Brain correlates of pro-social personality traits: a voxel-based morphometry study

The Brain That Understands Diversity: A Pilot Study Focusing on the Triple Network

Background/Objectives: Interest in diversity is growing worldwide. Today, an understanding and social acceptance of diverse people is becoming increasingly important. Therefore, in this study, we aimed to clarify the relationship between an individual's gray matter volume (GMV), which is thought to reflect brain health, and their understanding of diversity (gender, sexuality (LGBTQ), and origin). Methods: GMV was determined as the value of the Gray Matter Brain Healthcare Quotient (GM-BHQ) based on MRI image analysis. Meanwhile, participants' understanding and acceptance of diversity was calculated based on their answers to the psychological questions included in the World Values Survey Wave 7 (WVS7). Results: Our analysis indicated that, in the group of participants with the highest understanding of diversity (PHUD. n = 11), not only the GMV at the whole brain level (t = 2.587, p = 0.027, Cohen's d = 0.780) but also the GMV of the central executive network (CEN: t = 2.700, p= 0.022, Cohen's d = 0.814) and saliency network (SN: t = 3.100, p = 0.011, Cohen's d = 0.935) were shown to be significantly higher than the theoretical value estimated from sex, age, and BMI at the 5% level. In addition, the GMV of the default mode network (DMN: t = 2.063, p = 0.066, Cohen's d = 0.622) was also higher than the theoretical value at the 10% level. Meanwhile, in the group of others (n = 10), there was no significant difference from the theoretical value. These differences between PHUD and others were also observed when comparing the two with and without controlling for educational and occupational covariates at the 5% or 10% levels. Conclusions: These results suggest that understanding diversity requires a healthy brain, centered on three networks that govern rational judgment, emotion regulation, other-awareness, self-awareness, and the valuing of actions. This is the first study to show that brain structure is related to an understanding and acceptance of the diversity of people.

Brain dynamics and personality: a preliminary study

Personality can be considered a system characterized by complex dynamics that are extremely adaptive depending on continuous interactions with the environment and situations. The present preliminary study explores the dynamic interplay between brain flexibility and personality by taking the dynamic approach to personality into account, thereby drawing from Cloninger's psychobiological model. 46 healthy individuals were recruited, and their brain dynamics were assessed using magnetoencephalography (MEG) during the resting state. We identified brain activation patterns and measured brain flexibility by employing the theory of neuronal avalanches. Subsequent correlation analyses revealed a significant positive association between brain flexibility and cooperativeness, thus highlighting the role of brain reconfiguration tendencies in fostering openness, tolerance, and empathy towards others. Additionally, this preliminary finding suggests a neurobiological basis for adaptive social behaviors. Although the results are preliminary, this study provides initial insights into the intricate relationship between brain dynamics and personality, thus laying the groundwork for further research in this emerging field using a dynamic network analysis of the functional activity of the brain.

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.

Revised Temperament and Character Inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years

Introduction

Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer's disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study.

Methods

Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to AD-dementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD.

Results

Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors.

Conclusion

The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline.

Empathy deficits, callous-unemotional traits and structural underpinnings in autism spectrum disorder and conduct disorder youth

Distinct empathy deficits are often described in patients with conduct disorder (CD) and autism spectrum disorder (ASD) yet their neural underpinnings and the influence of comorbid Callous-Unemotional (CU) traits are unclear. This study compares the cognitive (CE) and affective empathy (AE) abilities of youth with CD and ASD, their potential neuroanatomical correlates, and the influence of CU traits on empathy. Adolescents and parents/caregivers completed empathy questionnaires (N = 148 adolescents, mean age = 15.16 years) and T1 weighted images were obtained from a subsample (N = 130). Group differences in empathy and the influence of CU traits were investigated using Bayesian analyses and Voxel-Based Morphometry with Threshold-Free Cluster Enhancement focusing on regions involved in AE (insula, amygdala, inferior frontal gyrus and cingulate cortex) and CE processes (ventromedial prefrontal cortex, temporoparietal junction, superior temporal gyrus, and precuneus). The ASD group showed lower parent-reported AE and CE scores and lower self-reported CE scores while the CD group showed lower parent-reported CE scores than controls. When accounting for the influence of CU traits no AE deficits in ASD and CE deficits in CD were found, but CE deficits in ASD remained. Across all participants, CU traits were negatively associated with gray matter volumes in anterior cingulate which extends into the mid cingulate, ventromedial prefrontal cortex, and precuneus. Thus, although co-occurring CU traits have been linked to global empathy deficits in reports and underlying brain structures, its influence on empathy aspects might be disorder-specific. Investigating the subdimensions of empathy may therefore help to identify disorder-specific empathy deficits.

