Anxious personality and functional efficiency of the insular-opercular network: A graph-analytic approach to resting-state fMRI

Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability

We propose that the application of network theory to established psychological personality conceptions has great potential to advance a biologically plausible model of human personality. Stable behavioral tendencies are conceived as personality “traits.” Such traits demonstrate considerable variability between individuals, and extreme expressions represent risk factors for psychological disorders. Although the psychometric assessment of personality has more than hundred years tradition, it is not yet clear whether traits indeed represent “biophysical entities” with specific and dissociable neural substrates. For instance, it is an open question whether there exists a correspondence between the multilayer structure of psychometrically derived personality factors and the organizational properties of traitlike brain systems. After a short introduction into fundamental personality conceptions, this article will point out how network neuroscience can enhance our understanding about human personality. We will examine the importance of intrinsic (task-independent) brain connectivity networks and show means to link brain features to stable behavioral tendencies. Questions and challenges arising from each discipline itself and their combination are discussed and potential solutions are developed. We close by outlining future trends and by discussing how further developments of network neuroscience can be applied to personality research.

Whole-Brain Resting-State Functional Connectivity Patterns Associated With Pediatric Anxiety and Involuntary Attention Capture

BACKGROUND

Pediatric anxiety disorders are linked to dysfunction in multiple functional brain networks, as well as to alterations in the allocation of spatial attention. We used network-level analyses to characterize resting-state functional connectivity (rs-fc) alterations associated with 1) symptoms of anxiety and 2) alterations in stimulus-driven attention associated with pediatric anxiety disorders. We hypothesized that anxiety was related to altered connectivity of the frontoparietal, default mode, cingulo-opercular, and ventral attention networks and that anxiety-related connectivity alterations that include the ventral attention network would simultaneously be related to deviations in stimulus-driven attention.

METHODS

A sample of children (n = 61; mean = 10.6 years of age), approximately half of whom met criteria for a current anxiety disorder, completed a clinical assay, an attention task, and rs-fc magnetic resonance imaging scans. Network-level analyses examined whole-brain rs-fc patterns associated with clinician-rated anxiety and with involuntary capture of attention. Post hoc analyses controlled for comorbid symptoms.

RESULTS

Elevated clinician-rated anxiety was associated with altered connectivity within the cingulo-opercular network, as well as between the cingulo-opercular network and the ventral attention, default mode, and visual networks. Connectivity between the ventral attention and cingulo-opercular networks was associated with variation in both anxiety and stimulus-driven attention.

CONCLUSIONS

Pediatric anxiety is related to aberrant connectivity patterns among several networks, most of which include the cingulo-opercular network. These results help clarify the within- and between-network interactions associated with pediatric anxiety and its association with altered attention, suggesting that specific network connections could be targeted to improve specific altered processes associated with anxiety.

Attention Alterations in Pediatric Anxiety: Evidence From Behavior and Neuroimaging

BACKGROUND

Pediatric anxiety disorders involve greater capture of attention by threatening stimuli. However, it is not known if disturbances extend to nonthreatening stimuli, as part of a pervasive disturbance in attention-related brain systems. We hypothesized that pediatric anxiety involves greater capture of attention by salient, nonemotional stimuli, coupled with greater activity in the portion of the inferior frontal gyrus (IFG) specific to the ventral attention network (VAN).

METHODS

A sample of children (n = 129, 75 girls, mean 10.6 years of age), approximately half of whom met criteria for a current anxiety disorder, completed a task measuring involuntary capture of attention by nonemotional (square boxes) and emotional (angry and neutral faces) stimuli. A subset (n = 61) completed a task variant during functional magnetic resonance imaging. A priori analyses examined activity in functional brain areas within the right IFG, supplemented by a whole-brain, exploratory analysis.

RESULTS

Higher clinician-rated anxiety was associated with greater capture of attention by nonemotional, salient stimuli (F1,125 = 4.94, p = .028) and greater activity in the portion of the IFG specific to the VAN (F1,57 = 10.311, p = .002). Whole-brain analyses confirmed that the effect of anxiety during capture of attention was most pronounced in the VAN portion of the IFG, along with additional areas of the VAN and the default mode network.

