ERPs/EEG-based Neural Mechanisms Between Micro-Expression Recognition And Lie Detection

Background: The existing behavioral researches have revealed that the ability to recognize micro-expressions is relative to the ability of lie detection,with the evidence that training to identify micro-expressions can improve the detection accuracy of deception.But little researches have focused on the neural mechanisms between both of them.Thus,this research is attempting to explore this vulnerability by conducting two separate experiments which are called ERPs/EEG-based facial expression recognition research and deception detection research for further analyzing the neural mechanisms between micro-expressions and deception detection.Method: This Research includes two experiments,expression recognition and lie detection.In the process of expression recognition,35 college students were recruited to participate in,and dynamic expressions were uniquely used as experimental stimuli.All the subjects were asked to select the categories where the dynamic macro expressions and dynamic micro expressions appeared on the central screen could be embraced,enabling us to further analyze the differences in neuro-electrophysiological characteristics between the macro-expressions and micro-expressions.In the experiment of lie detection,all the subjects were instructed to judge whether the model in the central screen were lying or not in the experiment of lie detection,and all the subjects were instructed to judge whether the model in the central screen were lying or not.The experimental material in the deception detection experiment were jointedvideos clipped from Godlie,a Chinese reality show program,and Goldenball which is an American reality show program.Totally,there were 36 20-seconds honest and cheat video clips which were provided by 36 models selected from 18 Goldenball players and18 Godlie players.The purpose for this experiment was to reveal the difference in brain mechanism between truth and falsehood.For the reason that all the subjects were asked to participate in both of the experiments about expression recognition and lie detection in one month in succession while the experiment order was random.Therefore,the research attempts to explore the differences in neuro-electrophysiological characteristics between micro-expressions recognition and deception detection by means of analyzing the two experiments.Results: In the facial expression recognition experiment,the research results include:(1)the beta neural oscillations for the recognition of macro-expressions were significantly higher than that of micro-expressions.(2)the beta neural oscillations on the channels of OZ and FZ were significantly higher that of CZ and PZ.(3)the neural network-based functional connectivity showed no significant differences in the abilities to recognize macro-expressions and micro-expressions.In addition,the behavioral data in deception detection experiment found that there was no significant difference between the accuracy on the detection of honesty and deception,and both of them had approximately random accuracy rate.Meanwhile,the beta neural oscillations for the detection of lies and truth had no significant differences,and OZ channel conveyed the highest beta oscillations with FZ as second place.Brain network functional connectivity found that the network for the detection of liars and truth-tellers had no significant differences.More importantly,after integrating and analyzing both of the data of facial expression recognition and deception detection,it was found that there were no significant correlations between the accuracy rates of micro-expressions and lie detection.At the same time,for recognizing micro-expressions,the beta oscillations elicited from FZ channel had no significant differences with that for detecting liars whereas the beta oscillations elicited from channels OZ and PZ had significant differences with that for detecting liars.More unexpectedly,brain network functional connectivity found that the connectivity between Frontal-Sup-Medial-R and left Precuneus were more intensive in the classification of liars.Conclusions:(1)Recognizing micro-expressions and macro-expressions may elicit different neural oscillations,but the same brain network.(2)The process of honest detection and lie detection may elicit the same neural oscillations and the similar brain network.(3)Micro-expressions and lie detection may have both similar and different neural mechanisms and different brain network’s collaboration.