Causal interactions in resting-state networks predict perceived loneliness

Loneliness and brain rhythmic activity in resting state: an exploratory report

Recent studies using resting-state functional magnetic resonance imaging have shown that loneliness is associated with altered blood oxygenation in several brain regions. However, the relationship between loneliness and changes in neuronal rhythm activity in the brain remains unclear. To evaluate brain rhythm, we conducted an exploratory resting-state electroencephalogram (EEG) study of loneliness. We recorded resting-state EEG signals from 139 participants (94 women; mean age = 19.96 years) and analyzed power spectrum density (PSD) and functional connectivity (FC) in both the electrode and source spaces. The PSD analysis revealed significant correlations between loneliness scores and decreased beta-band powers, which may indicate negative emotion, attention, reward, and/or sensorimotor processing. The FC analysis revealed a trend of alpha-band FC associated with individuals' loneliness scores. These findings provide new insights into the neural basis of loneliness, which will facilitate the development of neurobiologically informed interventions for loneliness.

Social Isolation, Brain Food Cue Processing, Eating Behaviors, and Mental Health Symptoms

Importance

Perceived social isolation is associated with negative health outcomes, including increased risk for altered eating behaviors, obesity, and psychological symptoms. However, the underlying neural mechanisms of these pathways are unknown.

Objective

To investigate the association of perceived social isolation with brain reactivity to food cues, altered eating behaviors, obesity, and mental health symptoms.

Design, Setting, and Participants

This cross-sectional, single-center study recruited healthy, premenopausal female participants from the Los Angeles, California, community from September 7, 2021, through February 27, 2023.

Exposure

Participants underwent functional magnetic resonance imaging while performing a food cue viewing task.

Main Outcomes and Measures

The main outcomes included brain reactivity to food cues, body composition, self-reported eating behaviors (food cravings, reward-based eating, food addiction, and maladaptive eating behaviors), and mental health symptoms (anxiety, depression, positive and negative affect, and psychological resilience).

Results

The study included 93 participants (mean [SD] age, 25.38 [7.07] years). Participants with higher perceived social isolation reported higher fat mass percentage, lower diet quality, increased maladaptive eating behaviors (cravings, reward-based eating, uncontrolled eating, and food addiction), and poor mental health (anxiety, depression, and psychological resilience). In whole-brain comparisons, the higher social isolation group showed altered brain reactivity to food cues in regions of the default mode, executive control, and visual attention networks. Isolation-related neural changes in response to sweet foods correlated with various altered eating behaviors and psychological symptoms. These altered brain responses mediated the connection between social isolation and maladaptive eating behaviors (β for indirect effect, 0.111; 95% CI, 0.013-0.210; P = .03), increased body fat composition (β, -0.141; 95% CI, -0.260 to -0.021; P = .02), and diminished positive affect (β, -0.089; 95% CI, -0.188 to 0.011; P = .09).

Conclusions and Relevance

These findings suggest that social isolation is associated with altered neural reactivity to food cues within specific brain regions responsible for processing internal appetite-related states and compromised executive control and attentional bias and motivation toward external food cues. These neural responses toward specific foods were associated with an increased risk for higher body fat composition, worsened maladaptive eating behaviors, and compromised mental health. These findings underscore the need for holistic mind-body-directed interventions that may mitigate the adverse health consequences of social isolation.

Away from the herd: loneliness as a dysfunction of social alignment

The tendency of all humans to experience loneliness at some point in their lives implies that it serves an adaptive function. Building on biological theories of herding in animals, according to which collective movement emerges from local interactions that are based on principles of attraction, repulsion and alignment, we propose an approach that synthesizes these principles with theories of loneliness in humans. We present here the 'herding model of loneliness' that extends these principles into the psychological domain. We hold that these principles serve as basic building blocks of human interactions and propose that distorted attraction and repulsion tendencies may lead to inability to align properly with others, which may be a core component in loneliness emergence and perpetuation. We describe a neural model of herding in humans and suggest that loneliness may be associated with altered interactions between the gap/error detection, reward signaling, threat and observation-execution systems. The proposed model offers a framework to predict the behavior of lonely individuals and thus may inform intervention designs for reducing loneliness intensity.

