Probabilistic learning of emotion categories
Open accessAbstract
Although the configurations of facial muscles that humans perceive vary continuously, we often represent emotions as categories. This suggests that, as in other domains of categorical perception such as speech and color perception, humans become attuned to features of emotion cues that map onto meaningful thresholds for these signals given their environments. However, little is known about the learning processes underlying the representation of these salient social signals. In Experiment 1 we test the role of statistical distributions of facial cues in the maintenance of an emotion category in both children (6-8 years old) and adults (18-22 years old). Children and adults learned the boundary between neutral and angry when provided with explicit feedback (supervised learning). However, after we exposed participants to different statistical distributions of facial cues, they rapidly shifted their category boundaries for each emotion during a testing phase. In Experiments 2 and 3, we replicated this finding and also tested the extent to which learners are able to track statistical distributions for multiple actors. Not only did participants form actor-specific categories, but the distributions of facial cues also influenced participants' trait judgments about the actors. Taken together, these data are consistent with the view that the way humans construe emotion (in this case, anger) is not only flexible, but reflects complex learning about the distributions of the myriad cues individuals experience in their social environments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835 · see citing works
An argument for basic emotions
Ekman, P. (1992) · Cognition and Emotion · doi:10.1080/02699939208411068 · Cited by 9,646 · see citing works
Baron‐Cohen, S., Wheelwright, S. J., Hill, J., Raste, Y., & Plumb, I. (2001) · PubMed · Cited by 4,313 · see citing works
The NimStim set of facial expressions: Judgments from untrained research participants.
Tottenham, N., Tanaka, J. W., Leon, A. C., McCarry, T., Nurse, M., Hare, T. A., Marcus, D. J., Westerlund, A., Casey, B., & Nelson, C. (2009) · Psychiatry Research · doi:10.1016/j.psychres.2008.05.006 · Cited by 3,454 · see citing works
Emotion, regulation, and moral development
Eisenberg, N. (2000) · Annual Review of Psychology · doi:10.1146/annurev.psych.51.1.665 · Cited by 2,422 · see citing works
Why faces are and are not special: An effect of expertise.
Diamond, R., & Carey, S. E. (1986) · Journal of Experimental Psychology General · doi:10.1037//0096-3445.115.2.107 · Cited by 1,584 · see citing works
Word Segmentation: The Role of Distributional Cues
Saffran, J. R., Newport, E. L., & Aslin, R. N. (1996) · Journal of Memory and Language · doi:10.1006/jmla.1996.0032 · Cited by 1,405 · cited 1× · see citing works
“…unsupervised learning aids in aspects of language acquisition such as phonemic discrimination and word segmentation (Maye, Werker, & Gerken, 2002; Saffran, Newport, & Aslin, 1996), where children could not be provided with sufficient explicit labeling of relevant distinctions between stimuli.”
BackgroundInfant sensitivity to distributional information can affect phonetic discrimination
Maye, J., Werker, J. F., & Gerken, L. (2002) · Cognition · doi:10.1016/s0010-0277(01)00157-3 · Cited by 1,364 · see citing works
Why faces are and are not special: An effect of expertise.
Diamond, R., & Carey, S. E. (1986) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.115.2.107 · Cited by 1,309 · see citing works
Sex differences in emotion: Expression, experience, and physiology.
Kring, A. M., & Gordon, A. H. (1998) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.74.3.686 · Cited by 1,067 · cited 1× · see citing works
“Substantial variability in expressivity exists (Friedman, Prince, Riggio, & DiMatteo, 1980), some resulting from personality (Friedman, DiMatteo, & Taranta, 1980) and gender (Kring & Gordon, 1998), such that some individuals are more expressive facially than others.”
