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White-matter structural connectivity underlying human laughter-related traits processing
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White-matter structural connectivity underlying human laughter-related traits processing

Ching-Lin Wu, Suyu Zhong, Yu-Chen Chan, Hsueh-Chih Chen, Gaolang Gong, Yong HePing Li
Frontiers in Psychology, 卷.7(OCT), 1637
10/2016

摘要

Brain network Connectome Diffusion tensor imaging Gelotophobia Graph theory Psychology (all)
Most research into the neural mechanisms of humor has not explicitly focused on the association between emotion and humor on the brain white matter networks mediating this connection. However, this connection is especially salient in gelotophobia (the fear of being laughed at), which is regarded as the presentation of humorlessness, and two related traits, gelotophilia (the enjoyment of being laughed at) and katagelasticism (the enjoyment of laughing at others). Here, we explored whether the topological properties of white matter networks can account for the individual differences in the laughter-related traits of 31 healthy adults. We observed a significant negative correlation between gelotophobia scores and the clustering coefficient, local efficiency and global efficiency, but a positive association between gelotophobia scores and path length in the brain's white matter network. Moreover, the current study revealed that with increasing individual fear of being laughed at, the linking efficiencies in superior frontal gyrus, anterior cingulate cortex, parahippocampal gyrus, and middle temporal gyrus decreased. However, there were no significant correlations between either gelotophilia or katagelasticism scores or the topological properties of the brain white matter network. These findings suggest that the fear of being laughed at is directly related to the level of local and global information processing of the brain network, which might provide new insights into the neural mechanisms of the humor information processing.

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https://doi.org/10.3389/fpsyg.2016.01637檢視
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