The establishment of ecological microexpressions recognition tes 
            <i>t</i> (EMERT): An improvement on JACBART microexpressions recognition test

Zhang, Jianxin; Lu, Li; Yin, Ming; Zhu, Chuanlin; Huang, Chunlu; Liu, Dianzhi

doi:10.3724/sp.j.1041.2017.00886

Cited by 9 publications

(80 citation statements)

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“…No study has yet reported on those patients’ ecological MEs processing characteristics, although ecological MEs (vs. ordinary facial expressions) are more consistent with real-life expressions and could better elucidate the facial expression processing characteristics in patients with depression. By adopting an ecological MEs recognition paradigm (Zhang et al, 2017 ), the present study explored the ecological MEs recognition characteristics of patients with depression for the first time.…”

Section: Discussionmentioning

confidence: 99%

“…Ecological MEs are MEs that occur in real life, rather than MEs only accompanying neutral expressions. The MEs in Zhang et al’s ( 2017 ) study were ecologically valid; therefore, they are considered to be ecological MEs.…”

Section: Introductionmentioning

confidence: 95%

“…However, the types of context that were adopted in Zhang et al’s ( 2014 ) study were still limited. Soon after that, Zhang et al ( 2017 ) examined the ME recognition characteristics of college students in fearful, sad, disgusting, angry, surprised and happy contexts. The results showed that the main effects of the fearful, sad, disgusting and angry context were significant, while those of surprise and happiness were not significant; on the basis of these results, Zhang et al ( 2017 ) established an ecologically valid ME recognition test.…”

Section: Introductionmentioning

confidence: 99%

“…To our knowledge, there has been no study examining the ME recognition characteristics of patients with depression. Based on this discussion, employing the ecological MEs recognition test established by Zhang et al ( 2017 ), this four (contexts: happy, neutral, sad and fearful) × 4 (ME: happy, neutral, sad and fearful) × 2 (group: depression and control group) study aimed to explore the ecological MEs recognition characteristics of patients with depression. Based on previous studies and the characteristics of MEs, we hypothesized that: (1) background expressions affect participants’ recognition of MEs; (2) compared with healthy individuals, the patients with depression would show lower ACC and longer RT while completing the ecological MEs recognition task; and (3) patients with depression would also show a negative bias in the ecological MEs task.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Zhu

Zhang

Zhiying

et al. 2017

Front. Behav. Neurosci.

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Previous studies have focused on the characteristics of ordinary facial expressions in patients with depression, and have not investigated the processing characteristics of ecological micro-expressions (MEs, i.e., MEs that presented in different background expressions) in these patients. Based on this, adopting the ecological MEs recognition paradigm, this study aimed to comparatively evaluate facial ME recognition in depressed and healthy individuals. The findings of the study are as follows: (1) background expression: the accuracy (ACC) in the neutral background condition tended to be higher than that in the fear background condition, and the reaction time (RT) in the neutral background condition was significantly longer than that in other backgrounds. The type of ME and its interaction with the type of background expression could affect participants’ ecological MEs recognition ACC and speed. Depression type: there was no significant difference between the ecological MEs recognition ACC of patients with depression and healthy individuals, but the patients’ RT was significantly longer than that of healthy individuals; and (2) patients with depression judged happy MEs that were presented against different backgrounds as neutral and judged neutral MEs that were presented against sad backgrounds as sad. The present study suggested the following: (1) ecological MEs recognition was influenced by background expressions. The ACC of happy MEs was the highest, of neutral ME moderate and of sadness and fear the lowest. The response to the happy MEs was significantly shorter than that of identifying other MEs. It is necessary to conduct research on ecological MEs recognition; (2) the speed of patients with depression in identifying ecological MEs was slower than of healthy individuals; indicating that the patients’ cognitive function was impaired; and (3) the patients with depression showed negative bias in the ecological MEs recognition task, reflecting the lack of happy ME recognition ability and the generalized identification of sad MEs in those patients.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Zhu

Zhang

Zhiying

et al. 2017

Front. Behav. Neurosci.

