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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Sobre autores

Victoria Rostovtseva

Institute of Ethnology and Anthropology, Russian Academy of Sciences

Autor responsável pela correspondência
Email: victoria.v.rostovtseva@gmail.com
ORCID ID: 0000-0002-1846-9865

кандидат биологических наук, старший научный сотрудник

Rússia, 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

Rússia, 32a Leninsky prospekt, Moscow, 119991

Bibliografia

  1. Adams, R.B., Jr., et al. 2012. Emotion in the Neutral Face: A Mechanism for Impression Formation? Cognition & Emotion 26 (3): 431–441. https://doi.org/10.1080/02699931.2012.666502
  2. Al-Shawaf, L., and T.K. Shackelford. 2024. The Oxford Handbook of Evolution and the Emotions. New York: Oxford University Press.
  3. Anokhin, P.K. 1964. Emotsii [Emotions]. In Bol’shaia meditsinskaia entsiklopediia [Great Medical Encyclopedia], edited by A.N. Bakulev, 35: 339–341. Moscow: Medgiz.
  4. Anokhin, P.K. 1964. Evoliutsiia emotsii [Evolution of Emotions]. In Bol’shaia meditsinskaia entsiklopediia [Great Medical Encyclopedia], edited by A.N. Bakulev, 35: 354–357. Moscow: Medgiz.
  5. Anokhin, P.K. 1968. Biologiia i neirofiziologiia uslovnogo refleksa [Biology and Neurophysiology of Conditioned Reflex]. Moscow: Medicina.
  6. Barabanshchikov, V.A. 2012. Ekspressii litsa i ikh vospriiatie [Facial Expressions and Their Perception]. Moscow: Institut psikhologii RAN.
  7. Barabanshchikov, V.A., and E.G. Hoze. 2012. Konfigurativnye priznaki ekspressii spokoinogo litsa [Configurative Features of Expressions of Neutral Face]. Eksperimental’naia psihologiia 5 (1): 45–68.
  8. Ben, X., et al. 2021. Video-Based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (9): 5826–5846. https://doi.org/10.1109/TPAMI.2021.3067464
  9. Bhushan, B. 2015. Study of Facial Micro-Expressions in Psychology. In Understanding Facial Expressions in Communication, edited by M. Mandal and A. Awasthi, 265–286. New Delhi: Springer. https://doi.org/10.1007/978-81-322-1934-7_13
  10. Butovskaya, M.L. 2004. Yazyk tela: priroda i kul’tura [Body Language: Nature and Culture]. Moscow: Nauchnyi mir.
  11. Caeiro, C., et al. 2013. OrangFACS: A Muscle-Based Facial Movement Coding System for Orangutans (Pongo spp.). International Journal of Primatology 34: 115–129. https://doi.org/10.1007/s10764-012-9652-x
  12. Charlesworth, W.R., and M.A. Kreutzer. 2006. Facial Expressions of Infants and Children. In Darwin and Facial Expression: A Century of Research in Review, edited by P. Ekman, 91–168. Los Atlos: Malor Books.
  13. Cowen, A.S., et al. 2024. How Emotion is Experienced and Expressed in Multiple Cultures: A Large-Scale Experiment Across North America, Europe, and Japan. Frontiers in Psychology 15: 1350631. https://doi.org/10.3389/fpsyg.2024.1350631
  14. Dahl, C.D., C. Wallraven, H.H. Bülthoff, and N.K. Logothetis. 2009. Humans and Macaques Employ Similar Face-Processing Strategies. Current Biology 19 (6): 509–513. https://doi.org/10.1016/j.cub.2009.01.061