BackgroundBarrett, L. F., Mesquita, B., & Gendron, M. (2011) · Current Directions in Psychological Science · doi:10.1177/0963721411422522 · Cited by 935 · see citing works
Brain mechanisms for emotional influences on perception and attention: What is magic and what is not
Pourtois, G., Schettino, A., & Vuilleumier, P. (2013) · Biological Psychology · doi:10.1016/j.biopsycho.2012.02.007 · Cited by 687 · see citing works
Categorical perception of facial expressions.
Etcoff, N., & Magee, J. J. (1992) · Cognition · doi:10.1016/0010-0277(92)90002-y · Cited by 587 · see citing works
Brauer, M., & Curtin, J. J. (2018) · Psychological Methods · doi:10.1037/met0000159 · Cited by 555 · see citing works
Pollak, S. D., & Kistler, D. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.142165999 · Cited by 475 · see citing works
Self-citationCategorical Perception of Morphed Facial Expressions
Calder, A. J., Young, A. W., Perrett, D. I., Etcoff, N. L., & Rowland, D. (1996) · Visual Cognition · doi:10.1080/713756735 · Cited by 416 · see citing works
Development of infants’ attention to faces during the first year
Frank, M. C., Vul, E., & Johnson, S. P. (2008) · Cognition · doi:10.1016/j.cognition.2008.11.010 · Cited by 415 · see citing works
Understanding and assessing nonverbal expressiveness: The Affective Communication Test.
Friedman, H. S., Prince, L. M., Riggio, R. E., & DiMatteo, M. R. (1980) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.39.2.333 · Cited by 343 · see citing works
Language is not Just for Talking
Lupyan, G., Rakison, D. H., & McClelland, J. L. (2007) · Psychological Science · doi:10.1111/j.1467-9280.2007.02028.x · Cited by 327 · see citing works
Alison Gopnik, C., O’Grady, S., Lucas, C. G., Griffiths, T. L., Wente, A., Bridgers, S., Aboody, R., Fung, H., & Dahl, R. E. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1700811114 · Cited by 324 · see citing works
Development of perceptual expertise in emotion recognition
Pollak, S. D., Messner, M., Kistler, D. J., & Cohn, J. F. (2008) · Cognition · doi:10.1016/j.cognition.2008.10.010 · Cited by 302 · see citing works
Self-citationPsychological Construction in the OCC Model of Emotion
Clore, G. L., & Ortony, A. (2013) · Emotion Review · doi:10.1177/1754073913489751 · Cited by 260 · see citing works
Comparing supervised and unsupervised category learning
Love, B. C. (2002) · Psychonomic Bulletin & Review · doi:10.3758/bf03196342 · Cited by 242 · see citing works
Influence of intensity on children’s sensitivity to happy, sad, and fearful facial expressions
Gao, X., & Maurer, D. M. (2009) · Journal of Experimental Child Psychology · doi:10.1016/j.jecp.2008.11.002 · Cited by 204 · see citing works
Rychlowska, M., Miyamoto, Y., Matsumoto, D., Heß, U., Gilboa‐Schechtman, E., Kamble, S. V., Muluk, H., Masuda, T., & Niedenthal, P. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1413661112 · Cited by 191 · see citing works
Smiles as Multipurpose Social Signals
Martin, J., Rychlowska, M., Wood, A., & Niedenthal, P. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.08.007 · Cited by 187 · see citing works
Self-citationCategorical Perception of Happiness and Fear Facial Expressions: An ERP Study
Campanella, S., Quinet, P., Bruyer, R., Crommelinck, M., & Guérit, J. M. (2002) · Journal of Cognitive Neuroscience · doi:10.1162/089892902317236858 · Cited by 177 · see citing works
Holistic person processing: Faces with bodies tell the whole story.
