Abstract
Learners flexibly update category boundaries to adjust to the range of experiences they encounter. However, little is known about whether the degree of flexibility is consistent across domains. We examined whether categorization of social input, specifically emotions, is afforded more flexibility as compared to other biological input. To address this question, children (6–12 years; 32 female, 37 male; 7 Hispanic or Latino, 62 not Hispanic or Latino; 8 Black or African American, 14 multiracial, 46 White, 1 selected “other”) categorized faces morphed from calm to upset and animals morphed from a horse to a cow across task phases that differed in the distribution of stimuli presented. Learners flexibly adjusted both emotion and animal category boundaries according to distributional information, yet children showed more flexibility when updating their category boundaries for emotions. These results provide support for the idea that children—who must adjust to the vast and varied emotional signals of their social partners—respond to social signals dynamically in order to make predictions about the internal states and future behaviors of others.
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References
Ahn, H. J. (2005). Teachers? Discussions of emotion in child care centers. Early Childhood Education Journal, 32(4), 237–242. https://doi.org/10.1007/s10643-004-1424-6
Aviezer, H., Hassin, R. R., Ryan, J., Grady, C., Susskind, J., Anderson, A., Moscovitch, M., & Bentin, S. (2008). Angry, disgusted, or afraid? Studies on the malleability of emotion perception. Psychological Science, 19(7), 724–732. https://doi.org/10.1111/j.1467-9280.2008.02148.x
Aviezer, H., Ensenberg, N., & Hassin, R. R. (2017). The inherently contextualized nature of facial emotion perception. Current Opinion in Psychology, 17, 47–54. https://doi.org/10.1016/j.copsyc.2017.06.006
Barrett, L. F., Adolphs, R., Marsella, S., Martinez, A. M., & Pollak, S. D. (2019). Emotional expressions reconsidered: Challenges to inferring emotion from human facial movements. Psychological Science in the Public Interest, 20(1), 1–68. https://doi.org/10.1177/1529100619832930
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), https://doi.org/10.18637/jss.v067.i01
Berkay, D., & Jenkins, A. C. (2023). A role for uncertainty in the neural distinction between social and nonsocial thought. Perspectives on Psychological Science, 18(2), 491–502. https://doi.org/10.1177/17456916221112077
Brauer, M., & Curtin, J. J. (2018). Linear mixed-effects models and the analysis of nonindependent data: A unified framework to analyze categorical and continuous independent variables that vary within-subjects and/or within-items. Psychological Methods, 23(3), 389–411. https://doi.org/10.1037/met0000159
Carmichael, C. A., & Hayes, B. K. (2001). Prior knowledge and exemplar encoding in children’s concept acquisition. Child Development, 72(4), 1071–1090. https://doi.org/10.1111/1467-8624.00335
Cordaro, D. T., Sun, R., Keltner, D., Kamble, S., Huddar, N., & McNeil, G. (2018). Universals and cultural variations in 22 emotional expressions across five cultures. Emotion, 18(1), 75–93. https://doi.org/10.1037/emo0000302
Cristia, A., Seidl, A., Vaughn, C., Schmale, R., Bradlow, A., & Floccia, C. (2012). Linguistic processing of accented speech across the lifespan. Frontiers in Psychology, 3, 479. https://doi.org/10.3389/fpsyg.2012.00479
Emmons, N. A., & Kelemen, D. A. (2015). Young children’s acceptance of within-species variation: Implications for essentialism and teaching evolution. Journal of Experimental Child Psychology, 139, 148–160. https://doi.org/10.1016/j.jecp.2015.05.011
Etcoff, N. L., & Magee, J. J. (1992). Categorical perception of facial expressions. Cognition, 44(3), 227–240. https://doi.org/10.1016/0010-0277(92)90002-Y
Foster-Hanson, E., & Rhodes, M. (2019). Is the most representative skunk the average or the stinkiest? Developmental changes in representations of biological categories. Cognitive Psychology, 110, 1–15. https://doi.org/10.1016/j.cogpsych.2018.12.004
Friedman, H. S., Prince, L. M., Riggio, R. E., & DiMatteo, M. R. (1980). Understanding and assessing nonverbal expressiveness: The Affective Communication Test. Journal of Personality and Social Psychology, 39(2), 333–351. https://doi.org/10.1037/0022-3514.39.2.333
Frost, R., Armstrong, B. C., Siegelman, N., & Christiansen, M. H. (2015). Domain generality versus modality specificity: The paradox of statistical learning. Trends in Cognitive Sciences, 19(3), 117–125. https://doi.org/10.1016/j.tics.2014.12.010
Frost, R., Armstrong, B. C., & Christiansen, M. H. (2019). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145(12), 1128–1153. https://doi.org/10.1037/bul0000210
Gao, X., & Maurer, D. (2009). Influence of intensity on children’s sensitivity to happy, sad, and fearful facial expressions. Journal of Experimental Child Psychology, 102(4), 503–521. https://doi.org/10.1016/j.jecp.2008.11.002
Gopnik, A., O’Grady, S., Lucas, C. G., Griffiths, T. L., Wente, A., Bridgers, S., Aboody, R., Fung, H., & Dahl, R. E. (2017). Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood. Proceedings of the National Academy of Sciences, 114(30), 7892–7899. https://doi.org/10.1073/pnas.1700811114
Hammer, R., Diesendruck, G., Weinshall, D., & Hochstein, S. (2009). The development of category learning strategies: What makes the difference? Cognition, 112(1), 105–119. https://doi.org/10.1016/j.cognition.2009.03.012
Hayes, B. K. (2006). Knowledge, development, and category learning. In Psychology of learning and motivation (Vol. 46, pp. 37–77). Academic Press. https://doi.org/10.1016/S0079-7421(06)46002-3
Hoemann, K., Wu, R., LoBue, V., Oakes, L. M., Xu, F., & Barrett, L. F. (2020). Developing an understanding of emotion categories: Lessons from objects. Trends in Cognitive Sciences, 24(1), 39–51. https://doi.org/10.1016/j.tics.2019.10.010
Hoemann, K., Gendron, M., & Barrett, L. F. (2022). Assessing the power of words to facilitate emotion category learning. Affective Science, 3(1), 69–80. https://doi.org/10.1007/s42761-021-00084-4
Huang-Pollock, C. L., Maddox, W. T., & Karalunas, S. L. (2011). Development of implicit and explicit category learning. Journal of Experimental Child Psychology, 109(3), 321–335. https://doi.org/10.1016/j.jecp.2011.02.002
Kalish, C. W., Zhu, X., & Rogers, T. T. (2015). Drift in children’s categories: When experienced distributions conflict with prior learning. Developmental Science, 18(6), 940–956. https://doi.org/10.1111/desc.12280
Kring, A. M., & Gordon, A. H. (1998). Sex differences in emotion: expression, experience, and physiology. Journal of Personality and Social Psychology, 74(3), 686–703. https://doi.org/10.1037/0022-3514.74.3.686
Leitzke, B. T., & Pollak, S. D. (2016). Developmental changes in the primacy of facial cues for emotion recognition. Developmental Psychology, 52(4), 572–581. https://doi.org/10.1037/a0040067
