD and loneliness. However, the neurobiological basis underlying these relationships remains unclear.

METHODS

In the current study, Granger causal analysis was performed to investigate amygdalar subdivision-based resting-state effective connectivity differences between 111 IGD subjects and 120 matched participants with recreational game use (RGUs). We further correlated neuroimaging findings with clinical measures. Mediation analysis was conducted to explore whether amygdalar subdivision-based effective connectivity mediated the relationship between IGD severity and loneliness.

RESULTS

Compared with RGUs, IGD subjects showed inhibitory effective connections from the left pregenual anterior cingulate cortex (pACC) to the left laterobasal amygdala (LBA) and from the right medial prefrontal cortex (mPFC) to the left LBA, as well as an excitatory effective connection from the left middle prefrontal gyrus (MFG) to the right superficial amygdala. Further analyses demonstrated that the left pACC-left LBA effective connection was negatively correlated with both Internet Addiction Test and UCLA Loneliness scores, and it mediated the relationship between the two.

CONCLUSION

IGD subjects and RGUs showed different connectivity patterns involving amygdalar subdivisions. These findings support a neurobiological mechanism for the relationship between IGD and loneliness, and suggest targets for therapeutic approaches that could be used to treat IGD.

Amygdala connectivity and implications for social cognition and disorders

The amygdala is a hub of subcortical region that is crucial in a wide array of affective and motivation-related behaviors. While early research contributed significantly to our understanding of this region's extensive connections to other subcortical and cortical regions, recent methodological advances have enabled researchers to better understand the details of these circuits and their behavioral contributions. Much of this work has focused specifically on investigating the role of amygdala circuits in social cognition. In this chapter, we review both long-standing knowledge and novel research on the amygdala's structure, function, and involvement in social cognition. We focus specifically on the amygdala's circuits with the medial prefrontal cortex, the orbitofrontal cortex, and the hippocampus, as these regions share extensive anatomic and functional connections with the amygdala. Furthermore, we discuss how dysfunction in the amygdala may contribute to social deficits in clinical disorders including autism spectrum disorder, social anxiety disorder, and Williams syndrome. We conclude that social functions mediated by the amygdala are orchestrated through multiple intricate interactions between the amygdala and its interconnected brain regions, endorsing the importance of understanding the amygdala from network perspectives.

The Infertility Trap: The Fertility Costs of Group-Living in Mammalian Social Evolution

Mammal social groups vary considerably in size from single individuals to very large herds. In some taxa, these groups are extremely stable, with at least some individuals being members of the same group throughout their lives; in other taxa, groups are unstable, with membership changing by the day. We argue that this variability in grouping patterns reflects a tradeoff between group size as a solution to environmental demands and the costs created by stress-induced infertility (creating an infertility trap). These costs are so steep that, all else equal, they will limit group size in mammals to ∼15 individuals. A species will only be able to live in larger groups if it evolves strategies that mitigate these costs. We suggest that mammals have opted for one of two solutions. One option (fission-fusion herding) is low cost but high risk; the other (bonded social groups) is risk-averse, but costly in terms of cognitive requirements.

Brain Coding of Social Network Structure

Humans have large social networks, with hundreds of interacting individuals. How does the brain represent the complex connectivity structure of these networks? Here we used social media (Facebook) data to objectively map participants' real-life social networks. We then used representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) activity patterns to investigate the neural coding of these social networks as participants reflected on each individual. We found coding of social network distances in the default-mode network (medial prefrontal, medial parietal, and lateral parietal cortices). When using partial correlation RSA to control for other factors that can be correlated to social distance (personal affiliation, personality traits. and visual appearance, as subjectively rated by the participants), we found that social network distance information was uniquely coded in the retrosplenial complex, a region involved in spatial processing. In contrast, information on individuals' personal affiliation to the participants and personality traits was found in the medial parietal and prefrontal cortices, respectively. These findings demonstrate a cortical division between representations of non-self-referenced (allocentric) social network structure, self-referenced (egocentric) social distance, and trait-based social knowledge.SIGNIFICANCE STATEMENT Each of us has a social network composed of hundreds of individuals, with different characteristics and different relations among them. How does our brain represent this complexity? To find out, we mapped participants' social connections using Facebook data and then asked them to think about individuals from their network while undergoing functional MRI scanning. We found that the position of individuals within the social network, as well as their affiliation to the participant, are mapped in the retrosplenial complex, a region involved in spatial processing. Individuals' personality traits were coded in another region, the medial prefrontal cortex. Our findings demonstrate a neural dissociation among different aspects of social knowledge and suggest a link between spatial and social cognitive mapping.