CONCLUSIONS

The pathophysiology of pediatric anxiety appears to involve greater capture of attention to salient stimuli, as well as greater activity in attention-related brain networks. These results provide novel behavioral and brain-based targets for treatment of pediatric anxiety disorders.

Gray matter structures associated with neuroticism: A meta-analysis of whole-brain voxel-based morphometry studies

Neuroticism is major higher-order personality trait and has been robustly associated with mental and physical health outcomes. Although a growing body of studies have identified neurostructural markers of neuroticism, the results remained highly inconsistent. To characterize robust associations between neuroticism and variations in gray matter (GM) structures, the present meta-analysis investigated the concurrence across voxel-based morphometry (VBM) studies using the anisotropic effect size signed differential mapping (AES-SDM). A total of 13 studies comprising 2,278 healthy subjects (1,275 females, 29.20 ± 14.17 years old) were included. Our analysis revealed that neuroticism was consistently associated with the GM structure of a cluster spanning the bilateral dorsal anterior cingulate cortex and extending to the adjacent medial prefrontal cortex (dACC/mPFC). Meta-regression analyses indicated that the neuroticism-GM associations were not confounded by age and gender. Overall, our study is the first whole-brain meta-analysis exploring the brain structural correlates of neuroticism, and the findings may have implications for the intervention of high-neuroticism individuals, who are at risk of mental disorders, by targeting the dACC/mPFC.

Dysregulated brain salience within a triple network model in high trait anxiety individuals: A pilot EEG functional connectivity study

Although previous studies have reported the association between large-scale brain networks alterations and pathological anxiety, abnormalities in the dynamic interaction among the triple network model in anxiety disorders and, especially, in trait anxiety is still poorly explored. Thus, the main aim of the current study was to investigate triple network functional dynamics in subjects with high trait anxiety during resting state (RS) through electroencephalography (EEG) connectivity. Twenty-three individuals with high-trait-anxiety (HTA) and forty-five participants with low-trait-anxiety (LTA) were enrolled. EEG analyses were conducted by means of the exact Low-Resolution Electromagnetic Tomography software (eLORETA). Compared to LTA participants, HTA subjects showed a decrease of alpha connectivity within the salience network (SN), between the dorsal anterior cingulate cortex (dACC) and both left and right anterior insula (AI). Furthermore, SN functional connectivity strength was negatively correlated with higher trait anxiety, even when controlling for potential confounding variables (e.g., depressive and obsessive-compulsive symptoms). Taken together, our results point out a specific functional connectivity pattern in HTA individuals, which consists in a dysfunctional communication within the SN, specifically in the AI-dACC pathway. This functional pattern could underline, at rest, saliency detection and brain correlates of altereted emotion regulation and cognitive control processes typically involved in anxiety.

Structural abnormalities in nucleus accumbens in patients with panic disorder

BACKGROUND

Although the pathogenesis of panic attacks has been well studied in patients with panic disorder (PD), the neurobiological basis of the long-term fear memories and avoidance behavior that are often observed in PD have not been well investigated. Recent animal studies have suggested that nucleus accumbens (NAcc) plays an important role in neurobiological basis of long-term fear memories and avoidance behavior.

METHODS

Thirty-eight patients with PD and 38 matched healthy control subjects (HC) participated in this study. Differences in relative volumes and shape deformations of NAcc were evaluated between groups. Correlation analyses were conducted to quantify the association between structural abnormalities in the NAcc and trait, state anxiety measured by the State-Trait Anxiety Inventory (STAI).

RESULTS

Significant volume reductions were observed in the bilateral NAcc in the patients with PD, relative to the HC. In terms of shape differences, the PD patients demonstrated significant inward deformation of the NAcc bilaterally, compared to the HC. Degree of shape deformation in the right NAcc was associated with higher scores of the STAI-Trait, and STAI-State measures in the PD patients.