"Nothing to see here": No structural brain differences as a function of the Big Five personality traits from a systematic review and meta-analysis

Personality reflects social, affective, and cognitive predispositions that emerge from genetic and environmental influences. Contemporary personality theories conceptualize a Big Five Model of personality based on the traits of neuroticism, extraversion, agreeableness, conscientiousness, and openness to experience. Starting around the turn of the millennium, neuroimaging studies began to investigate functional and structural brain features associated with these traits. Here, we present the first study to systematically evaluate the entire published literature of the association between the Big Five traits and three different measures of brain structure. Qualitative results were highly heterogeneous, and a quantitative meta-analysis did not produce any replicable results. The present study provides a comprehensive evaluation of the literature and its limitations, including sample heterogeneity, Big Five personality instruments, structural image data acquisition, processing, and analytic strategies, and the heterogeneous nature of personality and brain structures. We propose to rethink the biological basis of personality traits and identify ways in which the field of personality neuroscience can be strengthened in its methodological rigor and replicability.

The Interaction Between Caudate Nucleus and Regions Within the Theory of Mind Network as a Neural Basis for Social Intelligence

The organization of socio-cognitive processes is a multifaceted problem for which many sophisticated concepts have been proposed. One of these concepts is social intelligence (SI), i.e., the set of abilities that allow successful interaction with other people. The theory of mind (ToM) human brain network is a good candidate for the neural substrate underlying SI since it is involved in inferring the mental states of others and ourselves and predicting or explaining others’ actions. However, the relationship of ToM to SI remains poorly explored. Our recent research revealed an association between the gray matter volume of the caudate nucleus and the degree of SI as measured by the Guilford-Sullivan test. It led us to question whether this structural peculiarity is reflected in changes to the integration of the caudate with other areas of the brain associated with socio-cognitive processes, including the ToM system. We conducted seed-based functional connectivity (FC) analysis of resting-state fMRI data for 42 subjects with the caudate as a region of interest. We found that the scores of the Guilford-Sullivan test were positively correlated with the FC between seeds in the right caudate head and two clusters located within the right superior temporal gyrus and bilateral precuneus. Both regions are known to be nodes of the ToM network. Thus, the current study demonstrates that the SI level is associated with the degree of functional integration between the ToM network and the caudate nuclei.

Interactions between Personality, Depression, Anxiety and Cognition to Understand Early Stage of Alzheimer's Disease

The multifaceted nature of Alzheimer's disease (AD) and Mild cognitive impairment (MCI) can lead to wide inter-individual differences in disease manifestation in terms of brain pathology and cognition. The lack of understanding of phenotypic diversity in AD arises from a difficulty in understanding the integration of different levels of network organization (i.e. genes, neurons, synapses, anatomical regions, functions) and in inclusion of other information such as neuropsychiatric characteristics, personal history, information regarding general health or subjective cognitive complaints in a coherent model. Non-cognitive factors, such as personality traits and behavioral and psychiatric symptoms, can be informative markers of early disease stage. It is known that personality can affect cognition and behavioral symptoms. The aim of the paper is to review the different types of interactions existing between personality, depression/anxiety, and cognition and cognitive disorders at behavioral and brain/genetic levels.

Interplay Between the Salience and the Default Mode Network in a Social-Cognitive Task Toward a Close Other

Social cognition relies on two main subsystems to construct the understanding of others, which are sustained by different social brain networks. One of these social networks is the default mode network (DMN) associated with the socio-cognitive subsystem (i.e., mentalizing), and the other is the salience network (SN) associated with the socio-affective route (i.e., empathy). The DMN and the SN are well-known resting state networks that seem to constitute a baseline for the performance of social tasks. We aimed to investigate both networks' functional connectivity (FC) pattern in the transition from resting state to social task performance. A sample of 38 participants involved in a monogamous romantic relationship completed a questionnaire of dyadic empathy and underwent an fMRI protocol that included a resting state acquisition followed by a task in which subjects watched emotional videos of their romantic partner and elaborated on their partner's (Other condition) or on their own experience (Self condition). Independent component and ROI-to-ROI correlation analysis were used to assess alterations in task-independent (Rest condition) and task-dependent (Self and Other conditions) FC. We found that the spatial FC maps of the DMN and SN evidenced the traditional regions associated with these networks in the three conditions. Anterior and posterior DMN regions exhibited increased FC during the social task performance compared to resting state. The Other condition revealed a more limited SN's connectivity in comparison to the Self and Rest conditions. The results revealed an interplay between the main nodes of the DMN and the core regions of the SN, particularly evident in the Self and Other conditions.