Top-down modulation of DLPFC in visual search: a study based on fMRI and TMS

Effective visual search is essential for daily life, and attention orientation as well as inhibition of return play a significant role in visual search. Researches have established the involvement of dorsolateral prefrontal cortex in cognitive control during selective attention. However, neural evidence regarding dorsolateral prefrontal cortex modulates inhibition of return in visual search is still insufficient. In this study, we employed event-related functional magnetic resonance imaging and dynamic causal modeling to develop modulation models for two types of visual search tasks. In the region of interest analyses, we found that the right dorsolateral prefrontal cortex and temporoparietal junction were selectively activated in the main effect of search type. Dynamic causal modeling results indicated that temporoparietal junction received sensory inputs and only dorsolateral prefrontal cortex →temporoparietal junction connection was modulated in serial search. Such neural modulation presents a significant positive correlation with behavioral reaction time. Furthermore, theta burst stimulation via transcranial magnetic stimulation was utilized to modulate the dorsolateral prefrontal cortex region, resulting in the disappearance of the inhibition of return effect during serial search after receiving continuous theta burst stimulation. Our findings provide a new line of causal evidence that the top-down modulation by dorsolateral prefrontal cortex influences the inhibition of return effect during serial search possibly through the retention of inhibitory tagging via working memory storage.

Loneliness is related to smaller gray matter volumes in ACC and right VLPFC in people with major depression: a UK biobank study

The anterior cingulate cortex (ACC) and right ventrolateral prefrontal cortex (VLPFC) are thought to have important roles in loneliness (feeling of social isolation/exclusion) experience or regulation and in the pathophysiology of their disturbance in major depressive disorder (MDD). However, the structural abnormalities of these regions and the correlates with loneliness in MDD across the healthy population have not fully been clarified. The study analyzed the link between loneliness and gray matter volumes (GMVs) in the ACC and right VLPFC among 1,005 patients with MDD and 7,247 healthy controls (HCs) using UK Biobank data. Significant reductions in GMV in the right VLPFC were found in MDD males compared to HCs. MDD males also showed a higher association between loneliness and reduced GMVs in the right VLPFC and bilateral ACC than HCs. No such associations were found in MDD females. The findings suggest that loneliness may influence brain structures crucial for emotion experience and regulation, particularly in middle-older aged men with MDD. This highlights the potential adverse effects of loneliness on brain structure in MDD and suggests that social engagement could have a positive impact.

The positive and negative emotion functions related to loneliness: a systematic review of behavioural and neuroimaging studies

Loneliness is associated with high prevalences of major psychiatric illnesses such as major depression. However, the underlying emotional mechanisms of loneliness remained unclear. We hypothesized that loneliness originates from both decreases in positive emotional processing and increases in negative emotion processing. To test this, we conducted a systematic review of 29 previous studies (total participants n = 19 560, mean age = 37.16 years, female proportion = 59.7%), including 18 studies that included questionnaire measures of emotions only, and 11 studies that examined the brain correlates of emotions. The main findings were that loneliness was negatively correlated with general positive emotions and positively correlated with general negative emotions. Furthermore, limited evidence indicates loneliness exhibited negative and positive correlations with the brain positive (e.g. the striatum) and negative (e.g. insula) emotion systems, respectively, but the sign of correlation was not entirely consistent. Additionally, loneliness was associated with the structure and function of the brain emotion regulation systems, particularly the prefrontal cortex, but the direction of this relationship remained ambiguous. We concluded that the existing evidence supported a bivalence model of loneliness, but several critical gaps existed that could be addressed by future studies that include adolescent and middle-aged samples, use both questionnaire and task measures of emotions, distinguish between general emotion and social emotion as well as between positive and negative emotion regulation, and adopt a longitudinal design that allows us to ascertain the causal relationships between loneliness and emotion dysfunction. Our findings provide new insights into the underlying emotion mechanisms of loneliness that can inform interventions for lonely individuals.

