Unmasking the Dark Triad: A Data Fusion Machine Learning Approach to Characterize the Neural Bases of Narcissistic, Machiavellian and Psychopathic Traits

Abstract

The Dark Triad (DT), encompassing narcissism, Machiavellianism and psychopathy traits, poses significant societal challenges. Understanding the neural underpinnings of these traits is crucial for developing effective interventions and preventive strategies. Our study aimed to unveil the neural substrates of the DT by examining brain scans from 201 individuals (mean age: 32.43, 105 females) using the unsupervised learning algorithm transposed independent vector analysis (tIVA). tIVA, known for identifying complex patterns in neuroimaging data, detected 15 joint grey matter (GM) and white matter (WM) networks. Of these networks, four were associated with the DT. The first component comprises areas within the reward network, including the thalamus, caudate, anterior cingulate and prefrontal regions. The second component encompasses regions within the executive network, predominantly involving prefrontal and posterior areas. The third component includes regions within the default mode network (DMN), such as the angular gyrus, the precuneus and the posterior cingulate cortex. Lastly, the fourth component overlaps with areas of the visual network, primarily located in the occipital and temporal lobes. Within these networks, the reward-related component correlated with narcissism, suggesting an association with the need for constant interpersonal rewards to enhance self-esteem and grandiosity in narcissistic individuals. Conversely, the DM-related component correlated with Machiavellianism, potentially reflecting the heightened strategic thinking employed by Machiavellian individuals for manipulation purposes. In line with established trends, sex differences emerged, with males displaying notably higher DT scores. Our findings offer insights into the intricate neurobiological bases of the DT personality and hold implications for future research and interventions.