Testing the Process Dissociation Procedure by Behavioral and Neuroimaging Data: The Establishment of the Mutually Exclusive Theory and the Improved PDP

The establishment of the general microexpression recognition ability and its relevant brain activity

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. The PREMERT (pseudorandom ecological microexpression recognition test) could test the individual's microexpression recognition ability with six microexpression Ms (the mean of accuracy rates of a microexpression type under six expression backgrounds), and six microexpression SDs (the standard deviation of accuracy rates of this microexpression type under six expression backgrounds), but it and other studies did not explore the general microexpression recognition ability (the GMERA) or could not test the GMERA effectively. Therefore, the current study put forward and established the GMERA with the behavioral data of the PREMERT. The spontaneous brain activity in the resting state is a stable index to measure individual cognitive characteristics. Therefore, the current study explored the relevant resting-state brain activity of the GMERA indicators to prove that GMERA is an individual cognitive characteristic from brain mechanisms with the neuroimaging data of the PREMERT. The results showed that (1) there was a three-layer hierarchical structure in human microexpression recognition ability: The GMERA (the highest layer); recognition of a type of microexpression under different expression backgrounds (the second layer); and recognition of a certain microexpression under a certain expression background (the third layer). A common factor GMERA was extracted from the six microexpression types recognition in PREMERT. Four indicators of the GMERA were calculated from six microexpression Ms and six microexpression SDs, such as GMERAL (level of GMERA), GMERAF (fluctuation of GMERA), GMERAB (background effect of GMERA), and GMERABF (fluctuation of GMERAB), which had good parallel-forms reliability, calibration validity, and ecological validity. The GMERA provided a concise and comprehensive overview of the individual's microexpression recognition ability. The PREMERT was proved as a good test to measure the GMERA. (2) ALFFs (the amplitude of low-frequency fluctuations) in both eyes-closed and eyes-opened resting-states and ALFFs-difference could predict the four indicators of the GMERA. The relevant resting-state brain areas were some areas of the expression recognition network, the microexpression consciousness and attention network, and the motor network for the change from expression backgrounds to microexpression. (3) The relevant brain areas of the GMERA and different types of microexpression recognition belonged to the three cognitive processes, but the relevant brain areas of the GMERA were the "higher-order" areas to be more concise and critical than those of different types of microexpression recognition.

The gradual subjective consciousness fluctuation in implicit sequence learning and its relevant brain activity

Existing studies have investigated gradual subjective consciousnesses, guess, intuition, fluency, rule, and memory, and their fluctuation behavioral characteristics in implicit learning, but they did not investigate or elucidate the underlying brain mechanisms. Therefore, the current study asked participants to report subjective consciousnesses in each trial of inclusion and exclusion tasks after implicit sequence learning and used the eyes-closed and eyes-opened resting-states' fMRI to examine the relevant brain areas of the five gradual subjective consciousnesses and their fluctuation. The results showed that: (1) There were many relevant resting-state brain areas of the five gradual subjective consciousnesses to reveal their brain mechanisms. In the eyes-closed and eyes-opened resting states, as the participants' consciousness level was gradually increasing from guess to intuition, to fluency, to rule, and to memory, the positively-relevant brain areas correspondingly changed from somatic motor to a mixture of somatic motor, consciousness, emotion feeling, and implicit learning; and then to a mixture of visual, somatic motor, and consciousness; and then to a mixture of visual, somatic motor, and consciousness; and then to a mixture of visual, somatic motor, and consciousness. The negatively-relevant brain areas correspondingly changed from a mixture of visual, consciousness, somatic sensory, and implicit learning to a mixture of visual, somatic motor, somatic sensory, and other consciousness; and then to memory; and then to a mixture of other somatic motors; and then to a mixture of other consciousness and other somatic motors. However, in the amplitude of low frequency fluctuations (ALFFs)-difference, the relative directions of the guess and intuition were almost opposite to those in the eyes-closed and eyes-opened resting states. But the relative directions of the fluency, rule, and memory were consistent with those in the eyes-closed and eyes-opened resting states. (2) There were significant gradual subjective consciousness fluctuations, including the gradual subjective consciousness fluctuation-all M and SD. There were many relevant resting-state brain areas of gradual subjective consciousness fluctuations to reveal their brain mechanisms. The gradual subjective consciousness fluctuation M was positively related to Calcarine_R, Lingual_R, Lingual_R, Temporal_Pole_Mid_L, ParaHippocampal_L, Vermis_1_2, and Vermis_7; but was negatively related to Calcarine_R. The gradual subjective consciousness fluctuation-all SD was positively related to Parietal_Inf_L, Thalamus_L, Temporal_Mid_L, Vermis_9, Parietal_Inf_L, and Thalamus_L and Thalamus_R; but was negatively related to Rolandic_Oper_R, Rolandic_Oper_R, Insula_L, Insula_R, Cingulum_Post_L, and Temporal_Mid_L. The detailed function of the relevant brain areas of consciousness fluctuations needs further investigation. (3) ALFFs in eyes-closed and eyes-opened resting states and their ALFFs-difference could differently predict the five gradual subjective consciousnesses and their fluctuations, indicating that using the two resting states was necessary, and the ALFFs-difference was a new quantitative sensitivity index of the gradual subjective consciousnesses and their fluctuations.

The ecological validity of MET was favourable in sitting implicit sequence learning consciousness by eyes closed and eyes open resting states fMRI

The current study made participants sit to complete both the implicit sequence learning and the inclusion/exclusion tasks with the latter just after the former, and used eyes-closed and eyes-open resting states fMRI and their difference to test the ecological validity of the mutually exclusive theory (MET) in implicit-sequence-learning consciousness. (1) The behavioral and neuroimaging data did not support the process dissociation procedure, but did fit well with the MET. The correct inclusion-task response and the incorrect exclusion-task response were mutually exclusive with each other. The relevant brain areas of the two responses were either different or opposite in the eyes-closed and eyes-open resting-states and their difference. (2) ALFFs in eyes-closed and eyes-open resting-states and their difference were diversely related to the four MET knowledge in implicit sequence learning. The relevant brain areas of the four MET knowledge in the eyes-closed and eyes-open resting-state were the cerebral cortex responsible for vision, attention, cognitive control and consciousness, which could be called the upper consciousness network, and there were more relevant brain areas in the eyes-open resting-state than in the eye-closed resting-state.The relevant brain areas in ALFFs-difference were the subcortical nucleus responsible for sensory awareness, memory and implicit sequence learning, which could be called the lower consciousness network. ALFFs-difference could predict the four MET knowledge as a quantitative transition sensitivity index from internal feeling to external stimulus. (3) The relevant resting-state brain areas of the four MET knowledge were either different (for most brain areas, if some brain areas were related to one MET knowledge, they were not related to the other three MET knowledge) or opposite (for some brain areas, if some brain areas were positively related to one MET knowledge, they were negatively related to other MET knowledge). With the participants' control/consciousness level increasing from no-acquisition to controllable knowledge step by step, the positively relevant resting-state brain areas of the four MET knowledge changed from some consciousness network and the motor network, to some consciousness network and the implicit learning network, and then to some consciousness network; and the negatively relevant resting-state brain areas of the four MET knowledge changed from some consciousness network and visual perception network, to some consciousness network, then to some consciousness network and the motor network, and then to some consciousness network, the implicit learning network, and the motor network. In conclusion, the current study found the ecological validity of the MET was good in sitting posture and eyes-closed and eyes-open resting-states, ALFFs in eyes-closed and eyes-open resting-states and their difference could predict the four MET knowledge diversely, and the four MET knowledge had different or opposite relevant resting-state brain areas.