The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
A systematic review and meta-analysis of facial emotion recognition in autism spectrum disorder: The specificity of deficits and the role of task characteristics
Abstract
This review assessed the specificity of facial emotion recognition impairment and the role of task characteristics in facial emotion recognition in autism spectrum disorder (ASD). Based on subsets of 148 studies identified in PubMed and PsycINFO, random-effects meta-analyses showed significant impairment in recognizing all basic facial emotions in ASD. Additionally, ASD involves poorer facial emotion recognition than other clinical conditions and has similar impairment in recognizing emotional and nonemotional facial attributes, as well as in recognizing emotion in faces and other modalities. Furthermore, there are significant moderating effects for emotion complexity and holistic processing, a statistical trend for task type, and no significant effect for motion, social relevance, or stimulus salience on facial emotion recognition in ASD. Altogether, this review suggests nonselective facial emotion recognition impairment in ASD. Such impairment is relatively specific to ASD but is not specific to the recognition of emotional facial attributes or emotion recognition in the face modality. Identifying the role of task characteristics improves our understanding of the mechanisms underlying facial emotion recognition in ASD.
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“Similar to the current findings, Sapey-Triomphe and colleagues reported a comparable perception of tonic volatility combined with altered response model parameters [13] and modified neural correlates of prediction [14] in a probabilistic associative learning task.”
From Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework (2026) · cites this paper as [13]
In the citing paper
“Multiple studies using the HGF have now documented this similarity: probabilistic associative learning tasks [13, 14], the Wisconsin Card-Sorting task measuring cognitive flexibility and set-shifting [15] and a size-illusion task [16], experiment [9].”
From Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework (2026) · cites this paper as [13]
In the citing paper
“For example, a recent study by Shi et al. [5] investigated prior updating in ASD using the central tendency effect in combination with Kalman. They found an initial underweighting of priors in autistic adults, resonating with some previous findings indicating atypical priors [13, 56], which normalised by the end of the task, resonating with contrasting previous findings of intact priors in ASD [57”
From Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework (2026) · cites this paper as [13]
Citations
Cites
Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722
Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & the PRISMA Group* (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-4-200908180-00135 · Cited by 37,554
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
Duval, S., & Tweedie, R. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00455.x · Cited by 14,099
The expression of the emotions in man and animals.
Darwin, C. D. (1872) · J. Murray eBooks · doi:10.1037/10001-000 · Cited by 12,120
The combination of estimates from different experiments
Cochran, W. G. (1954) · Biometrics · doi:10.2307/3001666 · Cited by 5,380
JBI Manual for Evidence Synthesis
(2020) · JBI eBooks · doi:10.46658/jbimes-20-01 · Cited by 4,165
The weak coherence account: detail-focused cognitive style in autism spectrum disorders
Happé, F., & Frith, U. (2006) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-005-0039-0 · Cited by 2,884
Chapter 7: Systematic reviews of etiology and risk
Moola, S., Munn, Z., Tufanaru, C., Aromataris, E., Sears, K., Sfetic, R., Currie, M., Lisy, K., Qureshi, R., Mattis, P., et al. (2019) · JBI Reviewer's Manual · doi:10.46658/jbirm-17-06 · Cited by 2,114
Neural systems for recognizing emotion
Adolphs, R. (2002) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(02)00301-x · Cited by 1,933
Jones, H. E. (2010) · Paediatric and Perinatal Epidemiology · doi:10.1111/j.1365-3016.2010.01108.x · Cited by 1,447
Harms, M. B., Martin, A., & Wallace, G. L. (2010) · Neuropsychology Review · doi:10.1007/s11065-010-9138-6 · Cited by 1,028
Intercoder Reliability and Validity of WebPlotDigitizer in Extracting Graphed Data
Drevon, D., Fursa, S. R., & Malcolm, A. L. (2017) · Behavior Modification · doi:10.1177/0145445516673998 · Cited by 1,006
Baron‐Cohen, S., Wheelwright, S. J., & Jolliffe, T. (1997) · Visual Cognition · doi:10.1080/713756761 · Cited by 990
