Pathological personality traits modulate neural interactions.

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), includes an empirically supported dimensional model of personality pathology that is assessed via the Personality Inventory for the DSM-5 (PID-5). Here we used magnetoencephalography (MEG; 248 sensors) to evaluate resting-state neural network properties associated with the five primary DSM-5 maladaptive personality domains (negative affect, detachment, antagonism, disinhibition, and psychoticism) in 150 healthy veterans ("control" group) and 179 veterans with various psychiatric disorders ("psychopathology" group). Since a fundamental network property is the strength of functional connectivity among network elements, we used the absolute value of the pairwise correlation coefficient (aCC) between prewhitened MEG sensor time series as a measure of neural functional connectivity and assessed its relations to the quantitative PID-5 scores in a linear regression model, where the log-transformed aCC was the dependent variable and individual PID scores, age, and gender were the independent variables. The partial regression coefficient (pRC) for a specific PID-5 score in that model provided information concerning the direction (positive, negative) and size (absolute value) of the PID effect on the strength of neural correlations. We found that, overall, PID domains had a negative effect (i.e., negative pRC; decorrelation) on aCC in the control group, but a positive one (i.e., positive pRC; hyper-correlation) in the psychopathology group. This dissociation of PID effects on aCC was especially pronounced for disinhibition, psychoticism, and negative affect. These results document for the first time a fundamental difference in neural-PID relations between control and psychopathology groups.