  15. Darwin, C.R. 1872. The Expression of the Emotions in Man and Animals. London: John Murray.
  16. Demetrioff, S., S. Porter, and A. Baker. 2016. I Know How You Feel: The Influence of Psychopathic Traits on the Ability to Identify Micro-Expressions. Psychology, Crime & Law 23 (3): 274–290. https://doi.org/10.1080/1068316X.2016.1247159
  17. Dong, Z., et al. 2022. Spontaneous Facial Expressions and Micro-Expressions Coding: From Brain to Face. Frontiers in Psychology 12: 784834. https://doi.org/10.3389/fpsyg.2021.784834
  18. Du, S., Y. Tao, and A.M. Martinez. 2014. Compound Facial Expressions of Emotion. Proceedings of the National Academy of Sciences USA 111 (15): E1454–E1462. https://doi.org/10.1073/pnas.1322355111
  19. Edery, R. 2019. Detecting Deception as a Probable Healing Tool for Clients: A Review of Dr. Paul Ekman. EC Psychology and Psychiatry 8: 212–217.
  20. Eggleston, A., M. Tsantani, H. Over, and R. Cook. 2022. Preferential Looking Studies of Trustworthiness Detection Confound Structural and Expressive Cues to Facial Trustworthiness. Scientific Reports 12 (1): 17709. https://doi.org/10.1038/s41598-022-21586-6
  21. Ekman, P. 1970. Universal Facial Expressions of Emotions. California Mental Health Research Digest 8 (4): 151–158.
  22. Ekman, P. 1972. Universals and Cultural Differences in Facial Expressions of Emotions. In Nebraska Symposium on Motivation, edited by J. Cole, 207–282. Lincoln: University of Nebraska Press.
  23. Ekman, P. 2002. Microexpression Training Tool (METT). Stanford: Technical Reports.
  24. Ekman, P., ed. 2006. Darwin and Facial Expression: A Century of Research in Review. Los Atlos: Malor Books.
  25. Ekman, P. 2009. Lie Catching and Microexpressions. In The Philosophy of Deception, edited by C. Martin, 118–135. New York: Oxford University Press.
  26. Ekman, P.E., and R.J. Davidson. 1994. The Nature of Emotion: Fundamental Questions. London: Oxford University Press.
  27. Ekman, P., and W.V. Friesen. 1969. Nonverbal Leakage and Clues to Deception. Psychiatry 32 (1): 88–106. https://doi.org/10.1080/00332747.1969.11023575
  28. Ekman, P., and W.V. Friesen. 1971. Constants Across Cultures in the Face and Emotion. Journal of Personality and Social Psychology 17 (2): 124–129. https://doi.org/10.1037/h0030377
  29. Ekman, P., and W.V. Friesen. 1978. Manual for the Facial Action Code. Palo Alto: Consulting Psychologist Press.
  30. Ekman, P., and W.V. Friesen. 1982. Felt, False, and Miserable Smiles. Journal of Nonverbal Behavior 6 (4): 238–252. https://doi.org/10.1007/BF00987191
  31. Ekman, P., W.V. Friesen, and P. Ellsworth. 2013. Emotion in the Human Face: Guidelines for Research and an Integration of Findings. New York: Pergamon Press Inc.
  32. Ekman, P., W.V. Friesen, and J.C. Hager. 2002. Facial Action Coding System: The Manual. Salt Lake City: Research Nexus Division of Network Research Corporation.
  33. Ekman, P., W.V. Friesen, and R.C. Simons. 1985. Is the Startle Reaction an Emotion? Journal of Personality and Social Psychology 49 (5): 1416.
