Personality traits and the amplitude of spontaneous low-frequency oscillations during resting state

Identifying neural network structures explained by personality traits: combining unsupervised and supervised machine learning techniques in translational validity assessment

There have been studies previously the neurobiological underpinnings of personality traits in various paradigms such as psychobiological theory and Eysenck’s model as well as five-factor model. However, there are limited results in terms of co-clustering of the functional connectivity as measured by functional MRI, and personality profiles. In the present study, we have analyzed resting-state connectivity networks and character type with the Lowen bioenergetic test in 66 healthy subjects. There have been identified direct correspondences between network metrics such as eigenvector centrality (EC), clustering coefficient (CC), node strength (NS) and specific personality characteristics. Specifically, N Acc L and OFCmed were associated with oral and masochistic traits in terms of EC and CC, while Insula R is associated with oral traits in terms of NS and EC. It is noteworthy that we observed significant correlations between individual items and node measures in specific regions, suggesting a more targeted relationship. However, the more relevant finding is the correlation between metrics (NS, CC, and EC) and overall traits. A hierarchical clustering algorithm (agglomerative clustering, an unsupervised machine learning technique) and principal component analysis were applied, where we identified three prominent principal components that cumulatively explain 76% of the psychometric data. Furthermore, we managed to cluster the network metrics (by unsupervised clustering) to explore whether neural connectivity patterns could be grouped based on combined average network metrics and psychometric data (global and local efficiencies, node strength, eigenvector centrality, and node strength). We identified three principal components, where the cumulative amount of explained data reaches 99%. The correspondence between network measures (CC and NS) and predictors (responses to Lowen’s items) is 62% predicted with a precision of 90%.

Neuroticism and openness exhibit an anti-correlation pattern to dissociable default mode network: using resting connectivity and structural equation modeling analysis

The default mode network (DMN) can be subdivided into ventral and dorsal subsystems, which serve affective cognition and mental sense construction, respectively. An internally dissociated pattern of anti-correlations was observed between these two subsystems. Although numerous studies on neuroticism and openness have demonstrated the neurological functions of the DMN, little is known about whether different subsystems and hubs regions within the network are engaged in different functions in response to the two traits. We recruited 223 healthy volunteers in this study and collected their resting-state functional magnetic resonance imaging (fMRI) and NEO Five-Factor Inventory scores. We used independent component analysis (ICA) to obtain the DMN, before further decomposing it into the ventral and dorsal subsystems. Then, the network coherence of hubs regions within subsystems was extracted to construct two structural equation models (SEM) to explore the relationship between neuroticism and openness traits and DMN. We observed that the ventral DMN could significantly predict positive openness and negative neuroticism. The dorsal DMN was diametrically opposed. Additionally, the medial prefrontal cortex (mPFC) and middle temporal gyrus (MTG), both of which are core hubs of the subnetworks within the DMN, are significantly positively correlated with neuroticism and openness. These findings may point to a biological basis that neuroticism and openness are engaged in opposite mechanisms and support the hypothesis about the functional dissociation of the DMN.

Cerebellar volume and functional connectivity in neonates predicts social and emotional development in toddlers

Over the past decade, a growing body of research in adults has emphasized the role of the cerebellum in social and emotional cognition. This has been further supported by findings of delayed social and emotional development in toddlers with cerebellar injury during the fetal and newborn periods. However, the contributions of the cerebellum to social-emotional development in typically developing newborns are unclear. To bridge this gap in knowledge, we used multimodal MRI to investigate associations between cerebellar structure and function in 88 healthy neonates (mean ± sd of postmenstrual age, = 42.00 ± 1.91 weeks) and social-emotional development at 18-months assessed using the Infant-Toddler Social-Emotional Assessment (ITSEA) (mean age on ITSEA: 18.32 ± 1.19 months old). We found that cerebellar volume was not associated with ITSEA domain scores at 18 months. We further demonstrated cerebellar functional gradient (FGR) defined using principal component analysis (PCA) was associated with Externalizing domain (linear regression model, false-discovery-rate-adjusted p = 0.013). This cluster (FGR7) included the left dentate, right VI, left Vermis VIIIb, and right V lobules. Finally, we demonstrated that either structural or functional features of the cerebellum reliably predicted scores on the Externalizing and Internalizing domains (correlation between actual and predicted scores: for structural, Fisher's z = 0.48 ± 0.01 for Internalizing, p = 0.01; for functional, Fisher's z = 0.45 ± 0.01 for Externalizing, p = 0.02; with permutation test). Collectively, our findings suggest that the cerebellum plays an important role in social-emotional development during the critical early stages of life.

Resting-state functional network connectivity underlying conscientiousness in school-aged children

Conscientiousness is a personality trait that matures from early childhood to late adolescence, yet little is known about its underlying brain mechanisms during this period. To investigate this, our study examined the resting-state functional network connectivity (rsFNC) of 69 school-aged children (mean age = 10.12 years, range = 9-12) using a whole-brain region-of-interest (ROI) based analysis, based on functional magnetic resonance imaging (fMRI). The results indicated a positive association between conscientiousness and the rsFNC between the fronto-parietal network (FPN) and two brain networks: the somatosensory motor-hand network (SMHN) and the auditory network (AN). However, conscientiousness was negatively associated with the rsFNC between FPN and two other networks: the salience network (SN); the default mode network (DMN). Moreover, our results suggest that the FPN may play a hub role in the neural performance of children's conscientiousness. Intrinsic brain networks, particularly those involved in higher-order cognitive functions, impact children's conscientiousness. Therefore, FPN plays an important role in the development of children's personality, providing insight into the neural mechanisms underlying children's personality.

Resting-state neural correlates of individual differences in ignored experience and its deleterious effect

Uncovering the neural mechanisms of ostracism experience (including its subclasses of excluded and ignored experiences) is important. However, the resting-state functional brain substrates responsible for individual differences in ostracism experience and its negative effects remain largely undefined. This study explored these issues in a sample of 198 Chinese college students by assessing the amplitude of low-frequency fluctuations and functional connectivity. The findings indicated a positive correlation between ignored experience and the amplitude of low-frequency fluctuations in the right superior frontal gyrus and the functional connectivity between the right superior frontal gyrus and left cerebellum posterior lobe. Additionally, a negative correlation was found between ignored experience and the functional connectivity between the right superior frontal gyrus and the bilateral insula as well as the bilateral inferior parietal lobule. Moreover, the mediation analysis demonstrated that the effects of the functional connectivities of right superior frontal gyrus-left cerebellum posterior lobe and right superior frontal gyrus-right inferior parietal lobule on revenge intention were mediated by ignored experience. Our study offers novel insights into the neural correlates of both individual variations in ignored experience and its typical deleterious effect. These results could deepen our understanding of individual differences in negative experiences and inspire the development of targeted interventions for social stress from the perspective of the brain.