Functional integration of anterior insula related to meaning in life and loneliness

BACKGROUND

Meaning in life (MIL), defined as people's feelings of life's meaningfulness, plays a vital role in buffering loneliness - an important indicator of depression and other psychological disorders. Considerable evidence shows that MIL arises from widely distributed brain activity; however, how such activity is functionally integrated and how it influences loneliness is still understudied.

METHODS

We here examined how the functional integration of brain regions is related to individual MIL based on resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 970).

RESULTS

We found that the global brain connectivity (GBC) of the right anterior insula (rAI) can significantly predict individual MIL. Moreover, mediation analyses were conducted to investigate how the brain influences loneliness with MIL's mediation, which revealed that MIL fully mediates the effect of this hub on loneliness.

CONCLUSIONS

These findings suggest that the rAI is a key hub for MIL and loneliness. Its functional integration can be used as a biomarker to predict individual MIL and loneliness.

Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game

Objective. The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer's decision-making is a crucial issue. Yet the neural substrate of the proposer's decision behavior, especially from the resting-state network perspective, remains unclear.Approach. In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers' unfair offer rates in the ultimatum game.Main results.The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors.Significance. Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.

Exposure to loneliness cues reduces prosocial behavior: Evidence from N400 and P300

Loneliness is a major risk factor for morbidity and mortality. However, the effect of loneliness on subsequent prosocial behavior is not well known. Understanding the neurobiological mechanisms underlying loneliness is necessary to address this research gap. We investigate the mechanism using a modified public goods game (PGG) wherein participants can choose to act for a collective or selfish interest after being exposed to loneliness cues. Both behavioral (Study 1) and event-related potential (ERP) (Study 2) measures were used to explore this relationship. In Study 1 (N = 131), we found that participants exhibited decreased prosocial actions under the loneliness priming condition as opposed to the control condition. In Study 2 (N = 17), frontal N400 and posterior P300 components were identified under the loneliness priming condition as opposed to the control condition. Increased (decreased) frontal N400 and posterior P300 lead to selfish (prosocial) choices. These results indicate that humans instinctively perceive loneliness as inconsistency with their desired social-relational life, which in turn stimulates coping strategies for self-preservation. This study contributes to our understanding of the neurobiological basis of loneliness associated with prosocial behavior.

EEG emotion recognition based on cross-frequency granger causality feature extraction and fusion in the left and right hemispheres

EEG emotion recognition based on Granger causality (GC) brain networks mainly focus on the EEG signal from the same-frequency bands, however, there are still some causality relationships between EEG signals in the cross-frequency bands. Considering the functional asymmetric of the left and right hemispheres to emotional response, this paper proposes an EEG emotion recognition scheme based on cross-frequency GC feature extraction and fusion in the left and right hemispheres. Firstly, we calculate the GC relationship of EEG signals according to the frequencies and hemispheres, and mainly focus on the causality of the cross-frequency EEG signals in left and right hemispheres. Then, to remove the redundant connections of the GC brain network, an adaptive two-stage decorrelation feature extraction scheme is proposed under the condition of maintaining the best emotion recognition performance. Finally, a multi-GC feature fusion scheme is designed to balance the recognition accuracy and feature number of each GC feature, which comprehensively considers the influence of the recognition accuracy and computational complexity. Experimental results on the DEAP emotion dataset show that the proposed scheme can achieve an average accuracy of 84.91% for four classifications, which improved the classification accuracy by up to 8.43% compared with that of the traditional same-frequency band GC features.