Neurobiological Bases of Social Networks

A social network is a web that integrates multiple levels of interindividual social relationships and has direct associations with an individual’s health and well-being. Previous research has mainly focused on how brain and social network structures (structural properties) act on each other and on how the brain supports the spread of ideas and behaviors within social networks (functional properties). The structure of the social network is correlated with activity in the amygdala, which links decoding and interpreting social signals and social values. The structure also relies on the mentalizing network, which is central to an individual’s ability to infer the mental states of others. Network functional properties depend on multilayer brain-social networks, indicating that information transmission is supported by the default mode system, the valuation system, and the mentalizing system. From the perspective of neuroendocrinology, overwhelming evidence shows that variations in oxytocin, β-endorphin and dopamine receptor genes, including oxytocin receptor (OXTR), mu opioid receptor 1 (OPRM1) and dopamine receptor 2 (DRD2), predict an individual’s social network structure, whereas oxytocin also contributes to improved transmission of emotional and behavioral information from person to person. Overall, previous studies have comprehensively revealed the effects of the brain, endocrine system, and genes on social networks. Future studies are required to determine the effects of cognitive abilities, such as memory, on social networks, the characteristics and neural mechanism of social networks in mental illness and how social networks change over time through the use of longitudinal methods.

Social Cognition and White Matter: Connectivity and Cooperation

Humans are highly social animals whose survival and well-being depend on their capacity to cooperate in complex social settings. Advances in anthropology and psychology have demonstrated the importance of cooperation for enhancing social cohesion and minimizing conflict. The understanding of social behavior is informed by the notion of social cognition, a set of mental operations including emotion perception, mentalizing, and empathy. The social brain hypothesis posits that the mammalian brain has enlarged over evolution to meet the challenges of social life, culminating in a large human brain well adapted for social cognition. The structures subserving social cognition are mainly located in the frontal and temporal lobes, and although gray matter is critical, social cognition also requires white matter. Whereas the social brain hypothesis assumes that brain enlargement has been driven by neocortical expansion, cerebral white matter has expanded even more robustly than the neocortex, coinciding with the emergence of social cognition. White matter expansion is most evident in the frontal and temporal lobes, where it enhances connectivity between regions critical for social cognition. Myelination has, in turn, conferred adaptive social advantages by enabling prompt empathic concern for offspring and by strengthening networks that support cooperation and the related capacities of altruism and morality. Social cognition deficits related to myelinated tract involvement occur in many disorders, including stroke, Binswanger disease, traumatic brain injury, multiple sclerosis, glioma, and behavioral variant frontotemporal dementia. The contribution of white matter to social cognition can be conceptualized as the enhancement of cooperation through brain connectivity.

Network Neuroscience and the Adapted Mind: Rethinking the Role of Network Theories in Evolutionary Psychology

Evolutionary psychology is the comprehensive study of cognition and behavior in the light of evolutionary theory, a unifying paradigm integrating a huge diversity of findings across different levels of analysis. Since natural selection shaped the brain into a functionally organized system of interconnected neural structures rather than an aggregate of separate neural organs, the network-based account of anatomo-functional architecture is bound to yield the best mechanistic explanation for how the brain mediates the onset of evolved cognition and adaptive behaviors. While this view of a flexible and highly distributed organization of the brain is more than a century old, it was largely ignored up until recently. Technological advances are only now allowing this approach to find its rightful place in the scientific landscape. Historically, early network theories mostly relied on lesion studies and investigations on white matter circuitry, subject areas that still provide great empirical findings to this day. Thanks to new neuroimaging techniques, the traditional localizationist framework, in which any given cognitive process is thought to be carried out by its dedicated brain structure, is slowly being abandoned in favor of a network-based approach. We argue that there is a special place for network neuroscience in the upcoming quest for the biological basis of information-processing systems identified by evolutionary psychologists. By reviewing history of network theories, and by addressing several theoretical and methodological implications of this view for evolutionary psychologists, we describe the current state of knowledge about human neuroanatomy for those who wish to be mindful of both evolutionary and network neuroscience paradigms.

