ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

Advances in Psychological Science ›› 2018, Vol. 26 ›› Issue (9): 1567-1575.doi: 10.3724/SP.J.1042.2018.0567

• Research Reports • Previous Articles     Next Articles

Sex differences in adaptive multi-scale functional connectivity of the human brain

DUAN Kaikai1, DONG HaoMing2,3,4,5, MIAO Liwen1, SU Xuequan6,7, XIANG Jie1,**(), ZUO XiNian2,3,4,5,7,*()   

  1. 1 College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
    2 CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
    3 Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
    4 Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    5 Research Center for Lifespan Development of Mind and Brain, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    6 Institute of Physical Education, Guangxi Teachers Education University, Nanning 530000, China
    7 Key Laboratory of Brain and Education, Guangxi Teachers Education University, Nanning 530001, China
  • Received:2018-01-22 Online:2018-09-15 Published:2018-07-30
  • Contact: Jie XIANG,XiNian ZUO E-mail:xiangjie@tyut.edu.cn;zuoxn@psych.ac.cn

Abstract:

Recent advances on functional magnetic resonance imaging (fMRI) demonstrated sex differences in the brain function. However, no standard on fMRI signal’s frequency division limited further biologically plausible explanation of these observations. In this work, we proposed a fast-multi-dimensional ensemble empirical mode decomposition to extract their multi-scale features of fMRI signal. We found that: this method can perform adaptive frequency allocation for the resting-state fMRI signal, whereby the built multi-scale function network in the frequency brain of 0.06 ~ 0.10 Hz showed significant sex differences regarding its connectivity; males had strong functional connectivity primarily within the limbic network and ventral attention network whereas females presented their strong functional connectivity mainly related to the visual network, ventral attention network and frontoparietal control network. These findings present a new method for the analysis of functional MRI images and provided brain imaging evidence on sex differences in functional connectomics.

Key words: sex differences, functional connectivity, brain network, functional magnetic resonance imaging, low frequency characteristics

CLC Number: