Narcissistic personality traits and prefrontal brain structure

The resting-state brain activity and connectivity mediates the effect of overt narcissism on negative physical self

Overt narcissism is a stable personality trait in which individuals maintain a relatively positive self-image through self-improvement. Previous studies have suggested that examining the neurobiological processes behind personality could help to understand the mechanism by which the personality acts as a risk or protective factor. However, there is a lack of research investigating the neural mechanisms underlying the influence of overt narcissism on negative physical self (NPS). This study evaluated the resting state brain activity (fractional amplitude of low-frequency fluctuations, fALFF) and connectivity (functional connectivity, FC) of 1647 college students. Whole brain correlation analysis showed that overt narcissism was positively correlated with fALFF in the left insula, left precentral gyrus (PreCG) and bilateral superior temporal gyrus (STG). Moreover, overt narcissism exhibited a significant positive correlation with the right STG-PreCG connectivity, and also was significantly positively correlated with FC between the left STG and posterior cingulate gyrus, the left orbitofrontal cortex, the right inferior frontal gyrus and the right thalamus. The results of mediating analysis showed that fALFF in the left PreCG and the right STG-PreCG connectivity partially mediated the effects of overt narcissism on general and facial appearance of NPS, respectively. This study constructed a model (i.e., overt narcissism→brain regions/FC→NPS), providing neurobiological evidence for the relationship between overt narcissism and NPS.

Neural rhythms of narcissism: Facets of narcissism are associated with different neural sources in resting-state EEG

Trait narcissism is characterized by significant heterogeneity across individuals. Despite advances in the conceptualization of narcissism, including the increasing recognition that narcissism is a multidimensional construct, the sources of this heterogeneity remain poorly understood. Here, we used a neural trait approach to help better understand "how," and shed light on "why," individuals vary in facets of trait narcissism. Participants (N = 58) first completed personality measures, including the Narcissistic Personality Inventory (NPI), and then in a second session sat passively while resting-state electroencephalography (rs-EEG) was recorded. We then regressed source-localized rs-EEG activity on the distinct facets of narcissism: Grandiose Exhibitionism (GE), Entitlement/Exploitativeness (EE), and Leadership/Authority (LA). Results revealed that each facet was associated with different (though sometimes overlapping) neural sources. Specifically, GE was associated with reduced activation in the dorsomedial prefrontal cortex (DMPFC). EE was associated with reduced activation in the DMPFC and right lateral PFC. LA was associated with increased activation in the left anterior temporal cortex. These findings support the idea that trait narcissism is a multidimensional construct undergirded by individual differences in neural regions related to social cognition (the DMPFC), self-regulation (right lateral PFC), and self-referential processing (left anterior temporal cortex).

Narcissus reflected: Grey and white matter features joint contribution to the default mode network in predicting narcissistic personality traits

Despite the clinical significance of narcissistic personality, its neural bases have not been clarified yet, primarily because of methodological limitations of the previous studies, such as the low sample size, the use of univariate techniques and the focus on only one brain modality. In this study, we employed for the first time a combination of unsupervised and supervised machine learning methods, to identify the joint contributions of grey matter (GM) and white matter (WM) to narcissistic personality traits (NPT). After preprocessing, the brain scans of 135 participants were decomposed into eight independent networks of covarying GM and WM via parallel ICA. Subsequently, stepwise regression and Random Forest were used to predict NPT. We hypothesized that a fronto-temporo parietal network, mainly related to the default mode network, may be involved in NPT and associated WM regions. Results demonstrated a distributed network that included GM alterations in fronto-temporal regions, the insula and the cingulate cortex, along with WM alterations in cerebellar and thalamic regions. To assess the specificity of our findings, we also examined whether the brain network predicting narcissism could also predict other personality traits (i.e., histrionic, paranoid and avoidant personalities). Notably, this network did not predict such personality traits. Additionally, a supervised machine learning model (Random Forest) was used to extract a predictive model for generalization to new cases. Results confirmed that the same network could predict new cases. These findings hold promise for advancing our understanding of personality traits and potentially uncovering brain biomarkers associated with narcissism.

