The Establishment of Pseudorandom Ecological Microexpression Recognition Test (PREMERT) and Its Relevant Resting-State Brain Activity - Zhang, Jianxin; Yin, Ming; Shu, Deming; Liu, Dianzhi (Frontiers in Human Neuroscience, 2020)
The EMERT(ecological microexpression recognition test) by Zhang, et.al.(2017) used block design for backgrounds, therefore participants could not get comparable scores. The current study used random design for backgrounds to improve EMERT to REMERT (random EMERT), and used eyes-closed and eyes-open resting-state fMRI to detect relevant brain activity of REMERT for the first time. The results showed: (1)Two new recapitulative indexes of REMERT/EMERT were adopted, such as microexpression M and microexpression SD. Using random design, the participants could effectively identify almost all the microexpressions, and each microexpression type had significantly background effect. Using two EMERT as duplicates and calibrations, the REMERT had good duplicate reliability and calibration validity. Therefore the REMERT can be used as an individual test, and each participant can get comparable and recapitulative scores. (2)ALFFs in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression M, and the ALFFs-difference was less predictive. The relevant 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 ALFFs-difference could predict microexpression SD, and the ALFFs-difference was more predictive. The relevant 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 similarities and some differences of the relevant brain areas between microexpression M and SD. The ALFFs-difference was more sensitive to REMERT fluctuations. All these brain areas can be trained to enhance ecological microexpression recognition ability.