Extraversion is encoded by scale-free dynamics of default mode network

被引:76
|
作者
Lei, Xu [1 ]
Zhao, Zhiying
Chen, Hong
机构
[1] Southwest Univ, Sch Psychol, Chongqing 400715, Peoples R China
关键词
Hurst exponent; Default mode network; Extraversion; FUNCTIONAL CONNECTIVITY; BRAIN OSCILLATIONS; PERSONALITY; RANDOMNESS; DISEASE; SIGNAL; REST; MRI;
D O I
10.1016/j.neuroimage.2013.02.020
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Resting-state functional Magnetic Resonance Imaging (rsfMRI) is a powerful tool to investigate neurological and psychiatric diseases. Recently, the evidences linking the scaling properties of resting-state activity and the personality have been accumulated. However, it remains unknown whether the personality is associated with the scale-free dynamics of default mode network (DMN) - the most widely studied network in the rsfMRI literatures. To investigate this question, we estimated the Hurst exponent, quantifying long memory of a time-series, in DMN of rsfMRI in 20 healthy individuals. The Hurst exponent in DMN, whether extracted by independent component analysis (ICA) or region of interest (ROI), was significantly associated with the extraversion score of the revised Eysenck Personality Questionnaire. Specifically, longer memory in DMN corresponded to lower extraversion. We provide evidences for an association between individual differences in personality and scaling dynamics in DMN, whose alteration has been previously linked with introspective cognition. This association might arise from the efficiency in online information processing. Our results suggest that personality trait may be reflected by the scaling property of resting-state networks. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:52 / 57
页数:6
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