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Making sense of the world: Infant learning from a predictive processing perspective

MPS-Authors

Köster,  Moritz
Max Planck Research Group Early Social Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Education and Psychology, FU Berlin, Germany;
Department of Psychology, Graduate School of Letters, Kyoto University, Japan;

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Kayhan,  Ezgi
Max Planck Research Group Early Social Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Psychology, University of Potsdam, Germany;

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Langeloh,  Miriam
Max Planck Research Group Early Social Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Psychology, University of Heidelberg, Germany;

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Citation

Köster, M., Kayhan, E., Langeloh, M., & Hoehl, S. (2020). Making sense of the world: Infant learning from a predictive processing perspective. Perspectives on Psychological Science, 15(3), 562-571. doi:10.1177/1745691619895071.


Cite as: https://hdl.handle.net/21.11116/0000-0006-507C-5
Abstract
For human infants, the first years after birth are a period of intense exploration—getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one’s own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants’ motor and proprioceptive learning, and infants’ basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants’ early learning processes in theory, research, and application.