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

Journal: Scientific reports
PMID: 28935904

Abstract

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.

Authors

  • Xiao Pan Ding
    Department of Psychology, National University of Singapore, Singapore, 117570, Singapore. dingxiaopan@gmail.com.
  • Si Jia Wu
    Dr. Eric Jackman Institute of Child Study, University of Toronto, Toronto, M5R 2X2, Canada.
  • Jiangang Liu
    School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China.
  • Genyue Fu
    Department of Psychology, Hangzhou Normal University, Hangzhou, 311121, China. fugenyue@hznu.edu.cn.
  • Kang Lee
    Dr. Eric Jackman Institute of Child Study, University of Toronto, Toronto, M5R 2X2, Canada. kang.lee@utoronto.ca.

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