  34. Ekman, P., E.R. Sorenson, and W.V. Friesen. 1969. Pan-Cultural Elements in Facial Display of Emotions. Science 164: 86–88. https://doi.org/10.1126/science.164.3875.86
  35. Elfenbein, H.A. 2013. Nonverbal Dialects and Accents in Facial Expressions of Emotion. Emotion Review 5 (1): 90–96. https://doi.org/10.1177/1754073912451332
  36. Elfenbein, H.A., and N. Ambady. 2002. On the Universality and Cultural Specificity of Emotion Recognition: A Meta-Analysis. Psychological Bulletin 128 (2): 203–235. https://doi.org/10.1037/0033-2909.128.2.203
  37. Esmaeili, M., and K. Kiani. 2024. Generating Personalized Facial Emotions Using Emotional EEG Signals and Conditional Generative Adversarial Networks. Multimedia Tools and Applications 83 (12): 36013–36038. https://doi.org/10.1007/s11042-023-17018-w
  38. Guerdelli, H., et al. 2022. Macro- and Micro-Expressions Facial Datasets: A Survey. Sensors 22 (4): 1524. https://doi.org/10.3390/s22041524
  39. Hoze, E.G., et al. 2019. Kross-kul’turnye osobennosti vospriiatiia bazovyh emotsional’nyh ekspressii litsa [Cross-Cultural Features of Perception of Basic Emotional Facial Expressions]. In Litso cheloveka: poznanie, obshchenie, deiatel’nost’ [The Human Face: Cognition, Communication, Activity], edited by K.I. Ananyeva, V.A. Barabanshchikov, and A.A. Demidov, 506–515. Moscow: Moskovskii institut psihoanaliza.
  40. Hurley, C.M., et al. 2014. Background Factors Predicting Accuracy and Improvement in Micro Expression Recognition. Motivation and Emotion 38: 700–714. https://doi.org/10.1007/s11031-014-9410-9
  41. Fang, X., D.A. Sauter, M.W. Heerdink, and G.A. van Kleef. 2022. Culture Shapes the Distinctiveness of Posed and Spontaneous Facial Expressions of Anger and Disgust. Journal of Cross-Cultural Psychology 53 (5): 471–487. https://doi.org/10.1177/00220221221095208
  42. Fox, E. 2018. Perspectives from Affective Science on Understanding the Nature of Emotion. Brain and Neuroscience Advances 2: 2398212818812628. https://doi.org/10.1177/2398212818812628
  43. Frank, M., et al. 2009. I See How You Feel: Training Laypeople and Professionals to Recognize Fleeting Emotions. The Annual Meeting of the International Communication Association, Sheraton, New York, New York City: 1–35.
  44. Frank, M.G., and E. Svetieva. 2015. Microexpressions and Deception. In Understanding Facial Expressions in Communication: Cross-Cultural and Multidisciplinary Perspectives, edited by M. Mandal and A. Awasthi, 227–242. New Delhi: Springer. https://doi.org/10.1007/978-81-322-1934-7_11
  45. Freeberg, T.M., R.I.M. Dunbar, and T.J. Ord. 2012. Social Complexity as a Proximate and Ultimate Factor in Communicative Complexity Introduction. Philosophical Transactions of the Royal Society B-Biological Sciences 367: 1785–1801. https://doi.org/10.1098/rstb.2011.0213
  46. Haggard, E.A., and K.S. Isaacs. 1966. Micromomentary Facial Expressions as Indicators of Ego Mechanisms in Psychotherapy. In Methods of Research in Psychotherapy, edited by L.A. Gottschalk and A.H. Auerbach, 154–165. Boston: Springer. https://doi.org/10.1007/978-1-4684-6045-2_14
  47. Hester, N. 2019. Perceived Negative Emotion in Neutral Faces: Gender-Dependent Effects on Attractiveness and Threat. Emotion 19 (8): 1490–1494. http://dx.doi.org/10.1037/emo0000525
  48. Höfling, T.T.A., A.B. Gerdes, U. Föhl, and G.W. Alpers. 2020. Read My Face: Automatic Facial Coding Versus Psychophysiological Indicators of Emotional Valence and Arousal. Frontiers in Psychology 11: 1388. https://doi.org/10.3389/fpsyg.2020.01388
  49. Iwasaki, M., and Y. Noguchi. 2016. Hiding True Emotions: Micro-Expressions in Eyes Retrospectively Concealed by Mouth Movements. Scientific Reports 6 (1): 22049. https://doi.org/10.1038/srep22049
  50. Jaeger, B., and A.L. Jones. 2022. Which Facial Features are Central in Impression Formation? Social Psychological and Personality Science 13 (2): 553–561. https://doi.org/10.1177/19485506211034979
  51. Julle-Danière, E., et al. 2015. MaqFACS (Macaque Facial Action Coding System) Can Be Used to Document Facial Movements in Barbary Macaques (Macaca sylvanus). PeerJ 3: e1248. https://doi.org/10.7717/peerj.1248
  52. Larsen, J.T., et al. 2008. The Psychophysiology of Emotion. In Handbook of Emotions, edited by M. Lewis, J.M. Haviland-Jones, and L.F. Barrett, 180–195. N.Y.: The Guilford Press.