The Dark Tetrad: analysis of profiles and relationship with the Big Five personality factors

The Dark Tetrad (DT) is composed of the traits of Narcissism, Machiavellianism, Psychopathy, and Sadism. Most studies analyzing the DT have employed a variable-centered approach, analyzing the traits separately. In the present study, we treat DT as a whole, adopting a person-centered approach. We analyzed different homogeneous subgroups of individuals characterized by specific DT profiles, aiming to examine their relationship with Big Five personality factors. A sample of 1149 participants (50.1% women, 18-79 years) completed The Short Dark Triad and the Assessment of Sadistic Personality instrument to assess DT, while the Mini-IPIP was used to assess the Big Five personality factors. Cluster analysis yielded five groups: Narcissism, Machiavellianism, Mean DT, Low DT, and High DT group. The main results showed that the High DT group was distinguished by higher levels of extraversion and lower levels of agreeableness and conscientiousness (compared with the Low DT group). Moreover, the Narcissism group was characterized by higher scores on emotional stability, openness to experience, and extraversion. Finally, distribution according to gender varied across DT groups (more men than women in the High DT group and the opposite in the Low DT group). Limitations and future lines of research are discussed.

Dark triad personality traits are associated with decreased grey matter volumes in 'social brain' structures

Introduction

Personality traits and the degree of their prominence determine various aspects of social interactions. Some of the most socially relevant traits constitute the Dark Triad - narcissism, psychopathy, and Machiavellianism - associated with antisocial behaviour, disregard for moral norms, and a tendency to manipulation. Sufficient data point at the existence of Dark Triad 'profiles' distinguished by trait prominence. Currently, neuroimaging studies have mainly concentrated on the neuroanatomy of individual dark traits, while the Dark Triad profile structure has been mostly overlooked.

Methods

We performed a clustering analysis of the Dirty Dozen Dark Triad questionnaire scores of 129 healthy subjects using the k-means method. The variance ratio criterion (VRC) was used to determine the optimal number of clusters for the current data. The two-sample t-test within the framework of voxel-based morphometry (VBM) was performed to test the hypothesised differences in grey matter volume (GMV) for the obtained groups.

Results

Clustering analysis revealed 2 groups of subjects, both with low-to-mid and mid-to-high levels of Dark Triad traits prominence. A further VBM analysis of these groups showed that a higher level of Dark Triad traits may manifest itself in decreased grey matter volumes in the areas related to emotional regulation (the dorsolateral prefrontal cortex, the cingulate cortex), as well as those included in the reward system (the ventral striatum, the orbitofrontal cortex).

Discussion

The obtained results shed light on the neurobiological basis underlying social interactions associated with the Dark Triad and its profiles.

Narcissistic Personality Disorder as Prodromal Feature of Early-Onset, GRN-Positive bvFTD: A Case Report

Background

Behavioral variant frontotemporal dementia (bvFTD) typically involves subtle changes in personality that can delay a timely diagnosis.

Objective

Here, we report the case of a patient diagnosed of GRN-positive bvFTD at the age of 52 presenting with a 7-year history of narcissistic personality disorder, accordingly to DSM-5 criteria.

Methods

The patient was referred to neurological and neuropsychological examination. She underwent 3 Tesla magnetic resonance imaging (MRI) and genetic studies.

Results

The neuropsychological examination revealed profound deficits in all cognitive domains and 3T brain MRI showed marked fronto-temporal atrophy. A mutation in the GRN gene further confirmed the diagnosis.

Conclusions

The present case documents an unusual onset of bvFTD and highlights the problematic nature of the differential diagnosis between prodromal psychiatric features of the disease and primary psychiatric disorders. Early recognition and diagnosis of bvFTD can lead to appropriate management and support for patients and their families. This case highlights the importance of considering neurodegenerative diseases, such as bvFTD, in the differential diagnosis of psychiatric disorders, especially when exacerbations of behavioral traits manifest in adults.

Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach

Narcissism is a multifaceted construct often linked to pathological conditions whose neural correlates are still poorly understood. Previous studies have reported inconsistent findings related to the neural underpinnings of narcissism, probably due to methodological limitations such as the low number of participants or the use of mass univariate methods. The present study aimed to overcome the previous methodological limitations and to build a predictive model of narcissistic traits based on neural and psychological features. In this respect, two machine learning-based methods (Kernel Ridge Regression and Support Vector Regression) were used to predict narcissistic traits from brain structural organization and from other relevant normal and abnormal personality features. Results showed that a circuit including the lateral and middle frontal gyri, the angular gyrus, Rolandic operculum, and Heschl's gyrus successfully predicted narcissistic personality traits (p < 0.003). Moreover, narcissistic traits were predicted by normal (openness, agreeableness, conscientiousness) and abnormal (borderline, antisocial, insecure, addicted, negativistic, machiavellianism) personality traits. This study is the first to predict narcissistic personality traits via a supervised machine learning approach. As such, these results may expand the possibility of deriving personality traits from neural and psychological features.

The Neural Correlates of Narcissism: Is There a Connection with Desire for Fame and Celebrity Worship?

