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Hum Brain Mapp. 2016 Feb;37(2):773-9. doi: 10.1002/hbm.23065. Epub 2015 Nov 26.

Personality and complex brain networks: The role of openness to experience in default network efficiency.

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Department of Psychology, University of North Carolina at Greensboro, Greensboro, North Carolina, USA.
Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Psychology, University of Graz, Graz, Austria.
Department of Neurosurgery, University of New Mexico, Albuquerque, New Mexico, USA.
Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, Rhode Island, USA.


The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self-generated cognition, such as mind-wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease-related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functioning. Using structural equation modeling and graph theoretical analysis of resting-state fMRI data, we provide evidence that Openness to Experience-a normally distributed personality trait reflecting a tendency to engage in imaginative, creative, and abstract cognitive processes-underlies efficiency of information processing within the DN. Across two studies, Openness predicted the global efficiency of a functional network comprised of DN nodes and corresponding edges. In Study 2, Openness remained a robust predictor-even after controlling for intelligence, age, gender, and other personality variables-explaining 18% of the variance in DN functioning. These findings point to a biological basis of Openness to Experience, and suggest that normally distributed personality traits affect the intrinsic architecture of large-scale brain systems. Hum Brain Mapp 37:773-779, 2016.


default mode network; individual differences; network science; personality; structural equation modeling

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