In a new study published in the journal Social Neuroscience, researchers employed machine learning techniques to predict individual differences in narcissistic personality traits using distinct structural brain features. The study represents the first-ever attempt to harness machine learning for deciphering the neural underpinnings of narcissism.
Narcissistic traits encompass characteristics such as grandiosity, a constant need for admiration, a lack of empathy, entitlement, manipulative behavior, envy, arrogance, fragile self-esteem, and difficulties in maintaining healthy relationships. These traits reflect a self-centered and often arrogant perspective, where individuals may believe they are superior to others and expect special treatment.
When narcissistic traits are severe and persistent, they may lead to a diagnosis of narcissistic personality disorder, a complex clinical construct often comorbid with other psychological disorders such as borderline personality, substance abuse, antisocial tendencies, and anxiety. However, diagnosing narcissistic personality disorder can be challenging, as it relies on self-reported and observed behaviors, thoughts, and feelings. This is because there are no clear biological markers for the disorder, making it difficult to objectively assess the disorder.
The researchers sought to develop predictive models that could estimate an individual’s narcissistic traits based on their brain structure and personality features. This has practical implications for psychology and clinical assessments. Predictive models could potentially help identify individuals at risk of developing narcissistic traits or assist in the assessment and treatment of personality disorders.
“In our Lab, the Clinical and Affective Neuroscience Lab, we are particularly interested in understanding the neural fingerprint of personality. Especially personality disorders. We all have a personality that ranges from normal to abnormal traits and we believe it is of fundamental importance understanding it,” explained study author Alessandro Grecucci, a professor of affective neuroscience and neurotechnology at the University of Trento.
The researchers conducted a study using data from the MPI-Leipzig Mind Brain-Body dataset, which included structural MRI and questionnaire data from 135 healthy participants. Eligibility criteria included good health, no medication, and no history of substance abuse or neurological diseases. The participants’ demographic and behavioral data were recorded.
Using a machine learning technique called Kernel Ridge Regression, the researchers found that specific brain regions were linked to narcissistic traits, including the orbitofrontal cortex, Rolandic operculum, angular gyrus, rectus, and Heschl’s gyrus. These regions are associated with emotion processing, social cognitive processing, and auditory perception.
The findings provide evidence that “even such an intimate thing such as personality, the inner core of who we are, can be scientifically studied and predicted from our brain,” Grecucci told PsyPost. “In our lab, we are trying to develop neuro-predictive models of personality and other affective relevant dimensions. One day, these studies may help clinicians to characterize eventual difficulties before they turn into a full disorder.”
Furthermore, the researchers constructed a predictive model to determine an individual’s narcissistic traits based on specific subscales from the NEO Personality Inventory-Revised, Short Dark Triad questionnaire, and the Personality Styles and States Inventory.
Individuals with higher levels of openness, characterized by a willingness to explore new experiences and ideas, were more likely to exhibit narcissistic traits. Lower levels of agreeableness, which involve being less cooperative, sympathetic, and considerate of others, were associated with narcissistic traits. Higher levels of conscientiousness, indicating self-discipline, organization, and goal-oriented behavior, were linked to narcissistic traits.
Additionally, the study found that abnormal personality traits, including Borderline, Antisocial, Addicted, Negativistic, and Insecure traits, were related to narcissistic traits. Machiavellianism, characterized by manipulative and deceitful behavior, also predicted narcissistic traits. This suggests that individuals with narcissistic traits may exhibit a combination of personality traits, some of which are outside the normal range.
“In this and other studies, we are observing an emerging coherent pattern in different personality disorders,” Grecucci said. “Regions belonging to the same cortical-subcortical networks are at a forefront. This may lead to the development of a common ‘personality network’ behind specific personality traits.”
The study provides new insights into the neural underpinnings of narcissism. But as with all research, it includes some limitations. Firstly, the analysis focused solely on gray matter features, neglecting potential insights that could be gained from exploring white matter features or functional brain activity. Future research may benefit from a more comprehensive examination of various brain aspects. Secondly, while the study included a relatively larger sample size compared to previous research, it acknowledges the potential for even larger sample sizes to enhance brain-wide association analyses.
The researchers also believe that clinical personality models offer more robust and predictive insights into personality traits than non-clinical models.
“Personality is a complex thing, and no one knows which is the best model of personality we should use to study this topic at a brain level,” Grecucci explained. “Contrary to the vast majority of studies that are using normal personality models (such as the Big Five), we are trying to make a claim that personalities can be better captured using clinical models such as the DSM-5 personality disorder axis. The clinical personalities offer such a strong characterization of what different personalities are that in my opinion they can be more predictive than other non-clinical models. In the end, personality disorders are just exaggerated personality traits that we all have.”
The study, “Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach“, Khanitin Jornkokgoud, Teresa Baggio, Md Faysal, Richard Bakiaj, Peera Wongupparaj, Remo Job, and Alessandro Grecucci.