Aviezer, H., Yaacov Trope, B., & Todorov, A. T. (2012) · Journal of Personality and Social Psychology · doi:10.1037/a0027411 · Cited by 173 · see citing works
Functionalism cannot save the classical view of emotion
Barrett, L. F. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw156 · Cited by 163 · see citing works
Human and computer recognition of facial expressions of emotion
Susskind, J., Littlewort, G. C., Bartlett, M. S., Movellan, J. R., & Anderson, A. K. (2006) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2006.05.001 · Cited by 158 · see citing works
Prevalence-induced concept change in human judgment
Levari, D. E., Gilbert, D. T., Wilson, T. D., Sievers, B., Amodio, D. M., & Wheatley, T. P. (2018) · Science · doi:10.1126/science.aap8731 · Cited by 145 · see citing works
Categorical Perception of Facial Expressions: Categories and their Internal Structure
de Gelder, B., Teunisse, J., & Benson, P. J. (1997) · Cognition & Emotion · doi:10.1080/026999397380005 · Cited by 141 · see citing works
Fuzzy Concepts and the Perception of Emotion in Facial Expressions
Russell, J. A., & Bullock, M. (1986) · Social Cognition · doi:10.1521/soco.1986.4.3.309 · Cited by 123 · see citing works
The development of social brain functions in infancy.
Großmann, T. (2015) · Psychological Bulletin · doi:10.1037/bul0000002 · Cited by 110 · see citing works
Heterogeneity of long-history migration predicts emotion recognition accuracy.
Wood, A., Rychlowska, M., & Niedenthal, P. M. (2016) · Emotion · doi:10.1037/emo0000137 · Cited by 85 · see citing works
Self-citationCognitive penetrability and emotion recognition in human facial expressions
Marchi, F., & Newen, A. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00828 · Cited by 84 · see citing works
Altering sensorimotor feedback disrupts visual discrimination of facial expressions
Wood, A., Lupyan, G., Sherrin, S., & Niedenthal, P. M. (2015) · Psychonomic Bulletin & Review · doi:10.3758/s13423-015-0974-5 · Cited by 84 · see citing works
Self-citationFriedman, H. S., DiMatteo, M. R., & Taranta, A. (1980) · Journal of Research in Personality · doi:10.1016/0092-6566(80)90018-5 · Cited by 61 · see citing works
When a word is worth a thousand pictures: Language shapes perceptual memory for emotion.
Doyle, C. M., & Lindquist, K. A. (2018) · Journal of Experimental Psychology General · doi:10.1037/xge0000361 · Cited by 58 · see citing works
Developmental changes in the primacy of facial cues for emotion recognition.
Leitzke, B. T., & Pollak, S. D. (2016) · Developmental Psychology · doi:10.1037/a0040067 · Cited by 50 · see citing works
Self-citationFeelings and contexts: socioecological influences on the nonverbal expression of emotion
Niedenthal, P. M., Rychlowska, M., & Wood, A. (2017) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2017.07.025 · Cited by 34 · see citing works
Self-citationCan semi-supervised learning explain incorrect beliefs about categories?
Kalish, C. W., Rogers, T. T., Lang, J. S., & Zhu, X. (2011) · Cognition · doi:10.1016/j.cognition.2011.03.002 · Cited by 28 · see citing works
Historical Heterogeneity Predicts Smiling: Evidence from Large-Scale Observational Analyses
Girard, J. M., & McDuff, D. (2017) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2017.135 · Cited by 24 · see citing works
Pre-verbal infants perceive emotional facial expressions categorically
Cong, Y.-Q., Junge, C., Aktar, E., Raijmakers, M. E. J., Franklin, A., & Sauter, D. A. (2018) · Cognition & Emotion · doi:10.1080/02699931.2018.1455640 · Cited by 17 · see citing works
Unsupervised learning of facial emotion decoding skills
Huelle, J. O., Sack, B., Broer, K., Komlewa, I., & Anders, S. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00077 · Cited by 14 · see citing works
Drift in children's categories: when experienced distributions conflict with prior learning
Kalish, C. W., Zhu, X., & Rogers, T. T. (2014) · Developmental Science · doi:10.1111/desc.12280 · Cited by 14 · see citing works
Shariff, A., & Tracy, J. L. (2011) · Current Directions in Psychological Science · doi:10.1177/0963721411429126 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- Ahn HJ (2005). Teachers’ discussions of emotion in child care centers. Early Childhood Education Journal, 32(4), 237– 242.