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“…Yin et al (2016) proposed that all basic expression kinds for both backgrounds and microexpressions needed to be detected to set up the ecological microexpression recognition test. Therefore, Zhang et al (2017) examined the recognition characteristics of six basic expression kinds of microexpressions (sadness, fear, anger, disgust, surprise, happiness) under seven basic expression kinds of backgrounds (the six basic expressions and neutral) to establish an ecological microexpression recognition test (EMERT) and found that the test had good retest reliability, criterion validity, and ecological validity: (1) the ecological microexpression recognition was generally significantly related to the JACBART microexpression recognition and common expression recognition. (2) The background's main effect of sadness, fear, anger, and disgust microexpressions were significant; the background's main effect of surprise and happiness microexpressions were not significant, but there was a wide difference between them with the common expressions.…”

Section: The Ecological Microexpression Recognition Testmentioning

confidence: 99%

The Establishment of Pseudorandom Ecological Microexpression Recognition Test (PREMERT) and Its Relevant Resting-State Brain Activity

Zhang

Yin

Shu

et al. 2020

Front. Hum. Neurosci.

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The EMERT (ecological microexpression recognition test) by Zhang et al. (2017) used between-subjects Latin square block design for backgrounds; therefore, participants could not get comparable scores. The current study used within-subject pseudorandom design for backgrounds to improve EMERT to PREMERT (pseudorandom EMERT) and used eyes-closed and eyes-open resting-state functional magnetic resonance imaging to detect relevant brain activity of PREMERT for the first time. The results showed (1) two new recapitulative indexes of PREMERT were adopted, such as microexpression M and microexpression SD. Using pseudorandom design, the participants could effectively identify almost all the microexpressions, and each microexpression type had significant background effect. The PREMERT had good split-half reliability, parallelforms reliability, criterion validity, and ecological validity. Therefore, it could stably and efficiently detect the participants' microexpression recognition abilities. Because of its pseudorandom design, all participants did the same test; their scores could be compared with each other. (2) amplitude of low-frequency fluctuations (ALFF; 0.01-0.1 Hz) in both eyes-closed and eyes-open resting states and ALFF difference could predict microexpression M, and the ALFF difference was less predictive. The relevant resting-state brain areas of microexpression M were some frontal lobes, insula, cingulate cortex, hippocampus, amygdala, fusiform gyrus, parietal lobe, caudate nucleus, precuneus, thalamus, putamen, temporal lobe, and cerebellum. (3) ALFFs in both eyes-closed and eyes-open resting states and ALFF difference could predict microexpression SD, and the ALFF difference was more predictive. The relevant restingstate brain areas of microexpression SD were some frontal lobes, central anterior gyrus, supplementary motor area, insula, hippocampus, amygdala, cuneus, occipital lobe, fusiform gyrus, parietal lobe, caudate nucleus, pallidum, putamen, thalamus, temporal lobe, and cerebellum. (4) There were many similar relevant resting-state brain areas, such as brain areas of expression recognition, microexpressions consciousness and attention, and the change from expression backgrounds to microexpression, and some different relevant resting-state brain areas, such as precuneus, insula, and pallidum, between microexpression M and SD. The ALFF difference was more sensitive to PREMERT fluctuations.

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The Personality Influence Factors of Ecological Microexpressions Recognition and Natural Exposure Training Effect: Openness, Depression and Gender

Yin¹,

Zhang²,

Liu³

et al. 2020

PBS

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The establishment of ecological microexpressions recognition tes t (EMERT): An improvement on JACBART microexpressions recognition test

Cited by 9 publications

References 0 publications

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals

The Establishment of Pseudorandom Ecological Microexpression Recognition Test (PREMERT) and Its Relevant Resting-State Brain Activity

The Personality Influence Factors of Ecological Microexpressions Recognition and Natural Exposure Training Effect: Openness, Depression and Gender

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