Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis

The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or...

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Autores principales: Ding, Xiao Pan, Wu, Si Jia, Liu, Jiangang, Fu, Genyue, Lee, Kang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608888/
https://www.ncbi.nlm.nih.gov/pubmed/28935904
http://dx.doi.org/10.1038/s41598-017-11754-4
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author Ding, Xiao Pan
Wu, Si Jia
Liu, Jiangang
Fu, Genyue
Lee, Kang
author_facet Ding, Xiao Pan
Wu, Si Jia
Liu, Jiangang
Fu, Genyue
Lee, Kang
author_sort Ding, Xiao Pan
collection PubMed
description The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children’s functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children’s cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.
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spelling pubmed-56088882017-10-10 Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis Ding, Xiao Pan Wu, Si Jia Liu, Jiangang Fu, Genyue Lee, Kang Sci Rep Article The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children’s functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children’s cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception. Nature Publishing Group UK 2017-09-21 /pmc/articles/PMC5608888/ /pubmed/28935904 http://dx.doi.org/10.1038/s41598-017-11754-4 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ding, Xiao Pan
Wu, Si Jia
Liu, Jiangang
Fu, Genyue
Lee, Kang
Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis
title Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis
title_full Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis
title_fullStr Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis
title_full_unstemmed Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis
title_short Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis
title_sort functional neural networks of honesty and dishonesty in children: evidence from graph theory analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608888/
https://www.ncbi.nlm.nih.gov/pubmed/28935904
http://dx.doi.org/10.1038/s41598-017-11754-4
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