Cognitive process of facial recognition
Several domains in cognitive neuroscience have embraced this idea, including studies in perception, motor control, language, and affective, social, and clinical neuroscience. Despite the various studies that have used face stimuli to address questions related to predictive processing, there has been surprisingly little connection between this work and established cognitive models of face recognition. Here we suggest that the predictive framework can serve as an important complement of established cognitive face models. Conversely, the link to cognitive face models has the potential to shed light on issues that remain open in predictive frameworks. In very early neuroscience textbooks, vision seemed to be a hierarchical process that started at the lowest processing levels in the brain and propagated into higher areas that progressively computed more details and complexity. Srinivasan, Laughlin, and Dubs were the first to suggest a computational model based on a predictive-coding mechanism, to explain the center—surround antagonisms that interneurons of the retina exhibit.
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Integrating predictive frameworks and cognitive models of face perception
Face perception - Wikipedia
Cognitive Research: Principles and Implications volume 3 , Article number: 21 Cite this article. Metrics details. These measures were integrated into two separate studies examining the relationship between face processing and other tasks. In Study 2 we used additional measures of perceptual and cognitive abilities, and personality factors to place individual differences in a broader context. Performance was significantly correlated across the three face-identity tasks in both studies, suggesting some degree of commonality of underlying mechanisms. In Study 2 there were few associations between face tasks and other measures, with task-level influences seeming to account for the small number of associations present. In general, face tasks correlated with each other, but did not show an overall relation with other perceptual, cognitive or personality tests.
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The use of computational models for understanding human face perception and recognition has a long and intriguing history that runs parallel to efforts in the engineering literature to develop algorithms for computer-based face recognition systems. This article considers the insights gained from combining computational and cognitive approaches to the study of human face recognition and discusses the ways in which computational models have informed studies of human face processing and vice versa. Finally, it discusses recent progress in state-of-the-art computational models of face recognition, which offers a new perspective on the cognitive-computational dialog. Keywords: computational models , face perception , cognitive approaches , face space , adaptation. Alice J.
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