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Front. Hum. Neurosci. | doi: 10.3389/fnhum.2018.00070

Emotion regulation and complex brain networks: Association between expressive suppression and efficiency in the fronto-parietal network and default-mode network

Junhao Pan1, Liying Zhan1, Chuanlin Hu1,  Junkai Yang1, Cong Wang1, Li Gu1,  Shengqi Zhong1, Yingyu Huang1,  Qian Wu1, Xiaolin Xie1,  Qijin Chen1, Zhimin Zou1, Hui Zhou1, Miner Huang1* and  Xiang Wu1*
  • 1Sun Yat-sen University, China

Emotion regulation refers to the "implementation of a conscious or non-conscious goal to start, stop or otherwise modulate the trajectory of an emotion" (Etkin et al., 2015). Whereas multiple brain areas have been found to be involved in emotion regulation, relatively little is known about whether and how emotion regulation is associated with the global functioning of brain networks. Recent advances in brain connectivity research using graph-theory based analysis have shown that the brain can be organized into complex networks composed of functionally or structurally connected brain areas. Global efficiency is one graphic metric indicating the efficiency of information exchange among brain areas and is utilized to measure global functioning of brain networks. The present study examined the relationship between trait measures of emotion regulation (expressive suppression and cognitive reappraisal) and global efficiency in resting-state functional brain networks (the whole brain network and ten predefined networks) using structural equation modeling. The results showed that expressive suppression was reliably associated with efficiency in the fronto-parietal network and default-mode network. The finding advances the understanding of neural substrates of emotion regulation, revealing the relationship between expressive suppression and efficient organization of brain networks.

Keywords: DMN, Emotion Regulation, FPN, graph theory, Resting-state fMRI

Received: 05 Dec 2017; Accepted: 07 Feb 2018.

Edited by:

Delin Sun, Duke University, United States

Reviewed by:

Zhen Yuan, University of Macau, China
Junling Gao, University of Hong Kong, Hong Kong  

Copyright: © 2018 Pan, Zhan, Hu, Yang, Wang, Gu, Zhong, Huang, Wu, Xie, Chen, Zou, Zhou, Huang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Dr. Miner Huang, Sun Yat-sen University, Guangzhou, China, edshme@mail.sysu.edu.cn
Dr. Xiang Wu, Sun Yat-sen University, Guangzhou, China, rwfwuwx@gmail.com