Abstract
Zhang, et al. (2017) established the ecological microexpression recognition test (EMERT), but it only used white models' expressions as microexpressions and backgrounds, and there was no research detecting its relevant brain activity. The current study used white, black and yellow models' expressions as microexpressions and backgrounds to improve the materials ecological validity of EMERT, and it used eyes-closed and eyes-open resting-state fMRI to detect relevant brain activity of EMERT for the first time. The results showed: (1) Two new recapitulative indexes of EMERT were adopted, such as microexpression M and microexpression SD. The participants could effectively identify almost all the microexpressions, and each microexpression type had a significantly background effect. The EMERT had good retest reliability and calibration validity. (2) ALFFs (Amplitude of Low-Frequency Fluctuations) in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression M. The relevant brain areas of microexpression M were some frontal lobes, insula, cingulate cortex, hippocampus, parietal lobe, caudate nucleus, thalamus, amygdala, occipital lobe, fusiform, temporal lobe, cerebellum and vermis. (3) ALFFs in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression SD, and the ALFFs-difference was more predictive. The relevant brain areas of microexpression SD were some frontal lobes, insula, cingulate cortex, cuneus, amygdala, fusiform, occipital lobe, parietal lobe, precuneus, caudate lobe, putamen lobe, thalamus, temporal lobe, cerebellum and vermis. (4) There were many similarities and some differences in the relevant brain areas between microexpression M and SD. All these brain areas can be trained to enhance ecological microexpression recognition ability.
Highlights
1.1 The ecological microexpression recognition test (EMERT)Microexpressions are very transitory expressions lasting about 1/25–1/2 s, which can reveal people’s true emotions they try to hide or suppress [1, 2]
A single sample t test was made for each microexpression recognition accuracy with random level 1/6, and it was found that almost all the microexpression recognition accuracies in the first EMERT were significantly higher than random, except that fear under surprise, was not significantly higher than random (p>0.05)
Pearson correlation analysis was made between amplitude of low-frequency fluctuations (ALFFs) of resting-state and microexpression M. (1) In the eyes-closed resting state, ALFFs in the frontal lobe, insula, cingulate cortex, hippocampal, caudate nucleus, thalamus and vermis were significantly correlated with some microexpression M. (2) In the eyes-open resting state, ALFFs in the frontal lobe, insula, cingulate cortex, hippocampus, parietal lobe, caudate nucleus, thalamus, temporal lobe, cerebellum and vermis were significantly correlated with some microexpression M. (3) In the ALFFs-difference of eyes-open minus eyes-closed resting-states, ALFFs-difference in the frontal lobe, insula, amygdala, occipital lobe, fusiform, temporal lobe, cerebellum and vermis were significantly correlated with some microexpression M
Summary
1.1 The ecological microexpression recognition test (EMERT)Microexpressions are very transitory expressions lasting about 1/25–1/2 s, which can reveal people’s true emotions they try to hide or suppress [1, 2]. 1.1 The ecological microexpression recognition test (EMERT). The relevant resting-state brain activity of EMERT jiangnan.edu.cn/), the Top-notch Academic Programs Project of Jiangsu Higher Education Institutions Gov.cn/art/2015/6/1/art_38765_3245491.html), the Mentoring Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (2016): 2016SJD190004 (MY, http://jyt.jiangsu.gov.cn/art/2016/6/28/art_58391_ 7507970.html) and the National Natural Science Foundation of China JZ provided main research ideas and financial support, and was responsible for research design, data collection and analysis, and article writing. MY provided part of research ideas and financial support, and was responsible for research design, data analysis, and article writing. DL was responsible for guiding the design, implementation, data analysis and article writing of the whole research, and provided financial support
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