Little evidence for associations between the Big Five personality traits and variability in brain gray or white matter

Attempts to link the Big Five personality traits of Openness-to-Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism with variability in trait-like features of brain structure have produced inconsistent results. Small sample sizes and heterogeneous methodology have been suspected in driving these inconsistencies. Here, using data collected from 1,107 university students (636 women, mean age 19.69 ​± ​1.24 years), representing the largest sample to date of unrelated individuals, we tested for associations between the Big Five personality traits and measures of cortical thickness and surface area, subcortical volume, and white matter microstructural integrity. In addition to replication analyses based on a prior study, we conducted exploratory whole-brain analyses. Four supplementary analyses were also conducted to examine 1) possible associations with lower-order facets of personality; 2) modulatory effects of sex; 3) effect of controlling for non-target personality traits; and 4) parcellation scheme effects. Our analyses failed to identify significant associations between the Big Five personality traits and brain morphometry, except for a weak association between greater surface area of the superior temporal gyrus and lower conscientiousness scores. As the latter association is not supported by previous studies, it should be treated with caution. Our supplementary analyses mirrored these predominantly null findings, suggesting they were not substantively biased by our analytic choices. Collectively, these results indicate that if there are associations between the Big Five personality traits and brain structure, they are likely of very small effect size and will require very large samples for reliable detection.

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.

Diurnal Preference and Grey Matter Volume in a Large Population of Older Adults: Data from the UK Biobank

Eveningness (a diurnal preference for evening time) is associated with a number of negative health outcomes and risk and prevalence for psychiatric disorder. Our understanding of the anatomical substrates of diurnal preference, however, is limited. The current study used Voxel-Based Morphometry to compare grey matter volume in a large sample (N = 3730) of healthy adults determined by questionnaire to be either definite morning-type or definite evening-type. Eveningness was associated with increased grey matter volume in precuneus, brain regions implicated in risk and reward processing (bilateral nucleus accumbens, caudate, putamen and thalamus) and orbitofrontal cortex. These results indicate an anatomical-basis for diurnal preference which may underlie reported differences in behaviour and brain function observed in these individuals.

Less agreeable, better preserved? A PET amyloid and MRI study in a community-based cohort

The relationship between personality profiles and brain integrity in old age is still a matter of debate. We examined the association between Big Five factor and facet scores and MRI brain volume changes on a 54-month follow-up in 65 elderly controls with 3 neurocognitive assessments (baseline, 18 months, and 54 months), structural brain MRI (baseline and 54 months), brain amyloid PET during follow-up, and APOE genotyping. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE ε4 allele, and cognitive evolution. Lower agreeableness factor scores (and 4 of its facets) were associated with lower volume loss in the hippocampus, entorhinal cortex, amygdala, mesial temporal lobe, and precuneus bilaterally. Higher openness factor scores (and 2 of its facets) were also associated with lower volume loss in the left hippocampus. Our findings persisted when adjusting for confounders in multivariable models. These data suggest that the combination of low agreeableness and high openness is an independent predictor of better preservation of brain volume in areas vulnerable to neurodegeneration.

Personality traits and negative affect mediate the relationship between cortical thickness of superior frontal cortex and aggressive behavior

Aggression reflects the psychological and physical behavior that perpetrator intends to harm victim. Initiation of aggression is influenced by the distal factors (e.g. personality) and proximate causes (e.g. affect) of perpetrator. However, few studies explored the brain structural basis of relationship between these traits and aggressive behavior. In this study, we first explored the association between cortical thickness and aggression in a large young adult sample from the Human Connectome Project. Results found aggressive behavior assessed by the Adult Self-Report was positively correlated with cortical thickness in left superior frontal gyrus (SFG), which was implicated in emotion regulation and executive function. Then, mediation analyses with distal and proximate factors separately showcased that the association between the left SFG thickness and aggressive behavior was partially mediated by negative affect (anger and sadness), and fully mediated by personality traits (agreeableness and neuroticism). Taken together, these experimental findings established dorsal prefrontal cortex as the key region in generating aggressive behavior, and gave a neutral explanation for why individuals with high negative affect and neuroticism exhibit more aggression. This study implicated the possible targeted brain region and behavioral intervention for such at-risk individuals initiating violence.

