New study maps the brain network behind narcissism using advanced machine learning.

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A recent study provides insight into how structural brain networks contribute to narcissistic personality traits. Using advanced machine learning techniques, researchers identified specific patterns in gray and white matter that predict narcissistic tendencies. The results were published recently European Journal of Neuroscience.

Individuals with high levels of narcissism often exhibit a sense of self-importance, an excessive need for praise, and a lack of empathy for others. These traits can significantly affect mental health and interpersonal relationships, leading to various social and personal difficulties. Narcissistic personality disorder, which appears more severe, affects approximately 1% to 15% of the US population in clinical settings and presents a unique challenge in mental health care because of its complex and other personality traits. have overlapping symptoms with disorders of

Despite the prevalence of narcissistic symptoms and NPD, research on their neurological underpinnings is limited. Existing studies focus primarily on gray or white matter separately and often use univariate methods that do not account for complex interactions within the brain. This study aims to fill this gap by examining the joint contribution of gray and white matter to narcissistic traits using multivariate machine learning approaches.

“At the Clinical and Affective Neuroscience Lab, we are interested in creating neuro-predictive models of personality to serve as future guides for clinical classification and prevention of the development of full-blown disease. Personality is its heart. However, our understanding of the neural bases of personality and how personality can be inferred is a long way from our lab trying to,'' said study author Alessandro Grecucci, professor of affective neuroscience and neurotechnology at the University of Trento.

To investigate the neural basis of narcissistic personality traits, the researchers used data from the MPI-Leipzig Mind Brain-Body dataset, which includes MRI and behavioral data from 318 participants. For their analysis, they focused on a subset of 135 healthy individuals, including 64 women and 71 men with an average age of 31.94 years. These participants were selected based on their good health, absence of medication use, and no history of substance abuse or neurological disorders.

Personality traits were assessed using the Personality Styles and Disorders Inventory (PSDI), a validated self-report inventory that measures a variety of personality styles and can identify potential personality disorders. The researchers focused on the narcissistic, histrionic, insecure/precautionary, and paranoid subscales to differentiate the neural networks associated with these traits.

To analyze the data, the team used Parallel Independent Component Analysis (p-ICA), a machine learning technique that identifies independent components in multimodal data. This method allowed them to examine the coherence of gray and white matter. They then applied stepwise regression and random forest regression to predict narcissistic traits based on these brain networks.

The researchers identified eight independent networks in both gray and white matter. Gray matter consists mainly of neuronal cell bodies, dendrites and synapses and is involved in the processing and interpretation of information in the brain. White matter, on the other hand, consists of bundles of myelinated axons that connect different regions of gray matter, facilitating communication between them.

Among these networks, one stood out for its particularly strong association with narcissistic traits. This network encompasses areas of the frontal, temporal, and parietal lobes, including areas involved in social cognition and empathy, such as the superior temporal gyrus, angular gyrus, and middle temporal gyrus. Additionally, it involved white matter regions in the cerebellum and thalamus, which are important for cognitive and emotional processing.

Specifically, gray matter regions that largely overlap with the default mode network (DMN) are identified. The DMN is known for its role in self-referential thinking, social cognition, and the processing of emotional experiences. This overlap suggests that the DMN plays an important role in the expression of narcissistic traits, reinforcing the idea that these traits are deeply rooted in brain structure and functions related to self-perception and social interactions.

A predictive model of the study developed using random forest regression confirmed the robustness of these findings. This model showed that the identified network could reliably predict narcissistic traits in new individuals, highlighting the potential of using brain imaging data to predict personality traits. Is.

“We're trying to develop a neural model of narcissistic personality,” Grecucci told SciPost. “Narcissistic Personality Disorder is a mental health condition characterized by a pervasive pattern of grandiosity, a persistent need for admiration, and a lack of empathy for others. The disorder is characterized by significant impairments in personal and professional relationships and overall functioning. In the previous study, we focused on its gray matter. In this new paper, we extended our findings to include the contribution of white matter.

“Thanks to an advanced data fusion machine learning method, we found a gray and white matter circuit that encodes enough information to predict a narcissistic personality. A predictive model was then derived, thanks to which Your level of narcissism can be gauged from the circuit.

“This circuit overlaps with the default mode network, a network of interacting brain regions that are active when a person is at rest and are associated with mind wandering, introspection, thinking,” Grecocchi explained. “We're making the point that it might be one of the centers that encodes our personality. We've also found it in other personality traits like borderline, antisocial, and more recently obsessive-compulsive personality. Involved.

Research has shed light on the neurological underpinnings of narcissistic personality traits. But there are limitations to consider. Relying only on structural data meant that functional brain data, which could provide a more comprehensive understanding of neural mechanisms, were not considered.

The sample size, while larger than many previous studies, could still be increased for more robust brain association analyses. Another limitation is the assessment of narcissistic traits using the PSDI, which does not distinguish between vulnerable and grandiose subtypes of narcissism. Future research could explore these subtypes separately to see if different brain networks are involved.

The study, “Reflecting the Narcissist: Gray and White Matter Features Common Contributions to the Default Mood Network in Predicting Narcissistic Personality Traits,” Khanetan Jornkokgaud, Teresa Baggio, Richard Bakiage, Para Vongupraj , was written by Remo Job, and Alessandro Grecucci.

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