Stability of specific personality network features corresponding to openness trait across different adult age periods: A machine learning analysis

The functional connectivity patterns of the brain during resting state are closely related to an individual's cognition, emotion, behavior, and social interactions, making it an important research method to measure personality traits in an unbiased way, replacing traditional paper-and-pencil tests. However, due to the dynamic nature of the brain, whether the changes in functional connectivity caused by age can stably map onto personality traits has not been previously investigated. This study focuses on whether network features that are significantly related to personality traits can effectively distinguish subjects with different personality traits, and whether these network features vary across different periods of adulthood. The study included 343 healthy adult participants, divided into early adulthood and middle adulthood groups according to the age threshold of 35. Resting-state functional magnetic resonance imaging (fMRI) and the Big Five personality questionnaire were collected. we investigated the relationship between personality traits and intrinsic whole-brain functional connectome. We then used support vector machine (SVM) to evaluate the performance of personality network features in distinguishing subjects with high and low scores in the early-adulthood sample, and cross-validated in the mid-adulthood sample. Additionally, edge-based analysis (NBS) was used to explore the stability of personality networks across the two age samples. Our results show that the network features corresponding to openness personality trait are stable and can effectively differentiate subjects with different scores in both age samples. Furthermore, this study found that these network features vary to some extent across different periods of adulthood. These findings provide new evidence and insights into the application of resting-state functional connectivity patterns in measuring personality traits and help us better understand the dynamic characteristics of the human brain.

Dimensional personality impairment is associated with disruptions in intrinsic intralimbic functional connectivity

BACKGROUND

Recently proposed alternative dimensional models of personality disorder (PD) place the severity of impairments in self and interpersonal functioning at the core of personality pathology. However, associations of these impairments with disturbances in social, cognitive, and affective brain networks remain uninvestigated.

METHODS

The present study examined patterns of resting-state functional connectivity (rsFC) in a sample of 74 age- and sex-matched participants (45 inpatients with PD and 29 healthy controls). At a minimum, PD patients carried a diagnosis of borderline PD, although the majority of the sample had one or more additional PDs. rsFC patterns in the following networks were compared between groups and in association with dimensional personality impairments: default mode network (DMN)/core mentalization, frontolimbic, salience, and central executive. Further, the extent to which variation in rsFC was explained by levels of personality impairment as compared to typology-specific borderline PD symptom severity was explored.

RESULTS

Relative to controls, the PD group showed disruptions in rsFC within the DMN/core mentalization and frontolimbic networks. Among PD patients, greater severity of dimensional self-interpersonal impairment was associated with stronger intralimbic rsFC. In contrast, severity of borderline PD-specific typology was not associated with any rsFC patterns.

CONCLUSIONS

Disruptions in core mentalization and affective networks are present in PD. Higher intralimbic functional connectivity may underlie self-interpersonal personality impairment in PD regardless of diagnostic typology-specific PD symptoms, providing initial neurobiological evidence supporting alternative dimensional conceptualizations of personality pathology.

Neural correlates of neuroticism: A coordinate-based meta-analysis of resting-state functional brain imaging studies

Neuroticism is one of the most robust higher-order personality traits associated with negative emotionality and risk of mental disorders. Many studies have investigated relationships between neuroticism and the brain, but the results have been inconsistent. We conducted a meta-analysis of whole-brain resting-state functional neuroimaging studies to identify the most stable neurofunctional substrates of neuroticism. We found stable significant positive correlations between neuroticism and resting-state brain activity in the left middle temporal gyrus (MTG), left striatum, and right hippocampus. In contrast, resting-state brain activity in the left superior temporal gyrus (STG) and right supramarginal gyrus (SMG) was negatively associated with neuroticism. Additionally, meta-regression analysis revealed brain regions in which sex and age moderated the link of spontaneous activity with neuroticism. This is the first study to provide a comprehensive understanding of resting-state brain activity correlates of neuroticism, and the findings may be useful for the targeting of specific brain regions for interventions to decrease the risks of mental health problems.

Underlying differences in resting-state activity metrics related to sensitivity to punishment

Reinforcement sensitivity theory (RST) of personality establishes the punishment sensitivity trait as a source of variation in defensive avoidance/approach behaviors. These individual differences reflect dissimilar sensitivity and reactivity of the fight-flight-freeze and behavioral inhibition systems (FFFS/BIS). The sensitivity to punishment (SP) scale has been widely used in personality research aimed at studying the activity of these systems. Structural and functional neuroimaging studies have confirmed the core biological correlates of FFFS/BIS in humans. Nonetheless, some brain functional features derived from resting-state blood-oxygen level-dependent (BOLD) activity and its association with the punishment sensitivity dimension remain unclear. This relationship would shed light on stable neural activity patterns linked to anxiety-like behaviors and anxiety predisposition. In this study, we analyzed functional activity metrics "at rest" [e.g., regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF)] and their relationship with SP in key FFFS/BIS regions (e.g., amygdala, hippocampus, and periaqueductal gray) in a sample of 127 healthy adults. Our results revealed a significant negative correlation between the fALFF within all these regions and the scores on SP. Our findings suggest aberrant neural activity (lower fALFF) within the brain's defense system in participants with high trait anxiety, which in turn could reflect lower FFFS/BIS activation thresholds. These neurally-located differences could lead to pathological fear/anxiety behaviors arising from the FFFS and BIS.

Functional connectivity of the central autonomic and default mode networks represent neural correlates and predictors of individual personality

There is solid evidence for the prominent involvement of the central autonomic and default mode systems in shaping personality. However, whether functional connectivity of these systems can represent neural correlates and predictors of individual variation in personality traits is largely unknown. Resting-state functional magnetic resonance imaging data of 215 healthy young adults were used to construct the sympathetic (SN), parasympathetic (PN), and default mode (DMN) networks, with intra- and internetwork functional connectivity measured. Personality factors were assessed using the five-factor model. We examined the associations between personality factors and functional network connectivity, followed by performance of personality prediction based on functional connectivity using connectome-based predictive modeling (CPM), a recently developed machine learning approach. All personality factors (neuroticism, extraversion, conscientiousness, and agreeableness) other than openness were significantly correlated with intra- and internetwork functional connectivity of the SN, PN, and DMN. Moreover, the CPM models successfully predicted conscientiousness and agreeableness at the individual level using functional network connectivity. Our findings may expand existing knowledge regarding the neural substrates underlying personality.

Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity

Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.

Chronic Stress in Bipolar Disorders Across the Different Clinical States: Roles of HPA Axis and Personality

INTRODUCTION

Chronic stress has been linked to the pathophysiology of bipolar disorder (BD); however, the underlying mechanism remains unclear. In BD patients, hypothalamic-pituitary-adrenal (HPA) axis activity is associated with stress. This study aimed to examine the relationship between HPA axis activity and BD symptoms in various clinical states, as well as how personality influences the process.

METHODS

This study investigated the differences in HPA axis activity among four BD states. We enrolled 813 BD patients in an 8-week longitudinal study to examine the relationship between HPA axis activity and symptom trajectories using dynamic temporal warping (DTW) analysis and an unsupervised machine learning technique. Furthermore, using mediation analyses, the relationship between the HPA axis, personality, and BD symptoms was investigated.

RESULTS

Analysis of variance (ANOVA) analysis showed that glucocorticoid cortisol (CORT) and adrenocorticotropin (ACTH) did not differ significantly among the four clinical states of BD. The DTW integrating clustering analysis revealed that the two clusters were optimal, with cluster 1 characterized by severe manic symptoms, which then improved, and cluster 2, characterized by milder manic severity, which also improved. The two clusters showed different ACTH levels (t = 2.289, p = 0.022), and logistic regression analysis revealed a slight positive association between ACTH levels and cluster 1. Furthermore, the mediation analysis indicated that ACTH influences curative efficacy via conscientiousness (βc =0.103, p=0.001).

DISCUSSION

In conclusion, we found that a higher level of ACTH is associated with severe manic symptoms, indicating a chronic stress response in BD patients. Additionally, the ACTH levels affect short-term BD curative efficacy via the mediation of conscientiousness, providing a psychotherapeutic strategy direction for BD.

Using resting thalamic connectivity to identify the relationship between Eysenck personality traits and intelligence in healthy adults

Personality refers to a set of relatively stable psychological characteristics of individuals and has been associated with intelligence. It is well known that the thalamus plays an important role in cognitive processes and personality traits, but the relationship between personality traits, thalamic function, and intelligence has rarely been directly explored. Hence, we investigated the relationship between Eysenck personality traits, resting-state functional connectivity (rsFC) of the thalamus, and intelligence in a large sample of healthy adults (N = 176). We found that the trait of psychoticism was negatively associated with intelligence. The high intelligence group showed significantly lower psychoticism and demonstrated enhanced thalamic connectivity to the amygdala, inferior parietal lobules, pallidum, medial superior/middle frontal gyrus, and precuneus. Furthermore, a mediation analysis indicated that the FC between the left thalamus and left amygdala significantly mediated the correlation between psychoticism and full IQ (FIQ). These findings suggest that intelligent people may be less prone to psychoticism. Meanwhile, thalamic rsFC may reflect individual differences in intelligence and play a key role in the relationship between personality traits and intellectual abilities.

Stronger functional network connectivity and social support buffer against negative affect during the COVID-19 outbreak and after the pandemic peak

Health and financial uncertainties, as well as enforced social distancing, during the COVID-19 pandemic have adversely affected the mental health of people. These impacts are expected to continue even after the pandemic, particularly for those who lack support from family and friends. The salience network (SN), default mode network (DMN), and frontoparietal network (FPN) function in an interconnected manner to support information processing and emotional regulation processes in stressful contexts. In this study, we examined whether functional connectivity of the SN, DMN, and FPN, measured using resting-state functional magnetic resonance imaging before the pandemic, is a neurobiological marker of negative affect (NA) during the COVID-19 pandemic and after its peak in a large sample (N = 496, 360 females); the moderating role of social support in the brain-NA association was also investigated. We found that participants reported an increase in NA during the pandemic compared to before the pandemic, and the NA did not decrease, even after the peak period. People with higher connectivity within the SN and between the SN and the other two networks reported less NA during and after the COVID-19 outbreak peak, and the buffer effect was stronger if their social support was greater. These findings suggest that the functional networks that are responsible for affective processing and executive functioning, as well as the social support from family and friends, play an important role in protecting against NA under stressful and uncontrollable situations.

Neuroticism and Extraversion Are Related to Changes in Postural Stability During Anatomically-Related Cognitive Tasks

The relationship between personality and postural stability has received little attention. This study addressed whether neuroticism and extraversion correlate with changes in postural stability while performing cognitive tasks related to brain regions selectively associated with neuroticism and extraversion. Thirty-two adults stood on a foam mat in tandem stance and completed a 2-back task and a weather prediction task (WPT). As predicted, higher neuroticism was related to increased dual task sway during the 2-back task, r = 0.40, p = 0.023, and lower extraversion was related to increased dual task sway during the WPT, r = -0.43, p = 0.013, suggesting that personality is related to postural stability in healthy young adults and that personality could be considered in the prediction and treatment of individuals with balance difficulties.

Increased resting-state activity in the cerebellum with mothers having less adaptive sensory processing and trait anxiety

Child‐rearing mothers with high levels of trait anxiety have a tendency for less adaptive sensory processing, which causes parenting stress. However, the neural mechanisms underlying this sensory processing and trait anxiety remain unclear. We aimed to determine the whole‐brain spontaneous neural activity and sensory processing characteristics in mothers with varying parenting stress levels. Using resting‐state functional magnetic resonance imaging, we assessed mothers caring for more than one preschool aged (2–5 years) child and presenting with varying levels of sensory processing, trait anxiety, and parenting stress. Spontaneous neural activities in select brain regions were evaluated by whole‐brain correlation analyses based on the fractional amplitude of low‐frequency fluctuations (fALFF). We found significant positive correlations between levels of sensory processing with trait anxiety and parenting stress. Mothers having less adaptive sensory processing had significantly increased resting‐state network activities in the left lobule VI of the cerebellum. Increased fALFF values in the left lobule VI confirmed the mediation effect on the relationship between trait anxiety and sensory processing. A tendency for less adaptive sensory processing involving increased brain activity in lobule VI could be an indicator of maternal trait anxiety and the risk of parenting stress.

