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. (shrink)

The process dissociation procedure (PDP) of implicit sequence learning states that the correct inclusion-task response contains the incorrect exclusion-task response. However, there has been no research to test the hypothesis. The current study used a single variable (Stimulus Onset Asynchrony SOA: 850 ms vs. 1350 ms) between-subjects design, with pre-task resting-state fMRI, to test and improve the classical PDP to the mutually exclusive theory (MET). (1) Behavioral data and neuroimaging data demonstrated that the classical PDP has not been validated. In (...) the SOA = 850 ms group, the correct inclusion-task response was at chance, but the incorrect exclusion-task response occurred greater than chance. In the SOA = 850 ms group, the two responses were not correlated, but in the SOA = 1,350 ms group and putting the two groups together, the two responses were in contrast to each other. In each group, brain areas whose amplitude of low frequency fluctuations (ALFFs) in the resting-state related to the two responses were either completely different or opposite to one another. However, the results were perfectly consistent with the MET proposed by the present study which suggests that the correct inclusion-task response is equal to the correct exclusion-task response is equal toC+A1, and the incorrect exclusion-task response is equal toA2.Cdenotes the controlled response andA1andA2denote two different automatic responses. (2) The improved PDP was proposed to categorize the 12 kinds of triplets as delineating four knowledge types, namely non-acquisition of knowledge, uncontrollable knowledge, half-controllable knowledge, and controllable knowledge with the MET. ALFFs in the resting-state could predict the four knowledge types of the improved PDP among two groups. The participants’ control of the four knowledge types (degree of consciousness) gradually improved. Correspondingly, the brain areas in the resting-state positively related to the four knowledge types, gradually changed from the sensory and motor network to the somatic sensorimotor network, and then to the implicit learning network, and then to the consciousness network. The brain areas in the resting-state negatively related to the four knowledge types gradually changed from the consciousness network to the sensory and motor network. As SOA increased, the brain areas associated with almost all the four knowledge types changed. (3) The inhomogeneous hypothesis of the MET is best suited to interpret behavioral and neuroimaging data; it states that the same components among the four knowledge types are not homogeneous, and the same knowledge types are not homogeneous between the two SOA groups. (shrink)