  53. Li, J. 2019. Facial Micro-Expression Analysis: Computer Vision and Pattern Recognition. PhD diss., CentraleSupélec.
  54. Li, X., et al. 2022. 4DME: A Spontaneous 4D Micro-Expression Dataset with Multimodalities. IEEE Transactions on Affective Computing 14 (4): 3031–3047. https://doi.org/10.1109/TAFFC.2022.3182342
  55. Li, Y., X. Huang, and G. Zhao. 2018. Can Micro-Expression be Recognized Based on Single Apex Frame? In 2018 25th IEEE International Conference on Image Processing (ICIP), 3094–3098. Athens: IEEE. https://doi.org/10.1109/ICIP.2018.8451376
  56. Liong, S.T., and K. Wong. 2017. Micro-Expression Recognition Using Apex Frame with Phase Information. In 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 534–537. Kuala Lumpur: IEEE.
  57. Lindquist, K.A., et al. 2022. The Cultural Evolution of Emotion. Nature Reviews Psychology 1 (11): 669–681. https://doi.org/10.1038/s44159-022-00105-4
  58. Krautheim, J.T., et al. 2020. Emotion Specific Neural Activation for the Production and Perception of Facial Expressions. Cortex 127: 17–28. https://doi.org/10.1016/j.cortex.2020.01.026
  59. Mandal, M.K., and A. Awasthi, eds. 2015. Understanding Facial Expressions in Communication: Cross-Cultural and Multidisciplinary Perspectives. New Delhi: Springer.
  60. Matsumoto, D. 2006. Culture and Nonverbal Behavior. In The SAGE Handbook of Nonverbal Communication, edited by V. Manusov and M.L. Patterson, 219–235. Thousand Oaks: SAGE Publications.
  61. Matsumoto, D., and H.S. Hwang. 2011. Evidence for Training the Ability to Read Microexpressions of Emotion. Motivation and Emotion 35: 181–191. https://doi.org/10.1007/s11031-011-9212-2
  62. Matsumoto, D., and H.C. Hwang. 2018. Microexpressions Differentiate Truths from Lies about Future Malicious Intent. Frontiers in Psychology 9: 2545. https://doi.org/10.3389/fpsyg.2018.02545
  63. Müri, R.M. 2016. Cortical Control of Facial Expression. Journal of Comparative Neurology 524 (8): 1578–1585. https://doi.org/10.1002/cne.23908
  64. Okon-Singer, H., T. Hendler, L. Pessoa, and A.J. Shackman. 2015. The Neurobiology of Emotion–Cognition Interactions: Fundamental Questions and Strategies for Future Research. Frontiers in Human Neuroscience 9: 58. https://doi.org/10.3389/fnhum.2015.00058
  65. Oh, Y.H., et al. 2018. A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges. Frontiers in Psychology 9: 1128. https://doi.org/10.3389/fpsyg.2018.01128
  66. Panksepp, J. 2004. Affective Neuroscience: The Foundations of Human and Animal Emotions. London: Oxford University Press.
  67. Pavlov, I.P. 1951. Dvadtsatiletnii opyt ob’ektivnogo izucheniia vysshei nervnoi deiatel’nosti (povedeniia) zhivotnyh. Polnoe sobranie sochinenii [Twenty Years of Experience in the Objective Study of Higher Nervous Activity (Behavior) of Animals: Complete Works]. Moscow; St. Petersburg: Izdatel’stvo AN SSSR.
  68. Pessoa, L. 2008. On the Relationship Between Emotion and Cognition. Nature Reviews Neuroscience 9 (2): 148–158. https://doi.org/10.1038/nrn2317
  69. Polikovsky, S., Y. Kameda, and Y. Ohta. 2009. Facial Micro-Expressions Recognition Using High Speed Camera and 3D-gradient Descriptor. In 3rd International Conference on Imaging for Crime Detection and Prevention, 16. London. https://doi.org/10.1049/ic.2009.0244
  70. Porter, S., and L. Ten Brinke. 2008. Reading Between the Lies: Identifying Concealed and Falsified Emotions in Universal Facial Expressions. Psychological Science 19 (5): 508–514. https://doi.org/10.1111/j.1467-9280.2008.02116.x
  71. Rinn, W.E. 1984. The Neuropsychology of Facial Expression: A Review of the Neurological and Psychological Mechanisms for Producing Facial Expressions. Psychological Bulletin 95 (1): 52. https://doi.org/10.1037/0033-2909.95.1.52
  72. Rolls, E.T. 2015. Limbic Systems for Emotion and for Memory, but No Single Limbic System. Сortex 62: 119–157. https://doi.org/10.1016/j.cortex.2013.12.005
  73. Russell, J.A., and J.M. Fernandez-Dols, eds. 1997. The Psychology of Facial Expression. Melbourne: Cambridge University Press.
  74. Parr, L.A., et al. 2010. Brief Communication: MaqFACS: A Muscle Based Facial Movement Coding System for the Rhesus Macaque. American Journal of Physical Anthropology 143: 433–445. https://doi.org/10.1002/ajpa.21401
  75. Pfister, T., X. Li, G. Zhao, and M. Pietikäinen. 2011. Differentiating Spontaneous from Posed Facial Expressions within a Generic Facial Expression Recognition Framework. In 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 868–875. Barselona: IEEE. https://doi.org/10.1109/ICCVW.2011.6130343
  76. Pohl, A., et al. 2013. Positive Facial Affect – an fMRI Study on the Involvement of Insula and Amygdala. PLoS One 8 (8): e69886. https://doi.org/10.1371/journal.pone.0069886
  77. Rincon, A.V., et al. 2023. Higher Social Tolerance is Associated with More Complex Facial Behavior in Macaques. Elife 12: RP87008. https://doi.org/10.7554/eLife.87008.3
  78. Rostovtseva, V.V., and M.L. Butovskaya. 2022. Neitral’noe litso cheloveka neset otpechatok ego emotsional’nosti [Human Neutral Face Bears an Imprint of Emotionality]. Etnograficheskoe obozrenie 6: 160–177. https://doi.org/10.31857/S0869541522060094
  79. Shen, X.B., Q. Wu, and X.L. Fu. 2012. Effects of the Duration of Expressions on the Recognition of Microexpressions. Journal of Zhejiang University Science B 13: 221–230. https://doi.org/10.1631/jzus.B1100063
  80. Shreve, M., et al. 2009. Towards Macro- and Micro-Expression Spotting in Video Using Strain Patterns. In 2009 Workshop on Applications of Computer Vision (WACV), 1–6. Snowbird: IEEE. https://doi.org/10.1109/WACV.2009.5403044
  81. Svetieva, E., and M.G. Frank. 2016. Empathy, Emotion Dysregulation, and Enhanced Microexpression Recognition Ability. Motivation and Emotion 40: 309–320. https://doi.org/10.1007/s11031-015-9528-4
  82. Todorov, A., and D. Oh. 2021. The Structure and Perceptual Basis of Social Judgments from Faces. Advances in Experimental Social Psychology 63: 189–245. https://doi.org/10.1016/bs.aesp.2020.11.004
  83. Tomkins, S.S., and R. McCarter. 1964. What and Where are the Primary Affects? Some Evidence for a Theory. Perceptual and Motor Skills 18 (1): 119–158.