Mechanisms of the Effects of Parental Emotional Warmth on Extraversion in Children and Adolescents

The purpose of this study is to probe into the influence mechanism of parental emotional warmth (PEW) on extraversion for children and adolescents, as well as the moderating and mediating role of brain functional activity. Thirty-two children and adolescents underwent functional magnetic resonance imaging (fMRI) scans and completed Egna Minnen av Barndoms Uppfostran (EMBU) and Eysenck Personality Questionnaire (EPQ). Small-worldness (SW) of brain networks, fractional amplitude of low-frequency fluctuations (fALFF), and region-of-interest to region-of-interest (ROI-ROI) functional connectivity were calculated to study intrinsic neuronal activity. We found that PEW had a positive direct effect on extraversion, and all participants in the current study showed an efficient small-world structure. The positive association between PEW and extraversion was mediated by SW. Furthermore, the fALFF and extraversion were significantly and negatively correlated in the right precuneus and dorsolateral superior frontal gyrus. The mediating effect of SW was moderated by the functional connectivity between the right precuneus and the right dorsolateral superior frontal gyrus. The indirect effect was significant with lower level of the functional connectivity between the right precuneus and the right dorsolateral superior frontal gyrus. These findings indicate that SW of brain networks may be a key factor that accounts for the positive association between PEW and extraversion in children and adolescents and the level of the functional connectivity between the right precuneus and the right dorsolateral superior frontal gyrus could moderate the relationship.

Default Mode Network Functional Connectivity Negatively Associated with Trait Openness to Experience

Evaluating associations between the five-factor personality domains and resting-state functional connectivity networks (e.g., default mode network, DMN) highlights distributed neurobiological systems linked to behaviorally relevant phenotypes. Establishing these associations can highlight a potential underlying role for these neural pathways in related clinical illness and treatment response. Here we examined associations between within- and between-network resting-state functional connectivity with functional magnetic resonance imaging (fMRI) and the five-factor personality domains: Openness to experience (Openness), Extraversion, Neuroticism, Agreeableness and Conscientiousness. We included data from 470 resting-state scan sessions and personality assessments in 295 healthy participants. Within- and between-network functional connectivity from 32 a priori defined regions was computed across seven resting-state networks. The association between functional connectivity and personality traits was assessed using generalized least squares. Within-network DMN functional connectivity was significantly negatively associated with trait Openness (regression coefficient= -0.0010; [95% CI] = [-0.0017, -0.0003]; pFWER = 0.033), seemingly driven by association with the Fantasy subfacet. Trait Extraversion was significantly negatively associated with functional connectivity between the visual and dorsal attention networks and positively associated with functional connectivity between the frontoparietal and language networks. Our findings provide evidence that resting-state DMN is associated with trait Openness and gives insight into personality neuroscience.

Resting-state functional brain connectivity in a predominantly African-American sample of older adults: exploring links among personality traits, cognitive performance, and the default mode network

The personality traits of neuroticism, openness, and conscientiousness are relevant factors for cognitive aging outcomes. The present study examined how these traits were associated with cognitive abilities and corresponding resting-state functional connectivity (RSFC) of the default mode network (DMN) in an older and predominantly minority sample. A sample of 58 cognitively unimpaired, largely African-American, older adults (M age = 68.28 ± 8.33) completed a standard RSFC magnetic resonance imaging sequence, a Big Five measure of personality, and delayed memory, Stroop, and verbal fluency tasks. Personality trait associations of within-network connectivity of the posterior cingulate cortex (PCC), a hub of the DMN, were examined using a seed-based approach. Trait scores were regressed on cognitive performance (delayed memory for neuroticism, Stroop for conscientiousness, and verbal fluency for openness). Greater openness predicted greater verbal fluency and greater RSFC between the PCC and eight clusters, including the medial prefrontal cortex, left middle frontal gyrus, and precuneus. Greater PCC–precuneus connectivity predicted greater verbal fluency. Neuroticism and conscientiousness did not significantly predict either cognitive performance or RSFC. Although requiring replication and elaboration, the results implicate openness as a contributing factor to cognitive aging via concomitant cognitive performance and connectivity within cortical hubs of the DMN and add to the sparse literature on these variables in a diverse group of older adults.

Robust prediction of individual personality from brain functional connectome

Neuroimaging studies have linked inter-individual variability in the brain to individualized personality traits. However, only one or several aspects of personality have been effectively predicted based on brain imaging features. The objective of this study was to construct a reliable prediction model of personality in a large sample by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. High-quality resting-state functional magnetic resonance imaging data of 810 healthy young participants from the Human Connectome Project dataset were used to construct large-scale brain networks. Personality traits of the five-factor model (FFM) were assessed by the NEO Five Factor Inventory. We found that CPM successfully and reliably predicted all the FFM personality factors (agreeableness, openness, conscientiousness and neuroticism) other than extraversion in novel individuals. At the neural level, we found that the personality-associated functional networks mainly included brain regions within default mode, frontoparietal executive control, visual and cerebellar systems. Although different feature selection thresholds and parcellation strategies did not significantly influence the prediction results, some findings lost significance after controlling for confounds including age, gender, intelligence and head motion. Our finding of robust personality prediction from an individual's unique functional connectome may help advance the translation of 'brain connectivity fingerprinting' into real-world personality psychological settings.

The Similarity Between Chinese Five-Pattern and Eysenck's Personality Traits: Evidence From Theory and Resting-State fMRI

Chinese five-pattern and Eysenck’s personality traits are two types of personality theories based on different cultural backgrounds. The former is an indigenous theory, and the latter is a cross-cultural theory. In order to verify the relationship between two different personality traits from theory and neuropsychology, the current study recruited 170 healthy adults to calculate their five-Pattern Personality Inventory (FPPI) and Eysenck Personality Questionnaire-Revised (EPQ) scales and to scan their brains using functional magnetic resonance imaging (fMRI). Then, we performed stepwise-regression analysis and mediation-effect analysis to explore the association between brain regional homogeneity (ReHo) and two types of personality traits. The results showed that the ReHo of the right superior temporal gyrus (STG) positively correlated with TaiYang traits for FPPI and that there was a significant linear relationship with extraversion and neuroticism for EPQ. Besides, the ReHo of the right medial prefrontal cortex (mPFC) positively correlated with TaiYin for FPPI, and it also showed a significant linear relationship with neuroticism for EPQ. Furthermore, we found that extroversion and neuroticism partially mediated the relationship between five-pattern personality traits and the regional brain function, based on the mediation-effect analysis. Our findings suggest that Chinese five-pattern personality traits have a close relationship with Eysenck’s personality traits and that both may be engaged in similar neurobiological mechanisms in common brain regions to some extent. Hence, these findings first reveal a relationship between Chinese traditional personality traits and Western Eysenck’s personality traits in terms of both theoretical and neurobiological contexts.