Meta-analytic evidence for the cognitive control model of loneliness in emotion processing

Loneliness is strongly related to affective dysregulation. However, the neuropsychological mechanisms underpinning the loneliness-affective processing relationships remain unclear. Here, we first utilised the coordinate-based activation likelihood estimation method to confirm functional clusters related to loneliness, including the striatum, superior and medial frontal gyrus, insula, and cuneus. Meta-analytic connectivity modelling was then performed to characterise the functional connectivity of these clusters across studies using emotion tasks. Our results revealed that these clusters co-activated with the cognitive control networks. From the literature, we understand that loneliness and its neural correlates are highly related to regulating the attention biases to social rewards and social cues. Therefore, our findings provide a proof-of-concept that loneliness up-regulates the cognitive control networks to process socio-affective information. Prolonged up-regulation thus exhausts cognitive resources and hence, affective dysregulation. This study offers insight into the intricate role of cognitive and affective regulation in loneliness and social perception and provides meta-analytic evidence of the cognitive control model of loneliness and loneliness-related affective dysregulation, bringing significant clinical implications.

A Narrative Review of Loneliness and Brain Health in Older Adults: Implications of COVID-19

Purpose of Review

This narrative review highlights important factors contributing to loneliness in older adults prior to and during the COVID-19 pandemic and effects on brain health.

Recent Findings

We characterize risk factors for loneliness in older adulthood and the impact of COVID-19. Furthermore, we discuss the implications of loneliness for older adults’ brain health.

Summary

Understanding the multifactorial causes of loneliness in different subpopulations of older adults both before and during the COVID-19 pandemic will provide insights for the development of interventions targeted to reduce loneliness in older adults based on their specific risk factors.

Loneliness inside of the brain: evidence from a large dataset of resting-state fMRI in young adult

Although loneliness itself is a natural emotion, prolonged loneliness is detrimental to human health. Despite its detrimental effect, few loneliness-related neuroimaging studies have been published and some have limitations on the sample size number. This study aims to find the difference in resting-state functional connectivity associated with loneliness within a big sample size via the seed-based approach. Functional connectivity analysis was performed on a large cohort of young adults (N = 1336) using the seed-based functional connectivity approach to address the concern from previous studies. The analysis yielded statistically significant positive correlations between loneliness and functional connectivities between the inferior frontal gyrus and supplementary motor area, precentral gyrus, and superior parietal lobule. Additionally, the analysis replicated a finding from a previous study, which is increased functional connectivities between the inferior frontal gyrus and supplementary motor area. In conclusion, greater loneliness is reflected by stronger functional connectivity of the visual attention brain area.

Resting-state functional connectivity of social brain regions predicts motivated dishonesty

Motivated dishonesty is a typical social behavior varying from person to person. Resting-state fMRI (rsfMRI) is capable of identifying unique patterns from functional connectivity (FC) between brain regions. Recent work has built a link between brain networks in resting state to dishonesty in Western participants. To determine and reproduce the relevant neural patterns and build an interpretable model to predict dishonesty, we analyzed two conceptually similar datasets containing rsfMRI data with different dishonesty tasks. Both tasks implemented the information-passing paradigm, in which monetary rewards were employed to induce dishonesty. We applied connectome-based predictive modeling (CPM) to build a model among FC within and between four social brain networks (reward, self-referential, moral, and cognitive control). The CPM analysis indicated that FCs of social brain networks are predictive of dishonesty rate, especially FCs within reward network, and between self-referential and cognitive control networks. Our study offers an conceptual replication with integrated model to predict dishonesty with rsfMRI, and the results suggest that frequent motivated dishonest decisions may require the higher engagement of social brain regions.

