Microstructural White Matter Alterations and Personality Traits: a Diffusion MRI Study

Background and Aim: The Big-Five of Personality (NEO-FFI), is one of the most generally recognized taxonomies of personality consisting of five major factors including Neuroticism (N), Extraversion (E), Openness (O), Agreeableness (A), and Conscientiousness (C). Methods A total of ۲۲۶ (۱۴۵(۶۴.۲%) male, mean age+SD=۳۹.۲۷+۲۰.۲۷ year) healthy individuals, who were tested for personality traits, according to NEO-FFI from the Leipzig Study for Mind-Body-Emotion Interactions (LEMON) database, were enrolled in the current study. Images were prepared and interpreted for the dMRI connectometry metric (spin distribution function). Tracks generated from bootstrap resampling were recorded, and a length threshold of ۲۰ voxel distance was used to select tracks. NEO-FFI factors associations with diffusion metrics were analyzed through dMRI connectometry. A multiple regression model was used to consider NEO-FFI factors separately. Results: Herein, we aimed to investigate the white matter (WM) integrity in specific trajectories with a significant difference regarding each personality factor using diffusion magnetic resonance imaging (MRI) connectometry. Conclusion Connectometry analyses showed a positive significant correlation between N and WM connectivity in the splenium of Corpus Callosum (CC), Middle and Superior Cerebellar Peduncle (MCP and SCP) (FDR=۰.۰۰۷) as well as a negative correlation between E and WM integrity in CC, MCP, SCP, and arcuate fasciculus (AF) (FDR=۰.۰۳۴). Besides, both A and C were associated with increased WM integrity in CC and cingulum (FDR=۰.۰۲۴, ۰.۰۴۲, respectively) as well as decreased integrity in cerebellum, MCP, and fornix (FDR=۰.۰۱۰, ۰.۰۱۱, respectively). Our findings suggest that WM integrity in trajectories with close relation with basal ganglia, language processing areas, and limbic system are significantly associated with N, E, and A, respectively.

Keywords:

Personality , Diffusion Magnetic Resonance Imaging , Connectometry