- Casasanto D, & Lupyan G (2011). Ad hoc cognition. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 33, No. 33).
- Fisher DH, Pazzani MJ, & Langley P (2014). Concept Formation: Knowledge and Experience in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann Publishers.
- Pollak LH, & Thoits PA (1989). Processes in emotional socialization. Social Psychology Quarterly, 22– 34.
Cited by
Sorted by citations
Emotional expressions reconsidered: Challenges to inferring emotion from human facial movements
Barrett, L. F., Adolphs, R., Marsella, S., Martinez, A. M., & Pollak, S. D. (2019) · Psychological Science in the Public Interest · doi:10.1177/1529100619832930 · Cited by 1,748 · see citing works
Self-citationA new science of emotion: implications for functional neurological disorder
Jungilligens, J., Paredes-Echeverri, S., Popkirov, S., Barrett, L. F., & Perez, D. L. (2022) · Brain · doi:10.1093/brain/awac204 · Cited by 164 · see citing works
A learning theory of attachment: Unraveling the black box of attachment development
Bosmans, G., Bakermans‐Kranenburg, M. J., Vervliet, B., Verhees, M. W. F. T., & van IJzendoorn, M. H. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.03.014 · Cited by 167 · see citing works
Masking Emotions: Face Masks Impair How We Read Emotions
Gori, M., Schiatti, L., & Amadeo, M. B. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.669432 · Cited by 147 · see citing works
Ruba, A. L., & Pollak, S. D. (2020) · PLoS ONE · doi:10.1371/journal.pone.0243708 · Cited by 136 · see citing works
Self-citationBarrett, L. F. (2022) · American Psychologist · doi:10.1037/amp0001054 · Cited by 100 · see citing works
The Development of Emotion Reasoning in Infancy and Early Childhood
Ruba, A. L., & Pollak, S. D. (2020) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-060320-102556 · Cited by 96 · see citing works
Self-citationDo Preverbal Infants Understand Discrete Facial Expressions of Emotion?
Ruba, A. L., & Repacholi, B. M. (2020) · Emotion Review · doi:10.1177/1754073919871098 · Cited by 78 · see citing works
Historical Migration Patterns Shape Contemporary Cultures of Emotion
Niedenthal, P. M., Rychlowska, M., Zhao, F., & Wood, A. (2019) · Perspectives on Psychological Science · doi:10.1177/1745691619849591 · Cited by 72 · see citing works
Self-citationChildhood unpredictability and the development of exploration
Xu, Y., Harms, M. B., Green, C. S., Wilson, R. C., & Pollak, S. D. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2303869120 · Cited by 48 · see citing works
Self-citationProgress in understanding the emergence of human emotion.