Emotion knowledge as a predictor of social behavior and academic competence in children at risk
Izard, C., Fine, S., Schultz, D., Mostow, A., Ackerman, B., & Youngstrom, E. (2001) · Psychological Science · doi:10.1111/1467-9280.00304 · Cited by 853
Recognition of Emotions in Autism: A Formal Meta-Analysis
Uljarevic, M., & Hamilton, A. (2013) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-012-1695-5 · Cited by 824
Diagnostic and Statistical Manual of Mental Disorders (DSM)
Cooper, R. (2017) · KNOWLEDGE ORGANIZATION · doi:10.5771/0943-7444-2017-8-668 · Cited by 780
A refined method for the meta-analysis of controlled clinical trials with binary outcome
Hartung, J., & Knapp, G. (2001) · Statistics in Medicine · doi:10.1002/sim.1009 · Cited by 775
Language as context for the perception of emotion
Barrett, L. F., Lindquist, K. A., & Gendron, M. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.06.003 · Cited by 762
Simulationist models of face-based emotion recognition
Goldman, A. I., & Sripada, C. S. (2005) · Cognition · doi:10.1016/j.cognition.2004.01.005 · Cited by 647
How to calculate effect sizes from published research: A simplified methodology
Thalheimer, W., & Cook, S. (2002) · Cited by 571
Facial expressions of emotion (KDEF): Identification under different display-duration conditions
Calvo, M. G., & Lundqvist, D. (2008) · Behavior Research Methods · doi:10.3758/brm.40.1.109 · Cited by 539
Face identity recognition in autism spectrum disorders: A review of behavioral studies
Weigelt, S., Koldewyn, K., & Kanwisher, N. (2011) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2011.12.008 · Cited by 513
A simple confidence interval for meta-analysis
Sidik, K., & Jonkman, J. N. (2002) · Statistics in Medicine · doi:10.1002/sim.1262 · Cited by 431
The perception and categorisation of emotional stimuli: A review
Brosch, T., Pourtois, G., & Sander, D. (2009) · Cognition & Emotion · doi:10.1080/02699930902975754 · Cited by 412
Emotion Perception from Face, Voice, and Touch: Comparisons and Convergence
Schirmer, A., & Adolphs, R. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.01.001 · Cited by 406
Bora, E., & Pantelis, C. (2015) · Psychological Medicine · doi:10.1017/s0033291715002573 · Cited by 360
Hoffmann, H., Kessler, H., Eppel, T., Rukavina, S., & Traue, H. C. (2010) · Acta Psychologica · doi:10.1016/j.actpsy.2010.07.012 · Cited by 335
Language and the perception of emotion.
Lindquist, K. A., Barrett, L. F., Bliss‐Moreau, E., & Russell, J. A. (2006) · Emotion · doi:10.1037/1528-3542.6.1.125 · Cited by 326
Impairments in facial affect recognition associated with autism spectrum disorders: A meta-analysis
Lozier, L. M., VanMeter, J. W., & Marsh, A. A. (2014) · Development and Psychopathology · doi:10.1017/s0954579414000479 · Cited by 324
Black, M. H., Chen, N. T. M., Iyer, K. K., Lipp, O. V., Bölte, S., Falkmer, M., Tan, T., & Girdler, S. J. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.06.016 · Cited by 279
Motion and Emotion: A Novel Approach to the Study of Face Processing by Young Autistic Children
Gepner, B., Deruelle, C., & Grynfeltt, S. (2001) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1005609629218 · Cited by 249
Smith, M. J. L., Montagne, B., Perrett, D. I., Gill, M., & Gallagher, L. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2010.03.008 · Cited by 229
Clark, T. F., Winkielman, P., & McIntosh, D. N. (2008) · Emotion · doi:10.1037/a0014124 · Cited by 203
Piggot, J., Kwon, H., Mobbs, D., Blasey, C., Lotspeich, L., Menon, V., Bookheimer, S., & Reiss, A. L. (2004) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/00004583-200404000-00014 · Cited by 201
Basic and complex emotion recognition in children with autism: cross-cultural findings
Fridenson-Hayo, S., Berggren, S., Lassalle, A., Tal, S., Pigat, D., Bölte, S., Baron‐Cohen, S., & Golan, O. (2016) · Molecular Autism · doi:10.1186/s13229-016-0113-9 · Cited by 197
Emotion Recognition: The Role of Featural and Configural Face Information
Bombari, D., Schmid, P. C., Mast, M. S., Birri, S., Mast, F. W., & Lobmaier, J. S. (2013) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2013.789065 · Cited by 194
Facial emotion recognition in child psychiatry: A systematic review
Collin, L., Bindra, J., Raju, M., Gillberg, C., & Minnis, H. (2013) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2013.01.008 · Cited by 183
Gross, T. F. (2004) · Research on Child and Adolescent Psychopathology · doi:10.1023/b:jacp.0000037777.17698.01 · Cited by 181
A new look at emotion perception: Concepts speed and shape facial emotion recognition.
