Individualized prediction of trait narcissism from whole-brain resting-state functional connectivity.

ABSTRACT: Narcissism is one of the most fundamental personality traits in which individuals in general population exhibit a large heterogeneity. Despite a surge of interest in examining behavioral characteristics of narcissism in the past decades, the neurobiological substrates underlying narcissism remain poorly understood. Here, we addressed this issue by applying a machine learning approach to decode trait narcissism from whole-brain resting-state functional connectivity (RSFC). Resting-state functional MRI (fMRI) data were acquired for a large sample comprising 155 healthy adults, each of whom was assessed for trait narcissism. Using a linear prediction model, we examined the relationship between whole-brain RSFC and trait narcissism. We demonstrated that the machine-learning model was able to d

SUBMITTER: Feng C 

PROVIDER: S-EPMC6866420 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature