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Making sense of the world
(2020)
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.
Due to their ability to capture attention, emotional stimuli tend to benefit from enhanced perceptual processing, which can be helpful when such stimuli are task-relevant but hindering when they are task-irrelevant. Altered emotion-attention interactions have been associated with symptoms of affective disturbances, and emerging research focuses on improving emotion-attention interactions to prevent or treat affective disorders. In line with the Human Affectome Project's emphasis on linguistic components, we also analyzed the language used to describe attention-related aspects of emotion, and highlighted terms related to domains such as conscious awareness, motivational effects of attention, social attention, and emotion regulation. These terms were discussed within a broader review of available evidence regarding the neural correlates of (1) Emotion-Attention Interactions in Perception, (2) Emotion-Attention Interactions in Learning and Memory, (3) Individual Differences in Emotion-Attention Interactions, and (4) Training and Interventions to Optimize Emotion-Attention Interactions. This comprehensive approach enabled an integrative overview of the current knowledge regarding the mechanisms of emotion-attention interactions at multiple levels of analysis, and identification of emerging directions for future investigations.