Affective Neuroscience of Loneliness: Potential Mechanisms underlying the Association between Perceived Social Isolation, Health, and Well-Being

Loneliness, or the subjective feeling of social isolation, is an important social determinant of health. Loneliness is associated with poor physical health, including higher rates of cardiovascular disease and dementia, faster cognitive decline, and increased risk of mortality, as well as disruptions in mental health, including higher levels of depression, anxiety, and negative affect. Theoretical accounts suggest loneliness is a complex cognitive and emotional state characterized by increased levels of inflammation and affective disruptions. This review examines affective neuroscience research on social isolation in animals and loneliness in humans to better understand the relationship between perceptions of social isolation and the brain. Loneliness associated increases in inflammation and neural changes consistent with increased sensitivity to social threat and disrupted emotion regulation suggest interventions targeting maladaptive social cognitions may be especially effective. Work in animal models suggests the neural changes associated with social isolation may be reversible. Therefore, ameliorating loneliness may be an actionable social determinant of health target. However, more research is needed to understand how loneliness impacts healthy aging, explore the role of inflammation as a potential mechanism in humans, and determine the best time to deliver interventions to improve physical health, mental health, and well-being across a diverse array of populations.

Individual Differences in Cerebral Perfusion as a Function of Age and Loneliness

Loneliness is defined as the subjective feeling that one's social needs are not satisfied by both quantity and quality of one's social relationships. Loneliness has been linked to a broad range of adverse physical and mental health consequences. There is an interest in identifying the neural and molecular processes by which loneliness adversely affects health. Prior imaging studies reported divergent networks involved in cognitive, emotional, and social processes associated with loneliness. Although loneliness is common among both younger and older adults, it is experienced differently across the lifespan and has different antecedents and consequences. The current study measured regional cerebral blood flow (CBF) using pulsed arterial spin labeling imaging. Forty-five older (M_age = 63.4) and forty-four younger adults (M_age = 20.9) with comparable degrees of loneliness were included. Whole-brain voxel-wise analysis revealed a main effect of age (in superior temporal and supramarginal gyri), but no main effect of loneliness. Furthermore, the age effect was only observed among people who reported higher level of loneliness. These regions have previously been implicated in social- and attention-related functions. The moderation of loneliness on age and regional CBF suggests that younger and older individuals present differential neural manifestations in response to loneliness, even with comparable levels of loneliness.

Neurobiology of loneliness: a systematic review

Loneliness is associated with increased morbidity and mortality. Deeper understanding of neurobiological mechanisms underlying loneliness is needed to identify potential intervention targets. We did not find any systematic review of neurobiology of loneliness. Using MEDLINE and PsycINFO online databases, we conducted a search for peer-reviewed publications examining loneliness and neurobiology. We identified 41 studies (n = 16,771 participants) that had employed various methods including computer tomography (CT), structural magnetic resonance imaging (MRI), functional MRI (fMRI), electroencephalography (EEG), diffusion tensor imaging (DTI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and post-mortem brain tissue RNA analysis or pathological analysis. Our synthesis of the published findings shows abnormal structure (gray matter volume or white matter integrity) and/or activity (response to pleasant versus stressful images in social versus nonsocial contexts) in the prefrontal cortex (especially medial and dorsolateral), insula (particularly anterior), amygdala, hippocampus, and posterior superior temporal cortex. The findings related to ventral striatum and cerebellum were mixed. fMRI studies reported links between loneliness and differential activation of attentional networks, visual networks, and default mode network. Loneliness was also related to biological markers associated with Alzheimer's disease (e.g., amyloid and tau burden). Although the published investigations have limitations, this review suggests relationships of loneliness with altered structure and function in specific brain regions and networks. We found a notable overlap in the regions involved in loneliness and compassion, the two personality traits that are inversely correlated in previous studies. We have offered recommendations for future research studies of neurobiology of loneliness.

Brain variability in dynamic resting-state networks identified by fuzzy entropy: a scalp EEG study

