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Causal interactions in resting-state networks predict perceived loneliness
Tian, Yin1,2,3; Yang, Li1; Chen, Sifan4; Guo, Daqing4; Ding, Zechao1; Tam, Kin Yip5; Yao, Dezhong4
Source PublicationPLOS ONE

Loneliness is broadly described as a negative emotional response resulting from the differences between the actual and desired social relations of an individual, which is related to the neural responses in connection with social and emotional stimuli. Prior research has discovered that some neural regions play a role in loneliness. However, little is known about the differences among individuals in loneliness and the relationship of those differences to differences in neural networks. The current study aimed to investigate individual differences in perceived loneliness related to the causal interactions between resting-state networks (RSNs), including the dorsal attentional network (DAN), the ventral attentional network (VAN), the affective network (AfN) and the visual network (VN). Using conditional granger causal analysis of resting-state fMRI data, we revealed that the weaker causal flow from DAN to VAN is related to higher loneliness scores, and the decreased causal flow from AfN to VN is also related to higher loneliness scores. Our results clearly support the hypothesis that there is a connection between loneliness and neural networks. It is envisaged that neural network features could play a key role in characterizing the loneliness of an individual.

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Indexed BySCI ; SSCI ; SSCI
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000401672400044
The Source to ArticleWOS
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Cited Times [WOS]:9   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Health Sciences
Corresponding AuthorTian, Yin; Yao, Dezhong
Affiliation1.Biomedical Engineering Department, ChongQing University of Posts and Telecommunications, ChongQing, China
2.Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmiiting Technology, Chongqing, China
3.Chongqing High School Innovation Team of Architecture and Core Technologies of Smart Medical System, Chongqing, China
4.Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
5.Faculty of Health Sciences, University of Macau, Taipa, Macau, China
Recommended Citation
GB/T 7714
Tian, Yin,Yang, Li,Chen, Sifan,et al. Causal interactions in resting-state networks predict perceived loneliness[J]. PLOS ONE,2017,12(5).
APA Tian, Yin.,Yang, Li.,Chen, Sifan.,Guo, Daqing.,Ding, Zechao.,...&Yao, Dezhong.(2017).Causal interactions in resting-state networks predict perceived loneliness.PLOS ONE,12(5).
MLA Tian, Yin,et al."Causal interactions in resting-state networks predict perceived loneliness".PLOS ONE 12.5(2017).
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