Structure and function in human and primate social networks: implications for diffusion, network stability and health

The human social world is orders of magnitude smaller than our highly urbanized world might lead us to suppose. In addition, human social networks have a very distinct fractal structure similar to that observed in other primates. In part, this reflects a cognitive constraint, and in part a time constraint, on the capacity for interaction. Structured networks of this kind have a significant effect on the rates of transmission of both disease and information. Because the cognitive mechanism underpinning network structure is based on trust, internal and external threats that undermine trust or constrain interaction inevitably result in the fragmentation and restructuring of networks. In contexts where network sizes are smaller, this is likely to have significant impacts on psychological and physical health risks.

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.

The fractal structure of communities of practice: Implications for business organization

Communities of practice (COP) are informal (sometimes formal) groupings of professionals with shared interests that form to facilitate the exchange of expertise and shared learning or to function as professional support networks. We analyse a dataset on the size of COPs and show that their distribution has a fractal structure similar to that found in huntergatherer social organisation and the structure of human personal social networks. Small communities up to about 40 in size can be managed democratically, but all larger communities require a leadership team structure. We show that frequency of interaction declines as size increases, as is the case in personal social networks. This suggests that professional work-oriented organisations may be subject to the same kinds of constraint imposed on human social organisation by the social brain. We discuss the implications for business management structure.

Amygdala activity related to perceived social support

Perceived social support enhances well-being and prevents stress-related ill-being. A recent structural neuroimaging study reported that the amygdala volume is positively associated with perceived social support. However, it remains unknown how neural activity in this region and functional connectivity (FC) between this and other regions are related to perceived social support. To investigate these issues, resting-state functional magnetic resonance imaging was performed to analyze the fractional amplitude of low-frequency fluctuation (fALFF). Perceived social support was evaluated using the Multidimensional Scale of Perceived Social Support (MSPSS). Lower fALFF values in the bilateral amygdalae were associated with higher MSPSS scores. Additionally, stronger FC between the left amygdala and right orbitofrontal cortex and between the left amygdala and bilateral precuneus were associated with higher MSPSS scores. The present findings suggest that reduced amygdala activity and heightened connectivity between the amygdala and other regions underlie perceived social support and its positive functions.

No strong evidence that social network index is associated with gray matter volume from a data-driven investigation

Recent studies in adult humans have reported correlations between individual differences in people's Social Network Index (SNI) and gray matter volume (GMV) across multiple regions of the brain. However, the cortical and subcortical loci identified are inconsistent across studies. These discrepancies might arise because different regions of interest were hypothesized and tested in different studies without controlling for multiple comparisons, and/or from insufficiently large sample sizes to fully protect against statistically unreliable findings. Here we took a data-driven approach in a pre-registered study to comprehensively investigate the relationship between SNI and GMV in every cortical and subcortical region, using three predictive modeling frameworks. We also included psychological predictors such as cognitive and emotional intelligence, personality, and mood. In a sample of healthy adults (n = 92), neither multivariate frameworks (e.g., ridge regression with cross-validation) nor univariate frameworks (e.g., univariate linear regression with cross-validation) showed a significant association between SNI and any GMV or psychological feature after multiple comparison corrections (all R-squared values ≤ .1). These results emphasize the importance of large sample sizes and hypothesis-driven studies to derive statistically reliable conclusions, and suggest that future meta-analyses will be needed to more accurately estimate the true effect sizes in this field.