Inward versus reward: white matter pathways in extraversion

The trait of extraversion is one of the longest-standing domains that captures the social dimension of personality and can potentially explain the covariation of a wide variety of behaviors. To date, there is a growing recognition that human behavior should be specified not only through the psychological mechanisms underlying each trait but also through their underlying neurobehavioral systems. While imaging studies have revealed important initial insights into the structural and functional neural correlates of extraversion, current knowledge about the relationships between extraversion and brain structures is still rather limited, especially with regard to the relationship between extraversion and white matter (WM). In this study, we aimed to investigate WM microstructure in extraversion in greater depth. Thirty-five healthy volunteers (21 women; mean age 35) underwent magnetic resonance imaging, as a part of a larger project aimed at investigating the longitudinal effect of motor training. WM integrity was assessed using the diffusion tensor imaging technique combining multiple diffusion tensor measures. Extraversion was assessed by the Eysenck Personality Questionnaire-Revised. Voxelwise correlation analyses between fractional anisotropy, axial diffusivities, and radial diffusivities maps and extraversion score showed decreased connectivity in the right inferior fronto-occipital fasciculus and forceps major among individuals who had high extraversion ratings. In conclusion, individual differences in extraversion may reflect differential organization of the WM tracts connecting frontal cortex, temporal, and occipital areas, which are related to socioemotional and control functions.

Brain gray matter correlates of extraversion: A systematic review and meta-analysis of voxel-based morphometry studies

Extraversion is a fundamental personality dimension closely related to an individual's life outcomes and mental health. Although an increasing number of studies have attempted to identify the neurostructural markers of extraversion, the results have been highly inconsistent. The current study aimed to achieve a comprehensive understanding of brain gray matter (GM) correlates of extraversion with a systematic review and meta-analysis approach. Our review showed relatively high interstudy heterogeneity among previous findings. Our meta-analysis of whole-brain voxel-based morphometry studies revealed that extraversion was stably associated with six core brain regions. Additionally, meta-regression analyses identified brain regions where the associations of extraversion with GM volume were modulated by gender and age. The relationships between extraversion and GM structures were discussed based on three extraversion-related functional systems. Furthermore, we explained the gender and age effects. Overall, our study is the first to reveal a comprehensive picture of brain GM correlates of extraversion, and the findings may be useful for the selection of targeted brain areas for extraversion interventions.

Cortical morphometry of the five-factor model of personality: findings from the Human Connectome Project full sample

This study is a replication of an existing large study (N = 507) on the surface-based morphometric correlates of five-factor model (FFM) personality traits. The same methods were used as the original study in another large sample drawn from the same population (N = 597) with results then being aggregated from both samples (N = 1104), providing the largest investigation into the neuroanatomical correlates of FFM personality traits to date. Clusters of association between brain morphometry and each FFM trait are reported. For neuroticism, agreeableness, openness and conscientiousness clusters of association were found in the dorsolateral prefrontal cortex for at least one morphometric index. Morphometry in various other regions was also associated with each personality trait. While some regions found in the original study were confirmed in the replication and full samples, others were not, highlighting the importance of replicating even high-quality, well-powered studies. Effect sizes were very similar in the replication and whole samples as those found in the original study. As a whole, the current results provide the strongest evidence to date on the neuroanatomical correlates of personality and highlights challenges in using this approach to understanding the neural correlates of personality.

Structural Correlates of Personality Dimensions in Healthy Aging and MCI

The revised NEO Personality Inventory (NEOPI-R), popularly known as the five-factor model, defines five personality factors: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. The structural correlates of these personality factors are still a matter of debate. In this work, we examine the impact of subtle cognitive deficits on structural substrates of personality in the elderly using DTI derived white matter (WM) integrity measure, Fractional Anisotropy (FA). We employed canonical correlation analysis (CCA) to study the relationship between personality factors of the NEOPI-R and FA measures in two population groups: healthy controls and MCI. Agreeableness was the only personality factor to be associated with FA patterns in both groups. Openness was significantly related to FA data in the MCI group and the inverse was true for Conscientiousness. Furthermore, we generated saliency maps using bootstrapping strategy which revealed a larger number of positive correlations in healthy aging in contrast to the MCI status. The MCI group was found to be associated with a predominance of negative correlations indicating that higher Agreeableness and Openness scores were mostly related to lower FA values in interhemispheric and cortico-spinal tracts and a limited number of higher FA values in cortico-cortical and cortico-subcortical connection. Altogether these findings support the idea that WM microstructure may represent a valid correlate of personality dimensions and also indicate that the presence of early cognitive deficits led to substantial changes in the associations between WM integrity and personality factors.

