Extraversion and Neuroticism Modulate the Effective Connectivity Network of the Amygdala: A Resting-

来源 :2015年中国生物医学工程联合学术年会 | 被引量 : 0次 | 上传用户:L1010732268
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  Background:In contrast to the wealth of data describing the neural network mechanisms of amygdala underlying extraversion and neuroticism [1,2,3],we know little about the information flow of amygdala involved in these two personality dimensions.Methods: In this study,we evaluated directional connectivity patterns from and to the amygdala by using Granger causality analysis(GCA)[4] and assessed their possible relationship with extraversion and neuroticism on resting-state functional magnetic resonance imaging(rs-fMRI)data of 70 participants.Results: Extraversion was positively correlated with the effective connectivity from the right inferior occipital gyrus(IOG)tothe left amygdala,and from the left fusiform gyrus(FG),bilateral IOG to the right amygdala.Neuroticismwas positively correlated with the effective connectivity from the right amygdala to the left middle frontal gyrus(MFG),while negatively correlated with the effective connectivity from the right Precuneus(PCu)to the right amygdala.Discussion:Our results shows that extraversion was positively correlated with the effective connectivity from the visual cortexto the amygdala,which may related to more effective facial information perception in extravert individuals.Conversely,neuroticism was positively associated with the effective connectivity from the amygdala to MFG,while negatively correlated with the effective connectivity from PCu to amygdala,providing further evidence for the relationship between neuroticism and alterations in cognitive-emotional functions such as emotional regulation and self-referential processing.These findings suggest that the strength and the direction of the information flow between face processing network,emotional regulation,and self-referential processing system are modulated by the individual differences in extraversion and neuroticism,offering further insights into the specific neural networks underlying personality.
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