The temporoinsular projection system: an anatomical study

OBJECTIVE

Connections between the insular cortex and the amygdaloid complex have been demonstrated using various techniques. Although functionally well connected, the precise anatomical substrate through which the amygdaloid complex and the insula are wired remains unknown. In 1960, Klingler briefly described the "fasciculus amygdaloinsularis," a white matter tract connecting the posterior insula with the amygdala. The existence of such a fasciculus seems likely but has not been firmly established, and the reported literature does not include a thorough description and documentation of its anatomy. In this fiber dissection study the authors sought to elucidate the pathway connecting the insular cortex and the mesial temporal lobe.

METHODS

Fourteen brain specimens obtained at routine autopsy were dissected according to Klingler's fiber dissection technique. After fixation and freezing, anatomical dissections were performed in a stepwise progressive fashion.

RESULTS

The insula is connected with the opercula of the frontal, parietal, and temporal lobes through the extreme capsule, which represents a network of short association fibers. At the limen insulae, white matter fibers from the extreme capsule converge and loop around the uncinate fasciculus toward the temporal pole and the mesial temporal lobe, including the amygdaloid complex.

CONCLUSIONS

The insula and the mesial temporal lobe are directly connected through white matter fibers in the extreme capsule, resulting in the appearance of a single amygdaloinsular fasciculus. This apparent fasciculus is part of the broader network of short association fibers of the extreme capsule, which connects the entire insular cortex with the temporal pole and the amygdaloid complex. The authors propose the term "temporoinsular projection system" (TIPS) for this complex.

Age-Related Structural Alterations in Human Amygdala Networks: Reflections on Correlations Between White Matter Structure and Effective Connectivity

The amygdala, which is involved in human social information processing and socio-emotional response neuronal circuits, is segmented into three subregions that are responsible for perception, affiliation, and aversion. Though there is different functional and effective connectivity (EC) among these networks, age-related structural changes and associations between structure and function within the amygdala remain unclear. Here, we used diffusion tensor imaging (DTI) data (106 participants) to investigate age-related structural changes in fractional anisotropy (FA) of amygdalar subregions. We also examined the relationship between FA and EC within the subregions. We found that the FA of the amygdalar subregions exhibited inverted-U-shape trends with age. Moreover, over the human lifespan, there were negative correlations between the FA of the right ventrolateral amygdala (VLA.R) and the Granger-based EC (GC) of VLA.R → perception network (PerN), the FA of the VLA.R and the GC of the net flow from VLA.R → PerN, and the FA of the left dorsal amygdala (DorA.L) and the GC of the aversion network (AveN). Conversely, there was a positive correlation between the FA of the DorA.L and the GC of the net flow from DorA.L → AveN. Our results suggest that age-related changes in the function of the brain are constrained by the underlying white matter architectures, while the functional information flow changes influence white matter structure. This work increases our understanding of the neuronal mechanisms in the maturation and aging process.

Causal Interactions in Human Amygdala Cortical Networks across the Lifespan

There is growing evidence that the amygdala serves as the base for dealing with complex human social communication and emotion. Although amygdalar networks plays a central role in these functions, causality connectivity during the human lifespan between amygdalar subregions and their corresponding perception network (PerN), affiliation network (AffN) and aversion network (AveN) remain largely unclear. Granger causal analysis (GCA), an approach to assess directed functional interactions from time series data, was utilized to investigated effective connectivity between amygdalar subregions and their related networks as a function of age to reveal the maturation and degradation of neural circuits during development and ageing in the present study. For each human resting functional magnetic resonance imaging (fMRI) dataset, the amygdala was divided into three subareas, namely ventrolateral amygdala (VLA), medial amygdala (MedA) and dorsal amygdala (DorA), by using resting-state functional connectivity, from which the corresponding networks (PerN, AffN and AveN) were extracted. Subsequently, the GC interaction of the three amygdalar subregions and their associated networks during life were explored with a generalised linear model (GLM). We found that three causality flows significantly varied with age: the GC of VLA → PerN showed an inverted U-shaped trend with ageing; the GC of MedA→ AffN had a U-shaped trend with ageing; and the GC of DorA→ AveN decreased with ageing. Moreover, during ageing, the above GCs were significantly correlated with Social Responsiveness Scale (SRS) and State-Trait Anxiety Inventory (STAI) scores. In short, PerN, AffN and AveN associated with the amygdalar subregions separately presented different causality connectivity changes with ageing. These findings provide a strong constituent framework for normal and neurological diseases associated with social disorders to analyse the neural basis of social behaviour during life.