Objective.Exploring the temporal variability in spatial topology during the resting state attracts growing interest and becomes increasingly useful to tackle the cognitive process of brain networks. In particular, the temporal brain dynamics during the resting state may be delineated and quantified aligning with cognitive performance, but few studies investigated the temporal variability in the electroencephalogram (EEG) network as well as its relationship with cognitive performance.Approach.In this study, we proposed an EEG-based protocol to measure the nonlinear complexity of the dynamic resting-state network by applying the fuzzy entropy. To further validate its applicability, the fuzzy entropy was applied into simulated and two independent datasets (i.e. decision-making and P300).Main results.The simulation study first proved that compared to the existing methods, this approach could not only exactly capture the pattern dynamics in time series but also overcame the magnitude effect of time series. Concerning the two EEG datasets, the flexible and robust network architectures of the brain cortex at rest were identified and distributed at the bilateral temporal lobe and frontal/occipital lobe, respectively, whose variability metrics were found to accurately classify different groups. Moreover, the temporal variability of resting-state network property was also either positively or negatively related to individual cognitive performance.Significance.This outcome suggested the potential of fuzzy entropy for evaluating the temporal variability of the dynamic resting-state brain networks, and the fuzzy entropy is also helpful for uncovering the fluctuating network variability that accounts for the individual decision differences.

Neuroimaging studies exploring the neural basis of social isolation

According to the social brain hypothesis, the human brain includes a network designed for the processing of social information. This network includes several brain regions that elaborate social cues, interactions and contexts, i.e. prefrontal paracingulate and parietal cortices, amygdala, temporal lobes and the posterior superior temporal sulcus. While current literature suggests the importance of this network from both a psychological and evolutionary perspective, little is known about its neurobiological bases. Specifically, only a paucity of studies explored the neural underpinnings of constructs that are ascribed to the social brain network functioning, i.e. objective social isolation and perceived loneliness. As such, this review aimed to overview neuroimaging studies that investigated social isolation in healthy subjects. Social isolation correlated with both structural and functional alterations within the social brain network and in other regions that seem to support mentalising and social processes (i.e. hippocampus, insula, ventral striatum and cerebellum). However, results are mixed possibly due to the heterogeneity of methods and study design. Future neuroimaging studies with longitudinal designs are needed to measure the effect of social isolation in experimental v. control groups and to explore its relationship with perceived loneliness, ultimately helping to clarify the neural correlates of the social brain.

The Influence of Listening to Music on Adults with Left-behind Experience Revealed by EEG-based Connectivity

The human brain has a close relationship with music. Music-induced structural and functional brain changes have been demonstrated in the healthy adult. In the present study, adults with left-behind experience (ALB) were divided into two groups. The experimental group (ALB-E) took part in the music therapy experiment with three stages, including before listening to music (pre-stage), initially listening to music (mid-stage) and after listening to music (post-stage). The control group (ALB-C) did not participate in music therapy. Scalp resting-state EEGs of ALB were recorded during the three stages. We found no significant frequency change in the ALB-C group. In the ALB-E group, only the theta power spectrum was significantly different at all stages. The topographical distributions of the theta power spectrum represented change in trends from the frontal regions to the occipital regions. The result of Granger causal analysis (GCA), based on theta frequency, showed a stronger information flow from the middle frontal gyrus to the middle temporal gyrus (MFG → MTG) in the left hemisphere at the pre-stage compared to the post-stage. Additionally, the experimental group showed a weaker information flow from inferior gyrus to superior temporal gyrus (IFG → STG) in the right hemisphere at post-test stage compared to the ALB-C group. Our results demonstrate that listening to music can play a positive role on improving negative feelings for individuals with left behind experience.

Loneliness and meaning in life are reflected in the intrinsic network architecture of the brain

Social relationships imbue life with meaning, whereas loneliness diminishes one's sense of meaning in life. Yet the extent of interdependence between these psychological constructs remains poorly understood. We took a multivariate network approach to examine resting-state fMRI functional connectivity’s association with loneliness and meaning in a large cohort of adults (N = 942). Loneliness and meaning in life were negatively correlated with one another. In their relationship with individually parcelled whole-brain measures of functional connectivity, a significant and reliable pattern was observed. Greater loneliness was associated with dense, and less modular, connections between default, frontoparietal, attention and perceptual networks. A greater sense of life meaning was associated with increased, and more modular, connectivity between default and limbic networks. Low loneliness was associated with more modular brain connectivity, and lower life meaning was associated with higher between-network connectivity. These findings advance our understanding of loneliness and life meaning as distinct, yet interdependent, features of sociality. The results highlight a potential role of the default network as a central hub, providing a putative neural mechanism for shifting between feelings of isolation and purpose.

