Predicting Personality from Network-based Resting-State Functional Connectivity

Vancouver Convention Centre 

Personality as a key feature of inter-individual differences affects all aspects of life, including affective, social, executive and memory functioning [3,4,6]. Task-based fMRI studies investigated personality and brain activity in association to each of these domains; however, since personality traits are enduring across situations [2], it is possible that they relate to many brain systems, not detected by task-based fMRI. The investigation of functional connectivity in resting state conditions might therefore help in capturing the intrinsic and complex neural architecture underlying personality [1]. A recent study [7] showed a sexual dimorphism in brain structure-personality relationships, with associations revealed only in males. In females, brain connectivity rather than structure, might thus play a stronger role in light of personality. Therefore, we aimed to predict scores of the five-factor personality model (openness, conscientiousness, extraversion, agreeableness, neuroticism) [2] from resting-state functional connectivity (RS-FC) in meta-analytically defined brain networks, and tested how these predictions are modulated by gender.