Social brain volume is associated with in-degree social network size among older adults

The social brain hypothesis proposes that large neocortex size evolved to support cognitively demanding social interactions. Accordingly, previous studies have observed that larger orbitofrontal and amygdala structures predict the size of an individual's social network. However, it remains uncertain how an individual's social connectedness reported by other people is associated with the social brain volume. In this study, we found that a greater in-degree network size, a measure of social ties identified by a subject's social connections rather than by the subject, significantly correlated with a larger regional volume of the orbitofrontal cortex, dorsomedial prefrontal cortex and lingual gyrus. By contrast, out-degree size, which is based on an individual's self-perceived connectedness, showed no associations. Meta-analytic reverse inference further revealed that regional volume pattern of in-degree size was specifically involved in social inference ability. These findings were possible because our dataset contained the social networks of an entire village, i.e. a global network. The results suggest that the in-degree aspect of social network size not only confirms the previously reported brain correlates of the social network but also shows an association in brain regions involved in the ability to infer other people's minds. This study provides insight into understanding how the social brain is uniquely associated with sociocentric measures derived from a global network.

Neuroimaging Studies Reveal the Subtle Difference Among Social Network Size Measurements and Shed Light on New Directions

Social network size is a key feature when we explore the constructions of human social networks. Despite the disparate understanding of individuals’ social networks, researchers have reached a consensus that human’s social networks are hierarchically organized with different layers, which represent emotional bonds and interaction frequency. Social brain hypothesis emphasizes the significance of complex and demanding social interaction environments and assumes that the cognitive constraints may have an impact on the social network size. This paper reviews neuroimaging studies on social networks that explored the connection between individuals’ social network size and neural mechanisms and finds that Social Network Index (SNI) and Social Network Questionnaires (SNQs) are the mostly-adopted measurements of one’s social network size. The two assessments have subtle difference in essence as they measure the different sublayers of one’s social network. The former measures the relatively outer sub-layer of one’s stable social relationship, similar to the sympathy group, while the latter assesses the innermost layer—the core of one’s social network, often referred to as support clique. This subtle difference is also corroborated by neuroimaging studies, as SNI-measured social network size is largely correlated with the amygdala, while SNQ-assessed social network size is closely related to both the amygdala and the orbitofrontal cortex. The two brain regions respond to disparate degrees of social closeness, respectively. Finally, it proposes a careful choice among the measurements for specific purposes and some new approaches to assess individuals’ social network size.

White matter pathways and social cognition

There is a growing consensus that social cognition and behavior emerge from interactions across distributed regions of the "social brain". Researchers have traditionally focused their attention on functional response properties of these gray matter networks and neglected the vital role of white matter connections in establishing such networks and their functions. In this article, we conduct a comprehensive review of prior research on structural connectivity in social neuroscience and highlight the importance of this literature in clarifying brain mechanisms of social cognition. We pay particular attention to three key social processes: face processing, embodied cognition, and theory of mind, and their respective underlying neural networks. To fully identify and characterize the anatomical architecture of these networks, we further implement probabilistic tractography on a large sample of diffusion-weighted imaging data. The combination of an in-depth literature review and the empirical investigation gives us an unprecedented, well-defined landscape of white matter pathways underlying major social brain networks. Finally, we discuss current problems in the field, outline suggestions for best practice in diffusion-imaging data collection and analysis, and offer new directions for future research.

The neural representation of social networks

The computational demands associated with navigating large, complexly bonded social groups are thought to have significantly shaped human brain evolution. Yet, research on social network representation and cognitive neuroscience have progressed largely independently. Thus, little is known about how the human brain encodes the structure of the social networks in which it is embedded. This review highlights recent work seeking to bridge this gap in understanding. While the majority of research linking social network analysis and neuroimaging has focused on relating neuroanatomy to social network size, researchers have begun to define the neural architecture that encodes social network structure, cognitive and behavioral consequences of encoding this information, and individual differences in how people represent the structure of their social world.