LIMITATIONS

All the patients received medication such as Psychotropic drug.

CONCLUSION

Patients with PD showed reduced volumes in the NAcc, especially in lateral regions, compared with HC. Furthermore, shape deformation in the right NAcc was associated with trait anxiety and state anxiety, which has been associated with avoidance behavior.

Network changes in patients with phobic postural vertigo

INTRODUCTION

Functional dizziness comprises a class of dizziness disorders, including phobic postural vertigo (PPV), that cause vestibular symptoms in the absence of a structural organic origin. For this reason, functional brain mechanisms have been implicated in these disorders.

METHODS

Here, functional network organization was investigated in 17 PPV patients and 18 healthy controls (HCs) during functional magnetic resonance imaging with a visual motion stimulus, data initially collected and described by Popp et al. (2018). Graph theoretical measures (degree centrality [DC], clustering coefficient [CC], and eccentricity) of 160 nodes within six functional networks were compared between HC and PPV patients during visual motion and static visual patterns.

RESULTS

Graph theoretical measures analyzed during the static condition revealed significantly different DC in the default-mode, sensorimotor, and cerebellar networks. Furthermore, significantly different group differences in network organization changes between static visual and visual motion stimulation were observed. In PPV, DC and CC showed a significantly stronger increase in the sensorimotor network during visual stimulation, whereas cerebellar network showed a significantly stronger decrease in DC.

CONCLUSION

These results suggest that the altered visual motion processing seen in PPV patients may arise from a modified state of sensory and cerebellar network connectivity.

Time-resolved connectome of the five-factor model of personality

The human brain is characterized by highly dynamic patterns of functional connectivity. However, it is unknown whether this time-variant 'connectome' is related to the individual differences in the behavioural and cognitive traits described in the five-factor model of personality. To answer this question, inter-network time-variant connectivity was computed in n = 818 healthy people via a dynamical conditional correlation model. Next, network dynamicity was quantified throughout an ad-hoc measure (T-index) and the generalizability of the multi-variate associations between personality traits and network dynamicity was assessed using a train/test split approach. Conscientiousness, reflecting enhanced cognitive and emotional control, was the sole trait linked to stationary connectivity across several circuits such as the default mode and prefronto-parietal network. The stationarity in the 'communication' across large-scale networks offers a mechanistic description of the capacity of conscientious people to 'protect' non-immediate goals against interference over-time. This study informs future research aiming at developing more realistic models of the brain dynamics mediating personality differences.

Neural evidence for long-term marriage shaping the functional brain network organization between couples

Long-term married couples have been reported to share personality and behavioural similarities, but whether long-term marriage would shape the brain is hitherto unknown. In this study, 35 pairs of long-term married couples, who have married and living together at least 30 years, were recruited, and resting state functional magnetic resonance imaging was used to examine the neural correlates of long-term marriage between couples. Seven intrinsic connectivity networks were extracted using spatially constrained group independent component analysis, and the spatial similarity of each network as well as functional connectome similarity between couples were investigated respectively. The significant spatial similarities in the salience and frontoparietal networks as well as marginally significant connectome similarity were observed in long-term married couples. In addition, the marital duration showed a significantly positive correlation with the spatial similarity in the frontoparietal network and connectome similarity. The results provide objective evidence that long-term marriage would shape brain network organization, and the combination of initial personality traits and long-term common experience of the couples may be potential factors that account for similar brain network organizations between couples.