Pollak, S. D., Camras, L. A., & Cole, P. M. (2019) · Developmental Psychology · doi:10.1037/dev0000789 · Cited by 41 · see citing works
Self-citationAcquiring Complex Communicative Systems: Statistical Learning of Language and Emotion
Ruba, A. L., Pollak, S. D., & Saffran, J. R. (2022) · Topics in Cognitive Science · doi:10.1111/tops.12612 · Cited by 43 · see citing works
Self-citationA review of attentional bias modification trainings for depression
Guo, L., Cai, X., Yang, Q., Cui, Q., Huang, L., Jing, X., & Wang, Y. (2022) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14022 · Cited by 29 · see citing works
The COVID‐19 pandemic, mask‐wearing, and emotion recognition during late‐childhood
Chester, M. A., Plate, R. C., Powell, T., Rodriguez, Y., Wagner, N. J., & Waller, R. E. (2022) · Social Development · doi:10.1111/sode.12631 · Cited by 25 · see citing works
Self-citationTowards Understanding Perceptual Differences between Genuine and Face-Swapped Videos
Wöhler, L., Zembaty, M., Castillo, S., & Magnor, M. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445627 · Cited by 24 · see citing works
Abused Children Experience High Anger Exposure
Plate, R. C., Bloomberg, Z., Bolt, D. M., Bechner, A. M. P., Roeber, B. J., & Pollak, S. D. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00440 · Cited by 22 · see citing works
Self-citationPrototype-based category learning in autism: A review
Vanpaemel, W., & Bayer, J. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.05.016 · Cited by 20 · see citing works
The Emergence of Organized Emotion Dynamics in Childhood
Nencheva, M. L., Nook, E. C., Thornton, M. A., Lew‐Williams, C., & Tamir, D. (2024) · Affective Science · doi:10.1007/s42761-024-00248-y · Cited by 14 · see citing works
Categorization of Vocal Emotion Cues Depends on Distributions of Input
Woodard, K. A., Plate, R. C., Morningstar, M. A., Wood, A., & Pollak, S. D. (2021) · Affective Science · doi:10.1007/s42761-021-00038-w · Cited by 15 · see citing works
Self-citationBeyond Language in Infant Emotion Concept Development
Ruba, A. L., & Repacholi, B. M. (2020) · Emotion Review · doi:10.1177/1754073920931574 · Cited by 17 · see citing works
Foster, J. C., Hodges, H. R., Beloborodova, A. V., Cohodes, E. M., Phillips, M. Q., Anderson, E. W., Fagbenro, B., & Gee, D. G. (2024) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2024.101399 · Cited by 13 · see citing works
Statistical Learning in an Emotional World
Plate, R. C., Woodard, K. A., & Pollak, S. D. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198855903.013.12 · Cited by 11 · see citing works
Self-citation“Grumpy” or “furious”? arousal of emotion labels influences judgments of facial expressions
Barker, M. S., Bidstrup, E. M., Robinson, G. A., & Nelson, N. L. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235390 · Cited by 11 · see citing works
Assessing the Power of Words to Facilitate Emotion Category Learning
Hoemann, K., Gendron, M., & Barrett, L. F. (2022) · Affective Science · doi:10.1007/s42761-021-00084-4 · Cited by 10 · see citing works
The Pacified Face: Early Embodiment Processes and the Use of Dummies
Rychlowska, M., & Vanderwert, R. E. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00387 · Cited by 11 · see citing works
Children track probabilistic distributions of facial cues across individuals
Woodard, K., Plate, R. C., & Pollak, S. D. (2022) · Journal of Experimental Psychology: General · doi:10.1037/xge0001087 · Cited by 9 · see citing works
Self-citationTraining reduces error in rating the intensity of emotions.
Leitzke, B. T., Plate, R. C., & Pollak, S. D. (2020) · Emotion · doi:10.1037/emo0000763 · Cited by 8 · see citing works
Self-citationPeer acceptance and rejection in childhood and adolescence
Davis, A. A., & Allen, J. P. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-818872-9.00041-8 · Cited by 8 · see citing works
Maternal care predicts facial expression processing in macaques
O’Callaghan, O., Whitehouse, J., Paukner, A., Witham, C. L., & Waller, B. M. (2025) · iScience · doi:10.1016/j.isci.2025.112179 · Cited by 6 · see citing works
Category Flexibility in Emotion Learning
Plate, R. C., Woodard, K. A., & Pollak, S. D. (2023) · Affective Science · doi:10.1007/s42761-023-00192-3 · Cited by 6 · see citing works
Self-citationZhang, W. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.950426 · Cited by 5 · see citing works
Huang, S., Pollak, S. D., & Xie, W. (2025) · Nature Communications · doi:10.1038/s41467-025-62210-1 · Cited by 4 · see citing works
Self-citationCalculated Feelings: How Children Use Probability to Infer Emotions
Doan, T., Friedman, O., & Denison, S. (2023) · Open Mind · doi:10.1162/opmi_a_00111 · Cited by 4 · see citing works
Lesson learned from the COVID-19 pandemic: toddlers learn earlier to read emotions with face masks
Gori, M., Schiatti, L., Faggioni, M., & Amadeo, M. B. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1386937 · Cited by 4 · see citing works
Infants track patterns of emotion transitions in the home.
