Catch a Liar: An Interdisciplinary Perspective

Lying is popular in daily life, and it appeared at the very beginning of human history. It involves an intentional effort to generate false information or to actively conceal the truth. As we can tell from the stories about lying or deception that are told in many of the ancient Chinese historic books, people have been deceiving each other since the very beginning of human history. However, it does not necessarily make us good at it. As a result, all kinds of techniques have been developed to detect deception, which also makes lie detection an important aspect in criminal justice system and in real-world counter-terrorism efforts.

Emotions always accompany deception. Liars will experience fear, anxiety, guilt, and/or happiness which can result in differences in emotional cues - microexpressions. Microexpression is a brief and subtle facial movement which usually lasts for from 1/25 to 1/5 of a second revealing an emotion a person is trying to conceal. The face will leak the concealed emotion while people trying to suppress their strongly felt emotions. The leaked emotions, i.e., microexpression, will appear very fleetingly. The fact that it cannot be suppressed makes the facial microexpression the most truthful part of the body. Therefore, recognizing microexpression can be a reliable method to detect lie which is pursuit by many researchers.

Considering the close relationship between microexpression and deception (lying about the true felt emotions), in this Research Topic we will mainly focus on the application of microexpression in the field of deception detection, as well as its underlying mechanisms. This approach is so-called emotion-based deception detection, which suggest that people who are better at recognizing microexpressions will have an advantage in deception detection. However, there are many questions not clearly answered about the application of microexpression in the field of deception detection. For example, how can people detect the fleeting microexpressions? Does microexpressions recognition ability facilitate deception detection? Can training in facial microexpression recognition improve efficiency of deception detection? Are there impacts of moderator variables (such as empathy, age, sex, occupation) on the microexpression recognition and deception detection? Can we unconsciously detect deception and microexpression by using body movements as an indicator? What are the patterns of brain activities while recognizing microexpression (it is closely related to lie) and detecting deception?

This Research Topic welcome empirical studies to establish the effectiveness and efficacy for linking microexpressions to deception. All kinds of research to fulfill this aim from the field of psychology, cognitive neuroscience, and computer science are suitable for this collection. Besides the efforts from psychology and cognitive neuroscience, computer vision has showed considerable interest in the field of microexpression recognition and deception detection. To justify the application of microexpression in deception detection we need more evidence from all kinds of related discipline to fill the gap between knowledge (e.g., recognition of microexpressions filmed in real life situations) and deception detection.

This Research Topic will strengthen the collaboration between researchers whose main area of expertise are psychology, cognitive neuroscience and researchers whose expertise is in computer vision. We hope to establish a more conclusive connection between microexpressions and deception through the co-work of researchers in the related areas.