On the psychology and economics of antisocial personality

How do fundamental concepts from economics, such as individuals' preferences and beliefs, relate to equally fundamental concepts from psychology, such as relatively stable personality traits? Can personality traits help us better understand economic behavior across strategic contexts? We identify an antisocial personality profile and examine the role of strategic context (the "situation"), personality traits (the "person"), and their interaction on beliefs and behaviors in trust games. Antisocial individuals exhibit a specific combination of beliefs and preferences that is difficult to reconcile with a rational choice approach that assumes that beliefs about others' behaviors are formed rationally and therefore, independently from preferences. Variations in antisocial personality are associated with effect sizes that are as large as strong variations in strategic context. Antisocial individuals have lower trust in others unless they know that they can punish them. They are also substantially less trustworthy, believe that others are like themselves, and respond to the possibility of being sanctioned more strongly, suggesting that they anticipate severe punishment if they betray their partner's trust. Antisocial individuals are not simply acting in their economic self-interest, because they harshly punish those who do not reciprocate their trust, although that reduces their economic payoff, and they do so nonimpulsively and in a very calculated manner. Antisocial individuals honor others' trust significantly less (if they cannot be punished) but also, harshly punish those who betray their trust. Overall, it seems that antisocial individuals have beliefs and behaviors based on a view of the world that assumes that most others are as antisocial as they themselves are.

Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: a graph-theoretic analysis of resting state functional connectivity

Previous studies have suggested that trait differences in emotional awareness (tEA) are clinically relevant, and associated with differences in neural structure/function. While multiple leading theories suggest that conscious awareness requires widespread information integration across the brain, no study has yet tested the hypothesis that higher tEA corresponds to more efficient brain-wide information exchange. Twenty-six healthy volunteers (13 females) underwent a resting state functional magnetic resonance imaging scan, and completed the Levels of Emotional Awareness Scale (LEAS; a measure of tEA) and the Wechsler Abbreviated Scale of Intelligence (WASI-II; a measure of general intelligence quotient [IQ]). Using a whole-brain (functionally defined) region of interest (ROI) atlas, we computed several graph theory metrics to assess the efficiency of brain-wide information exchange. After statistically controlling for differences in age, gender and IQ, we first observed a significant relationship between higher LEAS scores and greater average degree (i.e. overall whole-brain network density). When controlling for average degree, we found that higher LEAS scores were also associated with shorter average path lengths across the collective network of all included ROIs. These results jointly suggest that individuals with higher tEA display more efficient global information exchange throughout the brain. This is consistent with the idea that conscious awareness requires global accessibility of represented information.

Connectome-based individualized prediction of temperament trait scores

Temperament consists of multi-dimensional traits that affect various domains of human life. Evidence has shown functional connectome-based predictive models are powerful predictors of cognitive abilities. Putatively, individuals' innate temperament traits may be predictable by unique patterns of brain functional connectivity (FC) as well. However, quantitative prediction for multiple temperament traits at the individual level has not yet been studied. Therefore, we were motivated to realize the individualized prediction of four temperament traits (novelty seeking [NS], harm avoidance [HA], reward dependence [RD] and persistence [PS]) using whole-brain FC. Specifically, a multivariate prediction framework integrating feature selection and sparse regression was applied to resting-state fMRI data from 360 college students, resulting in 4 connectome-based predictive models that enabled prediction of temperament scores for unseen subjects in cross-validation. More importantly, predictive models for HA and NS could be successfully generalized to two relevant personality traits for unseen individuals, i.e., neuroticism and extraversion, in an independent dataset. In four temperament trait predictions, brain connectivities that show top contributing power commonly concentrated on the hippocampus, prefrontal cortex, basal ganglia, amygdala, and cingulate gyrus. Finally, across independent datasets and multiple traits, we show person's temperament traits can be reliably predicted using functional connectivity strength within frontal-subcortical circuits, indicating that human social and behavioral performance can be characterized by specific brain connectivity profile.