Revisiting the Functional Anatomy of the Human Brain: Toward a Meta-Networking Theory of Cerebral Functions

For more than one century, brain processing was mainly thought in a localizationist framework, in which one given function was underpinned by a discrete, isolated cortical area, and with a similar cerebral organization across individuals. However, advances in brain mapping techniques in humans have provided new insights into the organizational principles of anatomo-functional architecture. Here, we review recent findings gained from neuroimaging, electrophysiological, as well as lesion studies. Based on these recent data on brain connectome, we challenge the traditional, outdated localizationist view and propose an alternative meta-networking theory. This model holds that complex cognitions and behaviors arise from the spatiotemporal integration of distributed but relatively specialized networks underlying conation and cognition (e.g., language, spatial cognition). Dynamic interactions between such circuits result in a perpetual succession of new equilibrium states, opening the door to considerable interindividual behavioral variability and to neuroplastic phenomena. Indeed, a meta-networking organization underlies the uniquely human propensity to learn complex abilities, and also explains how postlesional reshaping can lead to some degrees of functional compensation in brain-damaged patients. We discuss the major implications of this approach in fundamental neurosciences as well as for clinical developments, especially in neurology, psychiatry, neurorehabilitation, and restorative neurosurgery.

Scaling behaviour in music and cortical dynamics interplay to mediate music listening pleasure

The pleasure of music listening regulates daily behaviour and promotes rehabilitation in healthcare. Human behaviour emerges from the modulation of spontaneous timely coordinated neuronal networks. Too little is known about the physical properties and neurophysiological underpinnings of music to understand its perception, its health benefit and to deploy personalized or standardized music-therapy. Prior studies revealed how macroscopic neuronal and music patterns scale with frequency according to a 1/f^α relationship, where a is the scaling exponent. Here, we examine how this hallmark in music and neuronal dynamics relate to pleasure. Using electroencephalography, electrocardiography and behavioural data in healthy subjects, we show that music listening decreases the scaling exponent of neuronal activity and-in temporal areas-this change is linked to pleasure. Default-state scaling exponents of the most pleased individuals were higher and approached those found in music loudness fluctuations. Furthermore, the scaling in selective regions and timescales and the average heart rate were largely proportional to the scaling of the melody. The scaling behaviour of heartbeat and neuronal fluctuations were associated during music listening. Our results point to a 1/f resonance between brain and music and a temporal rescaling of neuronal activity in the temporal cortex as mechanisms underlying music appreciation.

The relationship among resting-state brain activity and connectivity, agreeableness and displaced aggression: Two possible mediation models

BACKGROUND

Displaced aggression is a specific form of attack prompted by rumination on anger experiences and revenge thought which might lead to expression of anger on innocent people. There is sufficient evidence demonstrating the potential role of agreeableness in reducing displaced aggression in theory. However, little is known about the neural basis of displaced aggression and how agreeableness and the underlying neural mechanisms link to displaced aggression.

METHODS

In this investigation, we examined these issues on 123 college students by assessing resting-state brain activity (i.e. amplitude of low-frequency fluctuation, ALFF) and connectivity (i.e. resting-state functional connectivity, RSFC).

RESULTS

Whole-brain correlation analysis revealed that a higher level of displaced aggression was linked with decreased ALFF in the left dorsomedial prefrontal cortex (dmPFC) and decreased RSFC between the left dmPFC and left ventromedial prefrontal cortex (vmPFC). Mediation analysis further revealed that left dmPFC activity and the left dmPFC-vmPFC connectivity mediated the relationship between agreeableness and displaced aggression, as well as agreeableness mediated the relation between left dmPFC activity and the left dmPFC-vmPFC connectivity and displaced aggression.

LIMITATIONS

Only ALFF and RSFC were used as indicators of brain function in this study. The two mediation models need to be further tested by longitudinal design or experimental methods in further studies.

CONCLUSIONS

This study suggested that dmPFC and vmPFC might be the functional neural markers of displaced aggression and provided two possible mediation models regarding the relationship among the resting-state brain activity and connectivity, agreeableness and displaced aggression.

Brain structure links trait conscientiousness to academic performance

In the long history of identifying factors to predict academic performance, conscientiousness, a so-called ‘big five’ personality trait describing self-regulation and goal-directed behavior, has emerged as a stable predictor for this purpose. However, the neuroanatomical substrates of trait conscientiousness and the underlying brain mechanism linking trait conscientiousness and academic performance are still largely unknown. Here, we examined these issues in 148 high school students within the same grade by estimating cortical gray matter volume (GMV) utilizing a voxel-based morphometry method based on structural magnetic resonance imaging. A whole-brain regression analysis showed that trait conscientiousness was positively associated with the GMV in the bilateral superior parietal lobe (SPL) and was negatively associated with the GMV in the right middle frontal gyrus (MFG). Furthermore, mediation analysis revealed that trait conscientiousness mediated the influences of the SPL and MFG volume on academic performance. Importantly, our results persisted even when we adjusted for general intelligence, family socioeconomic status and ‘big five’ personality traits other than conscientiousness. Altogether, our study suggests that the GMV in the frontoparietal network is a neurostructural marker of adolescents’ conscientiousness and reveals a potential brain-personality-achievement pathway for predicting academic performance in which gray matter structures affect academic performance through trait conscientiousness.

Resting-state dynamics as a neuromarker of dopamine administration in healthy female adults

BACKGROUND

Different neuromarkers of people's emotions, personality traits and behavioural performance have recently been identified. However, not much attention has been devoted to neuromarkers of neural responsiveness to drug administration.

AIMS

We investigated the predictive neuromarkers of acute dopamine (DA) administration.

METHODS

In a double-blind, within-subject study, we administrated a DA agonist (pramipexole) or placebo to 27 healthy female subjects. Using multivariate classification and prediction analyses, we examined whether dopaminergic modulations of task-free resting-state brain dynamics predict individual differences in pramipexole's modulation of facial attractiveness evaluations.