  84. Tsikandilakis, M., et al. 2023. Learning Emotional Dialects: A British Population Study of Cross-Cultural Communication. Perception 52 (11–12): 812–843. https://doi.org/10.1177/03010066231204180
  85. Van Hooff, J.A.R.A.M. 1967. The Facial Displays of the Catarrhine Monkeys and Apes. In Primate Ethology, edited by D. Morris, 7–68. London: Weidenfels and Nicolson.
  86. Vick, S.J., et al. 2007. A Cross-Species Comparison of Facial Morphology and Movement in Humans and Chimpanzees Using the Facial Action Coding System (FACS). Journal of Nonverbal Behavior 31: 1–20. https://doi.org/10.1007/s10919-006-0017-z
  87. Vrij, A. 2019. Deception and Truth Detection when Analyzing Nonverbal and Verbal Cues. Applied Cognitive Psychology 33 (2): 160–167. https://doi.org/10.1002/acp.3457
  88. Waller, B.M., et al. 2008. Mapping the Contribution of Single Muscles to Facial Movements in the Rhesus Macaque. Physiology & Behavior 95: 93–100. https://doi.org/10.1016/j.physbeh.2008.05.002
  89. Waller, B.M., et al. 2012. GibbonFACS: A Muscle-Based Facial Movement Coding System for Hylobatids. International Journal of Primatology 33: 809–821. https://doi.org/10.1007/s10764-012-9611-6
  90. Waller, B.M., et al. 2013. Paedomorphic Facial Expressions Give Dogs a Selective Advantage. PLoS One 8: e82686. https://doi.org/10.1371/journal.pone.0082686
  91. Warren, G., E. Schertler, and P. Bull. 2009. Detecting Deception from Emotional and Unemotional Cues. Journal of Nonverbal Behavior 33: 59–69. https://doi.org/10.1007/s10919-008-0057-7
  92. Wathan, J., A.M. Burrows, B.M. Waller, and K. McComb. 2015. EquiFACS: The Equine Facial Action Coding System. PLoS One 10 (8): e0131738. https://doi.org/10.1371/journal.pone.0131738
  93. Weber, R., J. Li, C. Soladié, and R. Séguier. 2019. A Survey on Databases of Facial Macro-Expression and Micro-Expression. In Computer Vision, Imaging and Computer Graphics Theory and Applications: 13th International Joint Conference, VISIGRAPP 2018 Funchal–Madeira, Portugal, January 27–29, 2018, edited by D. Bechmann, et al., 298–325. Cham: Springer.
  94. Weinberger, S. 2010. Airport Security: Intent to Deceive? Nature 465 (7297): 412–416.
  95. Whitehouse, J., et al. 2024. Facial Expressivity in Dominant Macaques is Linked to Group Cohesion. Proceedings of the Royal Society B 291 (2027): 20240984. https://doi.org/10.1098/rspb.2024.0984
  96. Xie, H.X., L. Lo, H.H. Shuai, and W.H. Cheng. 2022. An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge. IEEE Transactions on Affective Computing 14 (3): 1857–1875. https://doi.org/10.1109/TAFFC.2022.3143100
  97. Yan, W.J., et al. 2013. How Fast are the Leaked Facial Expressions: The Duration of Micro-Expressions? Journal of Nonverbal Behavior 37: 217–230. https://doi.org/10.1007/s10919-013-0159-8
  98. Yildirim, S., M.S. Chimeumanu, and Z.A. Rana. 2023. The Influence of Micro-Expressions on Deception Detection. Multimedia Tools and Applications 82 (19): 29115–29133. https://doi.org/10.1007/s11042-023-14551-6
  99. Zhao, G., X. Li, Y. Li, and M. Pietikäinen. 2023. Facial Micro-Expressions: An Overview. Proceedings of the IEEE 111 (10): 1215–1235. https://doi.org/10.1109/JPROC.2023.3275192
  100. Zhao, Y., and J. Xu. 2019. A Convolutional Neural Network for Compound Micro-Expression Recognition. Sensors 19 (24): 5553. https://doi.org/10.3390/s19245553

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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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