Nencheva, M. L., Peng, R., Tamir, D., & Lew‐Williams, C. (2025) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0001495 · Cited by 3 · see citing works
Ziva, A., & Ziori, E. (2024) · Quarterly Journal of Experimental Psychology · doi:10.1177/17470218241281639 · Cited by 2 · see citing works
Emotion understanding in infants and young children: How input shapes emotional development
LoBue, V., Casasola, M., & Oakes, L. M. (2025) · Advances in child development and behavior · doi:10.1016/bs.acdb.2025.07.003 · Cited by 2 · see citing works
Emotional consistency guides social engagement in 18- to 24-month-old toddlers.
Fang, W., & Xiao, N.-Q. G. (2026) · Child Development · doi:10.1093/chidev/aacaf031 · Cited by 2 · see citing works
Statistical learning across cognitive and affective domains: a multidimensional review
Wang, Y., Lu, L., & Wu, M. (2025) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2025.1460471 · Cited by 5 · see citing works
Ong, J. H., & Liu, F. (2022) · Quarterly Journal of Experimental Psychology · doi:10.1177/17470218221135585 · Cited by 2 · see citing works
Why Internal Representations and Their Temporal Dependence Matter for Emotion Inference
Goel, S., & Gendron, M. (2025) · Emotion Review · doi:10.1177/17540739251379801 · Cited by 1 · see citing works
Kain, W. (2020) · Springer eBooks · doi:10.1007/978-3-662-59288-5_21 · Cited by 1 · see citing works
Factors Facilitating Emotion Understanding in Infancy: Commentary on Ogren and Johnson
Walle, E. A. (2020) · Human Development · doi:10.1159/000512411
Intergenerational Relations That Guide Educational Planning
Crawford, C. M., Bromer, B. L., Moffett, N. L., Andrews, S. K., Dickenson, V., Newsum, J. M., Wallace, J. K. Y., & Dillard, J. L. (2023) · Advances in early childhood and K-12 education · doi:10.4018/978-1-6684-8888-1.ch002
Cross-Modal Probabilistic Representation Learning for Conversational Emotion Recognition
Zhou, Z., Feng, X., Wang, W., & Chen, J. (2026) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2026.3711930
- Authors
- Plate, R. C., Wood, A., Woodard, K., & Pollak, S. D.
- Venue
- Journal of Experimental Psychology: General
- Published
- 2019-10
- Volume
- 148
- Issue
- 10
- Pages
- 1814-1827
- ISSN
- 0096-3445 (ISSN-L)
- 1939-2222
- PMC
- PMC6586538
- OpenAlex
- W2905769577
- Cited by
- 45
- References
- 35
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 4 · 2023: 4 · 2022: 9 · 2021: 6 · 2020: 9 · 2019: 5
- FWCI
- 2.95
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Experimental Psychology General (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- National Institute of Mental Health (R01MH61285, T32MH018931-24)
- National Institute of Child Health and Human Development (U54 HD090256)
- National Science Foundation (DGE-1256259)
- Sponsor name not included
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Evolutionary Psychology and Human Behavior
- Keywords
- emotion classification, categorical perception, facial expressions, anger, statistical learning, category boundaries, trait judgments, children and adults, supervised learning, probabilistic learning
- MeSH terms
- Adolescent, Child, Cues, Emotions, Facial Expression, Facial Muscles, Female, Humans, Judgment, Learning, Male, Social Environment, Social Perception, Speech, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