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.

Personality Traits in Patients with Neuroepithelial Tumors - A Prospective Study

Aim of this study was to analyze personality traits in patients with neuroepithelial brain tumors. Personality alteration is a common feature in brain tumor patients, but not much is known about associations between specific personality changes and brain tumors. We assessed potential factors influencing personality such as tumor location, tumor grade and tumor volume. Mini-mental state examination (MMSE), Beck's Depression Inventory II (BDI-II), and the NEO Five-Factor Inventory (NEO-FFI) for the five factors of personality were acquired. Patients had lower scores regarding the factor openness and higher scores regarding the BDI-II compared to the norm population. No significant influencing factors (tumor entity, location) were found regarding personality traits. Neuroticism was associated with depression, whereas extraversion showed an opposed association. Patients with intrinsic brain tumors have differences in personality traits compared to the control population, with an emphasis on the factor openness. No significant confounding factors like tumor grade, entity, or location were found for personality traits.

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.

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience

Personality neuroscience aims to find associations between brain measures and personality traits. Findings to date have been severely limited by a number of factors, including small sample size and omission of out-of-sample prediction. We capitalized on the recent availability of a large database, together with the emergence of specific criteria for best practices in neuroimaging studies of individual differences. We analyzed resting-state functional magnetic resonance imaging data from 884 young healthy adults in the Human Connectome Project (HCP) database. We attempted to predict personality traits from the "Big Five", as assessed with the NEO-FFI test, using individual functional connectivity matrices. After regressing out potential confounds (such as age, sex, handedness and fluid intelligence), we used a cross-validated framework, together with test-retest replication (across two sessions of resting-state fMRI for each subject), to quantify how well the neuroimaging data could predict each of the five personality factors. We tested three different (published) denoising strategies for the fMRI data, two inter-subject alignment and brain parcellation schemes, and three different linear models for prediction. As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 h of data), with the analysis pipeline that yielded the highest predictability overall. Across all results (test/retest; 3 denoising strategies; 2 alignment schemes; 3 models), Openness to experience emerged as the only reliably predicted personality factor. Using the full hour of resting-state data and the best pipeline, we could predict Openness to experience (NEOFAC_O: r=0.24, R2=0.024) almost as well as we could predict the score on a 24-item intelligence test (PMAT24_A_CR: r=0.26, R2=0.044). Other factors (Extraversion, Neuroticism, Agreeableness and Conscientiousness) yielded weaker predictions across results that were not statistically significant under permutation testing. We also derived two superordinate personality factors ("α" and "β") from a principal components analysis of the NEO-FFI factor scores, thereby reducing noise and enhancing the precision of these measures of personality. We could account for 5% of the variance in the β superordinate factor (r=0.27, R2=0.050), which loads highly on Openness to experience. We conclude with a discussion of the potential for predicting personality from neuroimaging data and make specific recommendations for the field.

Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality

The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project.

Neuroticism was associated with thicker cortex and smaller area and folding in prefrontal–temporal regions. Extraversion was linked to thicker pre-cuneus and smaller superior temporal cortex area. Openness was linked to thinner cortex and greater area and folding in prefrontal–parietal regions. Agreeableness was correlated to thinner prefrontal cortex and smaller fusiform gyrus area. Conscientiousness was associated with thicker cortex and smaller area and folding in prefrontal regions. These findings demonstrate that anatomical variability in prefrontal cortices is linked to individual differences in the socio-cognitive dispositions described by the FFM. Cortical thickness and surface area/folding were inversely related each others as a function of different FFM traits (neuroticism, extraversion and consciousness vs openness), which may reflect brain maturational effects that predispose or protect against psychiatric disorders.

Is there a T.R.U.M.P. brain? Implications for mental health and world peace

HIGHLIGHTS

Specific mind-brain processes are associated with political attitudes.The risks of a T.R.U.M.P. mindset are highlighted.An alternative G.A.N.D.H.I. mindset is suggested.

