Spontaneous Micro-Facial Expressions: Classical Studies and New Horizons

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Emotional facial expressions are one of the main sources of human non-verbal communication. At the same time, emotions are transmitted through facial expressions both consciously and unconsciously. In particular, micro-facial expressions and background facial expressions of low intensity are those that are poorly amenable to conscious control. According to many studies, micro-facial expressions can be considered a window into a person’s true feelings. However, due to their fleetingness and low intensity, micro expressions are very difficult to catch with the naked eye. This article presents an overview of scientific knowledge about human micro-facial expressions, starting from the discovery to the current level of development. We consider the history of studying the topic and describe in detail the current state of the art. We further discuss the limitations and presents ideas on the prospects for further studies of micro-facial expressions, taking into account the cross-cultural component.

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作者简介

Victoria Rostovtseva

Institute of Ethnology and Anthropology, Russian Academy of Sciences

编辑信件的主要联系方式.
Email: victoria.v.rostovtseva@gmail.com
ORCID iD: 0000-0002-1846-9865

кандидат биологических наук, старший научный сотрудник

俄罗斯联邦, 32a Leninsky prospekt, Moscow, 119991

Marina Butovskaya

Institute of Ethnology and Anthropology, Russian Academy of Sciences

Email: marina.butovskaya@gmail.com
ORCID iD: 0000-0002-5528-0519

член-корр. РАН, доктор исторических наук, профессор, главный научный сотрудник

俄罗斯联邦, 32a Leninsky prospekt, Moscow, 119991

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2. Fig. 1. An example of the use of the MaqFACS system in a study of facial expressions in rhesus macaques (Macaca mulatta) for coding facial movements. Figure adapted from the authors (Whitehouse et al. 2024)

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3. Fig. 2. Example of the time and amplitude profile of micro- and macroexpression. The figure shows a comparison of the duration and intensity of muscle activation for micro- and macroexpression of one of the human motor units (AU)

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4. Fig. 3. The figure shows a visualization of the recognition of background micro-facial expressions by the FaceReader system, namely the activation of AU17 (chin lift) and AU43 (eye closing) in a state of rest. (The photo is published with the personal permission of a participant in one of our experimental studies conducted in Moscow.)

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