Levari, D. E., Gilbert, D. T., Wilson, T. D., Sievers, B., Amodio, D. M., & Wheatley, T. (2018). Prevalence-induced concept change in human judgment. Science, 360(6396), 1465–1467. https://doi.org/10.1126/science.aap8731
Lucas, C. G., Bridgers, S., Griffiths, T. L., & Gopnik, A. (2014). When children are better (or at least more open-minded) learners than adults: Developmental differences in learning the forms of causal relationships. Cognition, 131(2), 284–299. https://doi.org/10.1016/j.cognition.2013.12.010
Montag, J. L. (2021). Limited evidence for probability matching as a strategy in probability learning tasks. In Psychology of learning and motivation (p. S0079742121000050). Elsevier. https://doi.org/10.1016/bs.plm.2021.02.005
Niedenthal, P. M., Rychlowska, M., & Wood, A. (2017). Feelings and contexts: Socioecological influences on the nonverbal expression of emotion. Current Opinion in Psychology, 17, 170–175. https://doi.org/10.1016/j.copsyc.2017.07.025
Nook, E. C., Sasse, S. F., Lambert, H. K., McLaughlin, K. A., & Somerville, L. H. (2018). The nonlinear development of emotion differentiation: Granular emotional experience is low in adolescence. Psychological Science, 29(8), 1346–1357. https://doi.org/10.1177/0956797618773357
Nook, E. C., Stavish, C. M., Sasse, S. F., Lambert, H. K., Mair, P., McLaughlin, K. A., & Somerville, L. H. (2020). Charting the development of emotion comprehension and abstraction from childhood to adulthood using observer-rated and linguistic measures. Emotion, 20(5), 773–792. https://doi.org/10.1037/emo0000609
Peirce, J., Gray, J. R., Simpson, S., MacAskill, M., Höchenberger, R., Sogo, H., ... & Lindeløv, J. K. (2019). PsychoPy2: Experiments in behavior made easy. Behavior Research Methods, 51, 195–203. https://doi.org/10.3758/s13428-018-01193-y
Plate, R. C., Fulvio, J. M., Shutts, K., Green, C. S., & Pollak, S. D. (2018). Probability learning: Changes in behavior across time and development. Child Development, 89(1), 205–218. https://doi.org/10.1111/cdev.12718
Plate, R. C., Wood, A., Woodard, K., & Pollak, S. D. (2018). Probabilistic learning of emotion categories. Journal of Experimental Psychology: General, 148(10), 1814-1827. https://doi.org/10.1037/xge0000529
Plate, R. C., Bloomberg, Z., Bolt, D. M., Bechner, A. M., Roeber, B. J., & Pollak, S. D. (2019). Abused children experience high anger exposure. Frontiers in Psychology, 10, 440. https://doi.org/10.3389/fpsyg.2019.00440
Plate, R. C., Woodard, K., & Pollak, S. D. (2022). Statistical learning in an emotional world. In D. Dukes, A. D. Samson, & E. A. Walle (Eds.), The Oxford handbook of emotional development (pp. 78–92).
Pollak, S. D., & Kistler, D. J. (2002). Early experience is associated with the development of categorical representations for facial expressions of emotion. Proceedings of the National Academy of Sciences, 99(13), 9072–9076.
Pollak, L. H., & Thoits, P. A. (1989). Processes in emotional socialization. Social Psychology Quarterly, 52(1), 22. https://doi.org/10.2307/2786901
R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/
Ruba, A., & Pollak, S. (2020). The development of emotion reasoning in infancy and early childhood. Annual Review of Developmental Psychology, 2, 503–531. https://doi.org/10.1146/annurev-devpsych-060320-102556
Ruba, A. L., Pollak, S., & Saffran, J. (2022). Acquiring complex communicative systems: Statistical learning of language and emotion. Topics in Cognitive Science, 14(3), 432–450.