(1) Objective: Narcissism is characterized by emotional regulation deficits, a lack of empathy for others, and extreme self-focus. Narcissism has also been linked to an increased desire for fame and celebrity worship. Here, the neuroscience underlying narcissism is examined in order to determine what regions and networks of the brain are altered when non-narcissistic individuals are compared to participants with both grandiose and vulnerable narcissism. (2) Methods: The behavioral relationships between grandiose narcissism and desire for fame and vulnerable narcissism and celebrity worship are explored, along with a possible relationship at the neural level between these constructs. In this paper, we review research demonstrating that increased levels of grandiose narcissism are associated with an increase in obsession with fame, while vulnerable narcissism is associated with celebrity worship. (3) Results: Based on current data, the frontal regions underlie narcissism and also likely underlie celebrity worship and desire for fame. This tenuous conclusion is based on a limited number of studies. (4) Conclusions: The brain areas associated with grandiose narcissism may be associated with an intense desire for fame as well, while brain regions associated with vulnerable narcissism may be similar in celebrity worshipers. Future research studies on the brain that are specifically designed to test these relationships at a neurological level are needed.

Structural connectivity of grandiose versus vulnerable narcissism as models of social dominance and subordination

Social dominance and subordination have been linked to fronto-limbic and fronto-thalamic networks and are related to phenotypes such as grandiose vs. vulnerable narcissistic traits. The latter have been linked to clinical features such as empathy and emotional regulation. In this study we tested the hypotheses that narcissistic traits are associated with white matter integrity in fasciculus uncinate, cingulum, and anterior thalamic radiation (ATR). We applied the Pathological Narcissism Inventory (PNI) to assess narcissistic traits in a sample of 267 psychiatrically healthy individuals. We used 3 T MRI to acquire Diffusion Tensor Imaging data for analysis with TBSS in FSL applying TFCE to test for correlations of fractional anisotropy (FA) and PNI scales. We detected a significant positive correlation of PNI total and FA in the right posterior cingulum. PNI Vulnerability was significantly correlated with FA in the left anterior and right posterior cingulum. We did not find overall correlations with PNI Grandiosity, but additional analyses showed significant effects with FA of ATR. Our results strengthen network models for narcissism underlying both personality variation and pathology. Especially associations of narcissistic vulnerability within fronto-limbic tracts suggest overlaps within neural correlates of related phenotypes like neuroticism, social subordination, and negative emotionality.

Self-Enhancement and the Medial Prefrontal Cortex: The Convergence of Clinical and Experimental Findings

Self-enhancement (SE) is often overlooked as a fundamental cognitive ability mediated via the Prefrontal Cortex (PFC). Here, we present research that establishes the relationship between the PFC, SE, and the potential evolved beneficial mechanisms. Specifically, we believe there is now enough evidence to speculate that SE exists to provide significant benefits and should be considered a normal aspect of the self. Whatever the metabolic or social cost, the upside of SE is great enough that it is a core and fundamental psychological construct. Furthermore, though entirely theoretical, we suggest that a critical reason the PFC has evolved so significantly in Homo sapiens is to, in part, sustain SE. We, therefore, elaborate on its proximate and ultimate mechanisms.

Impact of Early-Commenced and Continued Sports Training on the Precuneus in Older Athletes

Intervention studies on sedentary older adults have demonstrated that commencing physical exercise at an older age has a positive effect on brain structure. Although this suggests that older athletes with lifelong sports training have larger gray matter volume (GMV) in some brain regions compared to age-matched non-athletes, evidence in the literature is scarce. Moreover, it remains unclear whether a larger GMV is associated with training intensity or period of training in life. To address these gaps in the literature, we compared regional brain GMV between 24 older athletes (mean age, 71.4 years; age at the commencement of sports training, 31.2 years, continuous sports training, 40.0 years; current training time, 7.9 h/week) and 24 age-matched non-athletes (mean age, 71.0 years). The period of sports training and the current training time of the athletes were assessed. Both groups were evaluated for physical activity intensity as well as cognitive and motor performance. Although no group differences were noted in cognitive and motor performance, athletes reported higher physical activity intensity than non-athletes. Whole-brain structural analysis revealed a significantly larger GMV in several brain regions in athletes. Notably, the GMV of the precuneus in athletes was positively correlated with earlier commencement of sports training and training duration but was negatively correlated with current training time. Our findings demonstrate that early-commenced and continued sports training predicts structural maintenance of the precuneus in old age. Our results also suggest that excessive training time in old age may have a negative impact on the GMV of the precuneus; thereby delineating how the precuneus is associated with lifelong sports training in older athletes.