RESULTS

Our results demonstrate that pramipexole's effects on brain dynamics could be successfully discriminated from resting-state functional connectivity (accuracy: 78.9%; p < 0.0001). On the behavioural level, pramipexole increased facial attractiveness evaluations (t₍₃₉₎ = 4.44; p < 0.0001). In particular, pramipexole administration enhanced connectivity strength of the cinguloopercular network (t₍₂₃₎ = 3.29; p = 0.003) and increased brain signal variability in subcortical and prefrontal brain areas (t₍₁₃₎ = 3.05, p = 0.009). Importantly, multivariate predictive models reveal that pramipexole-dependent modulation of resting-state dynamics predicted the increase of facial attractiveness evaluations after pramipexole (connectivity strength: standardized mean squared error, smse = 0.65; p = 0.0007; brain signal variability: smse = 0.94, p = 0.015).

CONCLUSION

These results demonstrate that modulations of resting-state brain dynamics induced by a DA agonist predict drug-related effects on evaluation processes, providing a neuromarker of the neural responsiveness of specific brain networks to DA administration.

Reduced Brain Activity in the Right Putamen as an Early Predictor for Treatment Response in Drug-Naive, First-Episode Schizophrenia

Antipsychotic medications can have a significant effect on brain function after only several days of treatment. It is unclear whether such an acute effect can serve as an early predictor for treatment response in schizophrenia. Thirty-two patients with drug-naive, first-episode schizophrenia and 32 healthy controls underwent resting-state functional magnetic resonance imaging. Patients were treated with olanzapine and were scanned at baseline and 1 week of treatment. Healthy controls were scanned once at baseline. Symptom severity was assessed within the patient group using the Positive and Negative Syndrome Scale (PANSS) at three time points (baseline, 1 week of treatment, and 8 weeks of treatment). The fractional amplitude of low frequency fluctuation (fALFF) and support vector regression (SVR) methods were used to analyze the data. Compared with the control group, the patient group showed increased levels of fALFF in the bilateral putamen at baseline. After 1week of olanzapine treatment, the patient group showed decreased levels of fALFF in the right putamen relative to those at baseline. The SVR analysis found a significantly positive relationship between the reduction in fALFF after 1 week of treatment and the improvement in positive symptoms after 8 weeks of treatment (r = 0.431, p = 0.014). The present study provides evidence that early reduction and normalization of fALFF in the right putamen may serve as a predictor for treatment response in patients with schizophrenia.

Relationship between extraversion personality and gray matter volume and functional connectivity density in healthy young adults: an fMRI study

Extraversion and neuroticism are two main dimensions of Eysenck's personality. We assessed the relationship between extraversion and neuroticism with brain structure and function by voxel-based morphometry (VBM) and functional connectivity density (FCD). The resting state functional magnetic resonance image and high resolution structural T1 weighted images of 100 young healthy subjects were used in analysis. Our results showed that extraversion was negatively correlated with gray matter volume (GMV) of the bilateral putamen, and it was negatively correlated with FCD in the precuneus. No associations between neuroticism and brain structure and function changes. Overall, our results suggested that several brain regions involved in shaping of extraversion traits among young individuals, which may provide a neurobiological basis of extraversion.

Functional connectivity pattern underlies individual differences in independent self-construal

Independent vs interdependent self-construal is a concept that reflects how people perceive the relationship between self and other people, which has been extensively examined across disciplines. However, little evidence on the whole-brain functional connectivity (FC) pattern of independent vs interdependent self-construal has been reported. Here, in a sample of 51 healthy participants, we used resting-state functional magnetic resonance imaging and voxel-based FC analysis (i.e. FC strength and seed-based FC) by measuring the temporal correlation of blood oxygen level-dependent signals between spatially separate brain regions to investigate the neural mechanism of independent vs interdependent self-construal. First, we found that FC strength of bilateral posterior cingulate cortex and precuneus, and left inferior frontal gyrus were positively correlated with the independent vs interdependent score. Seed-based FC analysis with these three regions as seeds revealed that, FC within default mode network and executive control network was positively correlated with the independent vs interdependent score. Negative correlation with independent vs interdependent score was shown in the connections between default mode network and executive control regions. Taking together, our results provide a comprehensive FC architecture of the independent vs interdependent self-construal and advance the understanding of the interplay between culture, mind and brain.

Intersubject similarity of personality is associated with intersubject similarity of brain connectivity patterns

Personality is a central high-level psychological concept that defines individual human beings and has been associated with a variety of real-world outcomes (e.g., mental health and academic performance). Using 2 h, high resolution, functional magnetic resonance imaging (fMRI) resting state data of 984 (primary dataset N = 801, hold-out dataset N = 183) participants from the Human Connectome Project (HCP), we investigated the relationship between personality (five-factor model, FFM) and intrinsic whole-brain functional connectome. We found a pattern of functional brain connectivity ("global personality network") related to personality traits. Consistent with the heritability of personality traits, the connectivity strength of this global personality network is also heritable (more similar between monozygotic twin pairs compared to the dizygotic twin pairs). Validated by both the repeated family-based 10-fold cross-validation and hold-out dataset, our intersubject network similarity analysis allowed us to identify participants' pairs with similar personality profiles. Across all the identified pairs of participants, we found a positive correlation between the network similarity and personality similarity, supporting our "similar brain, similar personality" hypothesis. Furthermore, the global personality network can be used to predict the individual subject's responses in the personality questionnaire on an item level. In sum, based on individual brain connectivity pattern, we could predict different facets of personality, and this prediction is not based on localized regions, but rather relies on the individual connectivity pattern in large-scale brain networks.

Implication of the DGKH genotype in openness to experience, a premorbid personality trait of bipolar disorder

AIMS

The diacylglycerol kinase η gene (DGKH) is one of the few replicated risk genes for bipolar disorder. Meanwhile, specific personality traits, especially openness to experience, have been suggested as premorbid personality traits of the disorder. The aim of the present study was to examine the relation of the DGKH genotype with broad dimensions of personality, to obtain further evidence for its implication in the etiology of bipolar disorder.

METHODS

The subjects were 319 Japanese healthy volunteers. Personality was assessed by the NEO Personality Inventory-Revised, which has the neuroticism, extraversion, openness to experience, agreeableness and conscientiousness dimensions. The A/G polymorphism of DGKH (rs9525580) was detected by a PCR-RFLP method. The subjects were divided into two groups with respect to the presence or absence of the A allele, which is a putative risk allele for bipolar disorder.

