The role of visual features in object processing for perception and action

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We live in an ever-changing world that is rich with objects and events. It is too complex to analyze it completely. So, how can we properly interact with it? I will investigate three fundamental strategies that the brain can use to cope with complexity. First, it can use prior knowledge to guide its attention and to select pieces of information that need to be processed first while ignoring others. Second, it can use optimal ways to integrate information in the best possible way. Third, it can use sparse coding, that is, it can convert the complexity of its sensory information about the world into simpler, categorical descriptions. I will explore the role of these strategies for two types of functions, when perceiving objects and when controlling manual actions towards them. Specifically, I will ask: (1) What are the neural correlates of prior knowledge and attention for object perception? (2) Can differences between perception and grasp actions be explained by differences in optimization? (3) Do processes of perception and action differ with regards to sparse coding as often observed in higher cognitive functions such as category learning? I expect that results from this research will further an understanding of mechanisms of object perception, of the functional architecture of visual processes, and the contributions of sensorimotor processes to human thought.