Schmale, R., Cristia, A., & Seidl, A. (2012). Toddlers recognize words in an unfamiliar accent after brief exposure: Brief exposure to an unfamiliar accent. Developmental Science, 15(6), 732–738. https://doi.org/10.1111/j.1467-7687.2012.01175.x
Siegelman, N., Bogaerts, L., Elazar, A., Arciuli, J., & Frost, R. (2018). Linguistic entrenchment: Prior knowledge impacts statistical learning performance. Cognition, 177, 198–213. https://doi.org/10.1016/j.cognition.2018.04.011
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). The NimStim set of facial expressions: Judgments from untrained research participants. Psychiatry Research, 168(3), 242–249. https://doi.org/10.1016/j.psychres.2008.05.006
Tottenham, N., Phuong, J., Flannery, J., Gabard-Durnam, L., & Goff, B. (2012). A negativity bias for ambiguous facial-expression valence during childhood: Converging evidence from behavior and facial corrugator muscle responses. Emotion, 13(1), 92. https://doi.org/10.1037/a0029431
Weatherholtz, K., & Jaeger, T. F. (2016). Speech Perception and generalization across talkers and accents (Vol. 1). Oxford University Press. https://doi.org/10.1093/acrefore/9780199384655.013.95
Wickham, H. (2016). Ggplot2. Springer International Publishing. https://doi.org/10.1007/978-3-319-24277-4
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T., Miller, E., Bache, S., Müller, K., Ooms, J., Robinson, D., Seidel, D., Spinu, V., et al. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686. 10.21105/joss.01686.
Widen, S. C. (2013). Children’s interpretation of facial expressions: The long path from valence-based to specific discrete categories. Emotion Review, 5(1), 72–77.
Widen, S. C., & Russell, J. A. (2008). Children acquire emotion categories gradually. Cognitive Development, 23(2), 291–312. https://doi.org/10.1016/j.cogdev.2008.01.002
Wood, A., Lupyan, G., Sherrin, S., & Niedenthal, P. (2016). Altering sensorimotor feedback disrupts visual discrimination of facial expressions. Psychonomic Bulletin & Review, 23(4), 1150–1156. https://doi.org/10.3758/s13423-015-0974-5
Woodard, K., Plate, R. C., Morningstar, M., Wood, A., & Pollak, S. D. (2021). Categorization of vocal emotion cues depends on distributions of input. Affective Science, 2(3), 301–310. https://doi.org/10.1007/s42761-021-00038-w
Woodard, K., Plate, R. C., & Pollak, S. D. (2022). Children track probabilistic distributions of facial cues across individuals. Journal of Experimental Psychology: General, 151(2), 506–511. https://doi.org/10.1037/xge0001087
Wu, Y., Muentener, P., & Schulz, L. E. (2017). One- to four-year-olds connect diverse positive emotional vocalizations to their probable causes. Proceedings of the National Academy of Sciences, 114(45), 11896–11901. https://doi.org/10.1073/pnas.1707715114
Wu, Y., Schulz, L., Frank, M. C., & Gweon, H. (2020). Emotion as information in early social learning. PsyArXiv. https://doi.org/10.31234/osf.io/fz857
Acknowledgements
We thank the families who participated in this study and the research assistants who helped conduct the research, particularly Cassandra Windau, Carolyn Meissner, and Emily Weiss. Images were reproduced with permission from Tottenham et al. (2009) and Wood et al. (2016). The experiment was approved by the Institutional Review Board.
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This research was supported by the National Institute of Mental Health through grant R01MH61285 to S.D.P. and in part by a core grant to the Waisman Center from the National Institute of Child Health and Human Development (P50HD105353). R.C.P. was supported by a National Science Foundation Graduate Research Fellowship (DGE-1256259) and the Richard L. and Jeanette A. Hoffman Wisconsin Distinguished Graduate Fellowship.
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The authors declare competing interest.
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The experimental paradigm, de-identified data, and analysis scripts are available on Open Science Framework: https://osf.io/zckxq/.
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S.D.P. acquired funding for the research. R.C.P. and K.W. conducted data curation and formal analysis. R.C.P. prepared the original draft of the manuscript. All authors were involved with conceptualization, methodology, and reviewing and editing.
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Plate, R.C., Woodard, K. & Pollak, S.D. Category Flexibility in Emotion Learning. Affec Sci 4, 722–730 (2023). https://doi.org/10.1007/s42761-023-00192-3
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DOI: https://doi.org/10.1007/s42761-023-00192-3