RESULTS

The group with the A allele had significantly (p < 0.05) higher scores of openness to experience compared to that without this allele. Scores of other dimensions were not different between the two groups.

LIMITATIONS

The subjects had a homogeneous but rather specific background, and we did not employ a longitudinal design.

CONCLUSIONS

The present study shows that a bipolar-risk allele of DGKH is associated with higher openness to experience, providing further evidence for the implication of this gene in the etiology of bipolar disorder.

An Overview of Functional Magnetic Resonance Imaging Techniques for Organizational Research

Functional magnetic resonance imaging is a galvanizing tool for behavioral scientists. It provides a means by which to see what the brain does while a person thinks, acts, or perceives, without invasive procedures. In this, fMRI affords us a relatively easy manner by which to peek under the hood of behavior and into the brain. Characterizing behavior with a neural correlate allows us to support or discard theoretical assumptions about the brain and behavior, to identify markers for individual and group differences. The increasing popularity of fMRI is facilitated by the apparent ease of data acquisition and analysis. This comes at a price: low signal-to-noise ratios, limitations in experimental design, and the difficulty in correctly applying and interpreting statistical tests are just a few of the pitfalls that have brought into question the reliability and validity of published fMRI data. Here, we aim to provide a general overview of the method, with an emphasis on fMRI and its analysis. Our goal is to provide the novice user with a comprehensive framework to get started on designing an imaging experiment in humans.

Personality Profiles Are Associated with Functional Brain Networks Related to Cognition and Emotion

Personality factors as defined by the "five-factor model" are some of the most investigated characteristics that underlie various types of complex behavior. These are, however, often investigated as isolated traits that are conceptually independent, yet empirically are typically strongly related to each other. We apply Independent Component Analysis to these personality factors as measured by the NEO-FFI in 471 healthy subjects from the Human Connectome Project to investigate independent personality profiles that incorporate all five original factors. Subsequently we examine how these profiles are related to patterns of resting-state brain activity in specific networks-of-interest related to cognition and emotion. We find that a personality profile of contrasting openness and agreeableness is associated with engagement of a subcortical-medial prefrontal network and the dorsolateral prefrontal cortex. Likewise, a profile of contrasting extraversion and conscientiousness is associated with activity in the precuneus. This study shows a novel approach to investigating personality and how it is related to patterns of activity in the resting brain.

White-Matter Structural Connectivity in Relation to Humor Styles: An Exploratory Study

To investigate the potential relationship between white matter (WM) microstructure and humor styles, diffusion tensor images of brain WM and humor style tendencies were obtained from thirty healthy adults. Using connectivity efficiency measures from graph theoretical analysis and controlling for the influence of gender, age, educational level, and the big five personality traits, we preliminarily examined the prediction of humor styles from brain network efficiency. The results showed that the local efficiency within particular brain networks positively predicted a self-enhancing humor style and negatively predicted an aggressive humor style. The node efficiency of the left superior temporal gyrus distinguished the benevolent or hostile way that individuals coped with interpersonal embarrassment. These findings from this exploratory study support the hypothesis that WM structure influences humor styles, and provide the initial evidence and implications regarding the relationship between biological mechanisms and mental health for future research.

Neural correlates of creative insight: Amplitude of low-frequency fluctuation of resting-state brain activity predicts creative insight

Creative insight has attracted much attention across cultures. Although previous studies have explored the neural correlates of creative insight by functional magnetic resonance imaging (fMRI), little is known about intrinsic resting-state brain activity associated with creative insight. In the present study, we used amplitude of low-frequency fluctuation (ALFF) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in creative insight, which was measured by the response time of creative Chinese character chunk decomposition. Our results showed that ALFF in the superior frontal gyrus (SFG) positively predicted creative insight, while ALFF in the middle cingulate cortex/insula cortex (MCC/IC), superior temporal gyrus/angular gyrus (STG/AG), anterior cingulate cortex/caudate nucleus (ACC/CN), and culmen/declive (CU/DC) negatively predicted creative insight. Moreover, these findings indicate that spontaneous brain activity in multiple regions related to breaking mental sets, solutions exploring, evaluation of novel solutions, forming task-related associations, and emotion experience contributes to creative insight. In conclusion, the present study provides new evidence to further understand the cognitive processing and neural correlates of creative insight.

The optimistic brain: Trait optimism mediates the influence of resting-state brain activity and connectivity on anxiety in late adolescence

As a hot research topic in the field of psychology and psychiatry, trait optimism reflects the tendency to expect positive outcomes in the future. Consistent evidence has demonstrated the role of trait optimism in reducing anxiety among different populations. However, less is known about the neural bases of trait optimism and the underlying mechanisms for how trait optimism protects against anxiety in the healthy brain. In this investigation, we examined these issues in 231 healthy adolescent students by assessing resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations, fALFF) and connectivity (i.e., resting-state functional connectivity, RSFC). Whole-brain correlation analyses revealed that higher levels of trait optimism were linked with decreased fALFF in the right orbitofrontal cortex (OFC) and increased RSFC between the right OFC and left supplementary motor cortex (SMC). Mediation analyses further showed that trait optimism mediated the influence of the right OFC activity and the OFC-SMC connectivity on anxiety. Our results remained significant even after excluding the impact of head motion, positive and negative affect and depression. Taken together, this study reveals that fALFF and RSFC are functional neural markers of trait optimism and provides a brain-personality-symptom pathway for protection against anxiety in which fALFF and RSFC affect anxiety through trait optimism.

Neuroanatomical correlates of grit: Growth mindset mediates the association between gray matter structure and trait grit in late adolescence

There is a long-standing interest in exploring the factors related to student achievement. As a newly explored personality trait, grit is defined as a person's tendency to pursue long-term goals with continual perseverance and passion, and grit plays a critical role in student achievement. Increasing evidence has shown that growth mindset, the belief that one's basic abilities are malleable and can be developed through effort, is a potential factor for cultivating grit. However, less is known about the association between grit and the brain and the role of growth mindset in this association. Here, we utilized voxel-based morphometry to examine the neuroanatomical correlates of grit in 231 healthy adolescent students by performing structural magnetic resonance imaging. The whole-brain regression analyses revealed that the regional gray matter volume (rGMV) in the left dorsolateral prefrontal cortex (DLPFC) negatively predicted grit. In contrast, the rGMV in the right putamen positively predicted grit. Furthermore, mediating analyses suggested that growth mindset served as a mediator in the association between left DLPFC volume and grit. Our results persisted even after controlling for the influences of self-control and delayed gratification. Overall, our study presents novel evidence for the neuroanatomical basis of grit and highlights that growth mindset might play an essential role in cultivating a student's grit level.