Connectome-based individualized prediction of loneliness

Loneliness is an increasingly prevalent condition linking with enhanced morbidity and premature mortality. Despite recent proposal on medicalization of loneliness, so far no effort has been made to establish a model capable of predicting loneliness at the individual level. Here, we applied a machine-learning approach to decode loneliness from whole-brain resting-state functional connectivity (RSFC). The relationship between whole-brain RSFC and loneliness was examined in a linear predictive model. The results revealed that individual loneliness could be predicted by within- and between-network connectivity of prefrontal, limbic and temporal systems, which are involved in cognitive control, emotional processing and social perceptions and communications, respectively. Key nodes that contributed to the prediction model comprised regions previously implicated in loneliness, including the dorsolateral prefrontal cortex, lateral orbital frontal cortex, ventromedial prefrontal cortex, caudate, amygdala and temporal regions. Our findings also demonstrated that both loneliness and associated neural substrates are modulated by levels of neuroticism and extraversion. The current data-driven approach provides the first evidence on the predictive brain features of loneliness based on organizations of intrinsic brain networks. Our work represents initial efforts in the direction of making individualized prediction of loneliness that could be useful for diagnosis, prognosis and treatment.

Negative Affect Shared with Siblings is Associated with Structural Brain Network Efficiency and Loneliness in Adolescents

Loneliness has a strong neurobiological basis reflected by its specific relationships with structural brain connectivity. Critically, affect traits are highly related to loneliness, which shows close association with the onset and severity of major depressive disorder. This diffusion imaging study was conducted on a sample of adolescent siblings to examine whether positive and negative affect traits were related to loneliness, with brain network efficiency playing a mediating role. The findings of this study confirmed that both global and average local efficiency negatively mediated the association between low positive affect and high negative affect and loneliness, and the mediation was more sensitive to sibling-shared affect traits. The findings have important implications for interventions targeted at reducing the detrimental impact of familiar negative emotional experiences and loneliness.

Structural Brain Correlates of Loneliness among Older Adults

Ample evidence indicates that loneliness in old age is associated with poor bodily and mental health. However, little is known about structural cerebral correlates of loneliness in healthy older adults. We examined such correlates in a magnetic resonance imaging (MRI) subsample of 319 older adults aged 61 to 82 years drawn from the Berlin Aging Study II. Using voxel-based morphometry (VBM) and structural equation modeling (SEM), latent hierarchical regression analyses were performed to examine associations of (i) loneliness, (ii) a range of covariates, and (iii) loneliness by covariate interactions with latent brain volume estimates of brain structures known to be involved in processing, expressing, and regulating emotions. Results from whole-brain VBM analyses showed that individuals with higher loneliness scores tended to have smaller gray matter volumes in three clusters comprising (i) the left amygdala/anterior hippocampus, (ii) the left posterior parahippocampus and (iii) the left cerebellum. Significant associations and interactions between loneliness and latent factors for the amygdala and the hippocampus were confirmed with a region-of-interest (ROI)-based approach. These findings suggest that individual differences in loneliness among older adults are correlated with individual differences in the volumes of brain regions that are central to cognitive processing and emotional regulation, also after correcting for confounders such as social network size. We discuss possible mechanisms underlying these associations and their implications.

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.

Interest of neuroimaging of social exclusion in suicide

With one million deaths worldwide, suicide is a major health issue. The frequency of life events preceding suicidal act is high and raises the question of their role in suicidal process. At biological level, dysfunctional neural processing of social exclusion may participate in suicidal risk through an increased perception of social adversity in vulnerable subjects. The purpose of this narrative review is to discuss neuroimaging findings related to social exclusion and loneliness, and to open new perspectives to investigate sensitivity to social stress in suicide.