| Literature DB >> 29662443 |
Junhao Pan1, Liying Zhan1, ChuanLin Hu1, Junkai Yang1, Cong Wang1, Li Gu1, Shengqi Zhong1, Yingyu Huang1, Qian Wu1, Xiaolin Xie1, Qijin Chen1, Hui Zhou1, Miner Huang1, Xiang Wu1.
Abstract
Emotion regulation (ER) 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 ER, relatively little is known about whether and how ER 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 ER (expressive suppression (ES) and cognitive reappraisal (CR)) and global efficiency in resting-state functional brain networks (the whole brain network and ten predefined networks) using structural equation modeling (SEM). The results showed that ES was reliably associated with efficiency in the fronto-parietal network and default-mode network. The finding advances the understanding of neural substrates of ER, revealing the relationship between ES and efficient organization of brain networks.Entities:
Keywords: DMN; FPN; emotion regulation; graph theory; resting-state fMRI
Year: 2018 PMID: 29662443 PMCID: PMC5890121 DOI: 10.3389/fnhum.2018.00070
Source DB: PubMed Journal: Front Hum Neurosci ISSN: 1662-5161 Impact factor: 3.169