Predicting personality from network-based resting-state functional connectivity

Personality is associated with variation in all kinds of mental faculties, including affective, social, executive, and memory functioning. The intrinsic dynamics of neural networks underlying these mental functions are reflected in their functional connectivity at rest (RSFC). We, therefore, aimed to probe whether connectivity in functional networks allows predicting individual scores of the five-factor personality model and potential gender differences thereof. We assessed nine meta-analytically derived functional networks, representing social, affective, executive, and mnemonic systems. RSFC of all networks was computed in a sample of 210 males and 210 well-matched females and in a replication sample of 155 males and 155 females. Personality scores were predicted using relevance vector machine in both samples. Cross-validation prediction accuracy was defined as the correlation between true and predicted scores. RSFC within networks representing social, affective, mnemonic, and executive systems significantly predicted self-reported levels of Extraversion, Neuroticism, Agreeableness, and Openness. RSFC patterns of most networks, however, predicted personality traits only either in males or in females. Personality traits can be predicted by patterns of RSFC in specific functional brain networks, providing new insights into the neurobiology of personality. However, as most associations were gender-specific, RSFC-personality relations should not be considered independently of gender.

Focusing on the Differences of Resting-State Brain Networks, Using a Data-Driven Approach to Explore the Functional Neuroimaging Characteristics of Extraversion Trait

In recent years, functional magnetic resonance imaging (fMRI) has been widely used in studies that explored the personality-brain association. Researches on personality neuroscience have the potential to provide personality psychology with explanatory models—that is, why people differ from each other rather than how they differ from each other (DeYoung and Gray, 2009). As one of the most important dimensions of personality traits, extraversion is the most stable core and a universal component in personality theory. The aim of the present study was to employ a fully data-driven approach to study the brain mechanism of extraversion in a sample of 111 healthy adults. The Eysenck Personality Questionnaire (EPQ) was used to measure the personality characteristics of all the subjects. We investigated whether the subjects can be grouped into highly homogeneous communities according to the characteristics of their intrinsic connectivity networks (ICNs). The resultant subjects communities and the representative characteristics of ICNs were then associated to personality concepts. Finally, we found one ICN (salience network) whose subject community profiles exhibited significant associations with Extraversion trait.

Grit and the brain: spontaneous activity of the dorsomedial prefrontal cortex mediates the relationship between the trait grit and academic performance

As a personality trait, grit involves the tendency to strive to achieve long-term goals with continual passion and perseverance and plays an extremely crucial role in personal achievement. However, the neural mechanisms of grit remain largely unknown. In this study, we aimed to explore the association between grit and the fractional amplitude of low-frequency fluctuations (fALFF) in 217 healthy adolescent students using resting-state functional magnetic resonance imaging (RS-fMRI). We found that an individual’s grit was negatively related to the regional fALFF in the right dorsomedial prefrontal cortex (DMPFC), which is involved in self-regulation, planning, goal setting and maintenance, and counterfactual thinking for reflecting on past failures. The results persisted even after the effects of general intelligence and the ‘big five’ personality traits were adjusted for. More importantly, the fALFF of the right DMPFC played a mediating role in the association between grit and academic performance. Overall, these findings reveal regional fALFF as a neural basis of grit and highlight the right DMPFC as a neural link between grit and academic performance.

Neural basis of individual differences in the response to mental stress: a magnetoencephalography study

Stress is a risk factor for the onset of mental disorders. Although stress response varies across individuals, the mechanism of individual differences remains unclear. Here, we investigated the neural basis of individual differences in response to mental stress using magnetoencephalography (MEG). Twenty healthy male volunteers completed the Temperament and Character Inventory (TCI). The experiment included two types of tasks: a non-stress-inducing task and a stress-inducing task. During these tasks, participants passively viewed non-stress-inducing images and stress-inducing images, respectively, and MEG was recorded. Before and after each task, MEG and electrocardiography were recorded and subjective ratings were obtained. We grouped participants according to Novelty seeking (NS) - tendency to be exploratory, and Harm avoidance (HA) - tendency to be cautious. Participants with high NS and low HA (n = 10) assessed by TCI had a different neural response to stress than those with low NS and high HA (n = 10). Event-related desynchronization (ERD) in the beta frequency band was observed only in participants with high NS and low HA in the brain region extending from Brodmann's area 31 (including the posterior cingulate cortex and precuneus) from 200 to 350 ms after the onset of picture presentation in the stress-inducing task. Individual variation in personality traits (NS and HA) was associated with the neural response to mental stress. These findings increase our understanding of the psychological and neural basis of individual differences in the stress response, and will contribute to development of the psychotherapeutic approaches to stress-related disorders.

Delay discounting is associated with the fractional amplitude of low-frequency fluctuations and resting-state functional connectivity in late adolescence

As a component of self-regulation, delay discounting (DD) refers to an individual’s tendency to prefer smaller-but-sooner rewards over larger-but-later rewards and plays an essential role in many aspects of human behavior. Although numerous studies have examined the neural underpinnings of DD in adults, there are far fewer studies focusing on the neurobiological correlates underlying DD in adolescents. Here, we investigated the associations between individual differences in DD and the fractional amplitude of low-frequency fluctuations (fALFF) and resting-state functional connectivity (RSFC) in 228 high school students using resting-state functional magnetic resonance imaging (RS-fMRI). At the regional level, we found an association between higher DD and greater fALFF in the dorsal anterior cingulate cortex (dACC), which is involved in conflict monitoring and strategy adaptation. At the connectivity level, DD was positively correlated with the RSFC between the dACC and the left dorsolateral prefrontal cortex (DLPFC), a critical functional circuit in the cognitive control network. Furthermore, these effects persisted even after adjusting for the influences of general intelligence and trait impulsivity. Overall, this study reveals the fALFF and RSFC as the functional brain basis of DD in late adolescents, aiding to strengthen and corroborate our understanding of the neural underpinnings of DD.

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz) and slow-2 (0.198–0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.