Making Sense of the World: Infant Learning From a Predictive Processing Perspective

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  • Moritz Köster
    Max Planck Institute for Human Cognitive and Brain Sciences
  • Ezgi Kayhan
    Max Planck Institute for Human Cognitive and Brain Sciences
  • Miriam Langeloh
    Max Planck Institute for Human Cognitive and Brain Sciences
  • Stefanie Hoehl
    Department of Developmental and Educational Psychology, Faculty of Psychology, University of Vienna

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<jats:p> 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. </jats:p>

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