The Original Social Network: White Matter and Social Cognition

Social neuroscience has traditionally focused on the functionality of gray matter regions, ignoring the critical role played by axonal fiber pathways in supporting complex social processes. In this paper, we argue that research on white matter is essential for understanding a range of topics in social neuroscience, such as face processing, theory of mind, empathy, and imitation, as well as clinical disorders defined by aberrant social behavior, such as prosopagnosia, autism, and schizophrenia. We provide practical advice on how best to carry out these studies, which ultimately will substantially deepen our understanding of the neurobiological basis of social behavior.

Social network size relates to developmental neural sensitivity to biological motion

The ability to perceive others' actions and goals from human motion (i.e., biological motion perception) is a critical component of social perception and may be linked to the development of real-world social relationships. Adult research demonstrates two key nodes of the brain's biological motion perception system-amygdala and posterior superior temporal sulcus (pSTS)-are linked to variability in social network properties. The relation between social perception and social network properties, however, has not yet been investigated in middle childhood-a time when individual differences in social experiences and social perception are growing. The aims of this study were to (1) replicate past work showing amygdala and pSTS sensitivity to biological motion in middle childhood; (2) examine age-related changes in the neural sensitivity for biological motion, and (3) determine whether neural sensitivity for biological motion relates to social network characteristics in children. Consistent with past work, we demonstrate a significant relation between social network size and neural sensitivity for biological motion in left pSTS, but do not find age-related change in biological motion perception. This finding offers evidence for the interplay between real-world social experiences and functional brain development and has important implications for understanding disorders of atypical social experience.

The structural and functional brain networks that support human social networks

Social skills rely on a specific set of cognitive processes, raising the possibility that individual differences in social networks are related to differences in specific brain structural and functional networks. Here, we tested this hypothesis with multimodality neuroimaging. With diffusion MRI (DMRI), we showed that differences in structural integrity of particular white matter (WM) tracts, including cingulum bundle, extreme capsule and arcuate fasciculus were associated with an individual's social network size (SNS). A voxel-based morphology analysis demonstrated correlations between gray matter (GM) volume and SNS in limbic and temporal lobe regions. These structural changes co-occured with functional network differences. As a function of SNS, dorsomedial and dorsolateral prefrontal cortex showed altered resting-state functional connectivity with the default mode network (DMN). Finally, we integrated these three complementary methods, interrogating the relationship between social GM clusters and specific WM and resting-state networks (RSNs). Probabilistic tractography seeded in these GM nodes utilized the SNS-related WM pathways. Further, the spatial and functional overlap between the social GM clusters and the DMN was significantly closer than other control RSNs. These integrative analyses provide convergent evidence of the role of specific circuits in SNS, likely supporting the adaptive behavior necessary for success in extensive social environments.

Multistability of the Brain Network for Self-other Processing

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information.

Characterization of Face-Selective Patches in Orbitofrontal Cortex

Face processing involves a complex, multimodal brain network. While visual-perceptual face patches in posterior parts of the brain have been studied for over a decade, the existence and properties of face-selective regions in orbitofrontal cortex (OFC) is a relatively new area of research. While regions of OFC are implicated in the emotional processing of faces, this is typically interpreted as a domain-general response to affective value rather than a face- or socially-specific response. However, electrophysiology studies in monkeys have identified neurons in OFC that respond more to faces than any other stimuli. Here, we characterize the prevalence and location of OFC face-selective regions in 20 healthy college students. We did this by including another biologically motivating category (appetizing foods) in a variant of the standard face localizer. Results show that face-selective patches can be identified at the individual level. Furthermore, in both a region of interest (ROI) and a whole brain analysis, medial regions of the OFC were face-selective, while lateral regions were responsive to faces and foods, indicating a domain-general response in lateral OFC. Medial OFC (mOFC) response to faces scales in relationship to a measure of social motivation that is distinct from face processing abilities associated with fusiform cortex.