Nook, E. C., Lindquist, K. A., & Zaki, J. (2015) · Emotion · doi:10.1037/a0039166 · Cited by 147
Impaired recognition of facial emotions from low-spatial frequencies in Asperger syndrome
Kätsyri, J., Saalasti, S., Tiippana, K. M., von Wendt, L., & Sams, M. E. (2008) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2008.01.005 · Cited by 104
Emotion recognition of static and dynamic faces in autism spectrum disorder
Enticott, P. G., Kennedy, H. A., Johnston, P., Rinehart, N., Tonge, B. J., Taffe, J. R., & Fitzgerald, P. B. (2013) · Cognition & Emotion · doi:10.1080/02699931.2013.867832 · Cited by 74
Recognition of Emotional Expressions is Affected by Inversion and Presentation Time
Derntl, B., Seidel, E., Kainz, E., & Carbon, C. (2009) · Perception · doi:10.1068/p6448 · Cited by 69
Doi, H., Fujisawa, T. X., Kanai, C., Ohta, H., Yokoi, H., Iwanami, A., Kato, N., & Shinohara, K. (2013) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-013-1760-8 · Cited by 57
Lau, J. Y. F., Burt, D. M., Leibenluft, E., Pine, D. S., Rijsdijk, F. V., Shiffrin, N. D., & Eley, T. C. (2009) · Developmental Neuropsychology · doi:10.1080/87565640802564424 · Cited by 42
Yeung, M. K.-C., Lee, T., & Chan, A. S.-Y. (2019) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-019-03915-3 · Cited by 29
Self-citationRhodes, G., Burton, N. S., Jeffery, L., Read, A., Taylor, L., & Ewing, L. (2017) · British Journal of Psychology · doi:10.1111/bjop.12257 · Cited by 16
Research works printed but not linked: 1
- Schwarzer, 2015, Vol. 4784
Cited by
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Emotion Recognition in Children and Adolescents with ASD and ADHD: a Systematic Review
Lievore, R., Crisci, G., & Mammarella, I. C. (2023) · Review Journal of Autism and Developmental Disorders · doi:10.1007/s40489-023-00407-0 · Cited by 93
Human emotion recognition using Machine learning techniques based on the physiological signal
Kumar, A., & Kumar, A. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107039 · Cited by 50
Zhao, W., Liu, Q., Zhang, X., Song, X., Zhang, Z., Qing, P., Liu, X., Zhu, S., Yang, W., & Kendrick, K. M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120263 · Cited by 33
Kausel, L., Michon, M., Soto‐Icaza, P., & Aboitiz, F. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae066 · Cited by 28
Cortico-cortical transfer of socially derived information gates emotion recognition
Dautan, D., Monai, A., Maltese, F., Chang, X., Molent, C., Mauro, D., Galbusera, A., Vecchia, D., Antonelli, F., Benedetti, A., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01647-x · Cited by 27
Metadata
- Authors
- Yeung, M. K.
- Affiliations
- Montreal Neurological Institute and Hospital (CA)
- Corresponding author
- Yeung, Michael K.
- ORCID
- Yeung, Michael K.
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2022-02
- Volume
- 133
- Pages
- 104518
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W4205331548
- Cited by
- 187
- References
- 47
- Citations by year
- 2026: 46 · 2025: 47 · 2024: 62 · 2023: 29 · 2022: 3
- FWCI
- 3.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Neuroscience & Biobehavioral Reviews (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Keywords
- autism spectrum disorder, facial emotion recognition, basic emotions, task characteristics, holistic processing, facial attributes, social cognition
- MeSH terms
- Facial Recognition, Autism Spectrum Disorder, Emotions, Facial Expression, Humans, Recognition, Psychology
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