Network Neuroscience and Personality

Personality and individual differences originate from the brain. Despite major advances in the affective and cognitive neurosciences, however, it is still not well understood how personality and single personality traits are represented within the brain. Most research on brain-personality correlates has focused either on morphological aspects of the brain such as increases or decreases in local gray matter volume, or has investigated how personality traits can account for individual differences in activation differences in various tasks. Here, we propose that personality neuroscience can be advanced by adding a network perspective on brain structure and function, an endeavor that we label personality network neuroscience. With the rise of resting-state functional magnetic resonance imaging (MRI), the establishment of connectomics as a theoretical framework for structural and functional connectivity modeling, and recent advancements in the application of mathematical graph theory to brain connectivity data, several new tools and techniques are readily available to be applied in personality neuroscience. The present contribution introduces these concepts, reviews recent progress in their application to the study of individual differences, and explores their potential to advance our understanding of the neural implementation of personality. Trait theorists have long argued that personality traits are biophysical entities that are not mere abstractions of and metaphors for human behavior. Traits are thought to actually exist in the brain, presumably in the form of conceptual nervous systems. A conceptual nervous system refers to the attempt to describe parts of the central nervous system in functional terms with relevance to psychology and behavior. We contend that personality network neuroscience can characterize these conceptual nervous systems on a functional and anatomical level and has the potential do link dispositional neural correlates to actual behavior.

Oxytocin Facilitates Approach Behavior to Positive Social Stimuli via Decreasing Anterior Insula Activity

BACKGROUND

The neuropeptide oxytocin can extensively modulate human social behavior and affective processing, and its effects can be interpreted in terms of mediating approach-avoidance motivational processes. However, little is known about how oxytocin mediates approach-avoidance behavior and particularly the underlying neural mechanisms.

METHODS

In a randomized, double-blind, between-subject design, the present pharmaco-fMRI study used an approach-avoidance paradigm to investigate oxytocin's effects on approach-avoidance behavior and associated neural mechanisms.

RESULTS

Results revealed that oxytocin generally decreased activity in the right striatum irrespective of response (approach/avoidance) and social context, suggesting an inhibitory effect on motivational representation during both appetitive approach and aversive avoidance. Importantly, while on the behavioral level oxytocin selectively enhanced accuracy when approaching social positive stimuli, on the neural level it decreased left ventral and right dorsal anterior insula activity in response to social vs nonsocial positive stimuli compared with the placebo treatment. The left ventral anterior insula activity was negatively correlated with the corresponding accuracy difference scores in the oxytocin but not in the placebo group.

CONCLUSION

Given the role of the ventral anterior insula in emotional processing and the dorsal anterior insula in salience processing, the oxytocin-induced suppression of activity in these regions may indicate that oxytocin is acting to reduce interference from hyper-activity in core regions of the emotional and salience networks when approaching salient positive social stimuli and thereby to promote social interaction. Thus, oxytocin may be of potential therapeutic benefit for psychiatric disorders exhibiting avoidance of social stimuli.

Network Approaches to Understand Individual Differences in Brain Connectivity: Opportunities for Personality Neuroscience

Over the past decade, advances in the interdisciplinary field of network science have provided a framework for understanding the intrinsic structure and function of human brain networks. A particularly fruitful area of this work has focused on patterns of functional connectivity derived from noninvasive neuroimaging techniques such as functional magnetic resonance imaging. An important subset of these efforts has bridged the computational approaches of network science with the rich empirical data and biological hypotheses of neuroscience, and this research has begun to identify features of brain networks that explain individual differences in social, emotional, and cognitive functioning. The most common approach estimates connections assuming a single configuration of edges that is stable across the experimental session. In the literature, this is referred to as a static network approach, and researchers measure static brain networks while a subject is either at rest or performing a cognitively demanding task. Research on social and emotional functioning has primarily focused on linking static brain networks with individual differences, but recent advances have extended this work to examine temporal fluctuations in dynamic brain networks. Mounting evidence suggests that both the strength and flexibility of time-evolving brain networks influence individual differences in executive function, attention, working memory, and learning. In this review, we first examine the current evidence for brain networks involved in cognitive functioning. Then we review some preliminary evidence linking static network properties to individual differences in social and emotional functioning. We then discuss the applicability of emerging dynamic network methods for examining individual differences in social and emotional functioning. We close with an outline of important frontiers at the intersection between network science and neuroscience that will enhance our understanding of the neurobiological underpinnings of social behavior.