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

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

“…The main areas encompassed within IC-GM2 comprise frontal, temporal, and parietal regions, including the superior temporal gyrus, the angular gyrus, the supramarginal gyrus, the middle temporal gyrus, and the inferior parietal lobe. These findings align with our earlier study, which also identified parietal and temporal areas, such as the angular gyrus, the rolandic operculum, and the Heschl’s gyrus, as relevant to narcissism (Jornkokgoud et al, 2023). These areas likely play a pivotal role in empathic and social cognitive processing linked to narcissism.…”

“…Moreover, our earlier findings demonstrated a significant relationship between insecure personality traits and the level of narcissism (Jornkokgoud et al, 2023), likely attributed to the connection between vulnerable narcissism and individuals with insecure tendencies (Kowalchyk et al, 2021).…”

“…Although there are certain similarities between avoidant personality disorder and narcissistic personality disorder, such as insecure attachment patterns (Simonsen & Euler, 2019), and the avoidance of social situations in which they can be ashamed (Ronningstam, 2020), we found no overlap at a neural level, confirming different neural substrates in the two disorders. Moreover, our earlier findings demonstrated a significant relationship between insecure personality traits and the level of narcissism (Jornkokgoud et al, 2023), likely attributed to the connection between vulnerable narcissism and individuals with insecure tendencies (Kowalchyk et al, 2021).…”

“…Both clinical and non-clinical investigations have explored narcissistic traits (Nenadić et al, 2021), primarily relying on validated questionnaires, such as the Narcissistic Personality Inventory (NPI) (Raskin & Hall, 1979). However, research into the structural and functional correlates of narcissistic traits remains limited, with most studies having used separate analyses of a single neuroimaging modality, specifically gray matter (GM) or white matter (WM) (Chester et al, 2016; Jornkokgoud et al, 2023; Nenadić et al, 2021), and having employed univariate methods.…”

“…In a recent effort to overcome some of these limitations, Jornkokgoud and colleagues (2023) employed a multivariate supervised machine learning approach, specifically Support Vector Machine in the form of Kernel Ridge Regression. Their study successfully identified a GM network including the middle frontal gyrus, angular gyrus, Rolandic operculum, Rectus, and Heschl’s gyrus as a predictive indicator of NPT.…”