ABSTRACT

Neuroscientists have begun to investigate whether different political attitudes are associated with specific mind-brain markers. In this article, we build on political neuroscience research to briefly illustrate the structure and function of a Threatening, Reactionary, Unforgiving, Machiavellian, and Partisan (T.R.U.M.P.) mindset. Additionally, we discussed, building on neuroscience and clinical evidence, how to counteract the T.R.U.M.P. mindset.

The neuroanatomical delineation of agentic and affiliative extraversion

Extraversion is a fascinating personality dimension that consists of two major components, agentic extraversion and affiliative extraversion. Agentic extraversion involves incentive motivation and is expressed as a tendency toward assertiveness, persistence, and achievement. Affiliative extraversion involves the positive emotion of social warmth and is expressed as a tendency toward amicability, gregariousness, and affection. Here we investigate the neuroanatomical correlates of the personality traits of agentic and affiliative extraversion using the Multidimensional Personality Questionnaire Brief Form, structural magnetic resonance imaging, and voxel-based morphometry in a sample of 83 healthy adult volunteers. We found that trait agentic extraversion and trait affiliative extraversion were each positively associated with the volume of the medial orbitofrontal cortex bilaterally (t's ≥ 2.03, r's ≥ .23, p's < .05). Agentic extraversion was specifically and positively related to the volume of the left parahippocampal gyrus (t = 4.08, r = .21, p < .05), left cingulate gyrus (t = 4.75, r = .28, p < .05), left caudate (t = 4.29, r = .24, p < .05), and left precentral gyrus (t = 4.00, r = .18, p < .05) in males and females, and the volume of the right nucleus accumbens in males (t = 2.92, r = .20, p < .05). Trait affiliative extraversion was not found to be associated with additional regions beyond the medial orbitofrontal cortex. The findings provide the first evidence of a neuroanatomical dissociation between the personality traits of agentic and affiliative extraversion in healthy adults.

Extraversion mediates the relationship between structural variations in the dorsolateral prefrontal cortex and social well-being

Social well-being reflects the appraisal of one's circumstance and functioning in society, which is crucial for individuals' mental and physical health. However, little is known about the neural processes associated with social well-being. In this study, we used voxel-based morphometry (VBM) to identify the brain regions underlying individual differences in social well-being, as measured by the Social Well-being Scale (SWBS), in a large sample of young healthy adults. We found that social well-being was negatively correlated with gray matter volume in left mid-dorsolateral prefrontal cortex (mid-DLPFC) that is implicated in executive functioning, emotional regulation and social reasoning. The results remained significant even after controlling for the effect of socioeconomic status. Furthermore, although basic personality factors such as neuroticism, extraversion, and conscientiousness (as measured by the NEO Personality Inventory) all contributed to social well-being, only extraversion acted as a mediational mechanism underlying the association between the left mid-DLPFC volume and social well-being. Together, our findings provide the first evidence for the structural basis of individual differences in social well-being, and suggest that the personality trait of extraversion might play an important role in the acquisition and process of social well-being.

Relationship between personality and gray matter volume in healthy young adults: a voxel-based morphometric study

This study aims to investigate the neurostructural foundations of the human personality in young adults. High-resolution structural T1-weighted MR images of 71 healthy young individuals were processed using voxel-based morphometric (VBM) approach. Multiple regression analyses were performed to identify the associations between personality traits and gray matter volume (GMV). The Eysenck Personality Questionnaire-Revised, Short Scale for Chinese was chosen to assess the personality traits. This scale includes four dimensions, namely, extraversion, neuroticism, psychoticism, and lie. Particularly, we studied on two dimensions (extraversion and neuroticism) of Eysenck’s personality. Our results showed that extraversion was negatively correlated with GMV of the bilateral amygdala, the bilateral parahippocampal gyrus, the right middle temporal gyrus, and the left superior frontal gyrus, all of which are involved in emotional and social cognitive processes. These results might suggest an association between extraversion and affective processing. In addition, a positive correlation was detected between neuroticism and GMV of the right cerebellum, a key brain region for negative affect coordination. Meanwhile, a negative association was revealed between GMV of the left superior frontal gyrus and neuroticism. These results may prove that neuroticism is related to several brain regions involved in regulating negative emotions. Based on those findings, we concluded that brain regions involved in social cognition and affective process accounted for modulation and shaping of personality traits among young individuals. Results of this study may serve as a basis for elucidating the anatomical factors of personality.