Implicit and explicit learning of Bayesian priors differently impacts bias during perceptual decision-making

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作者
V. N. Thakur
M. A. Basso
J. Ditterich
B. J. Knowlton
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[1] University of California – Los Angeles,Department of Psychology
[2] University of California – Los Angeles,Fuster Laboratory of Cognitive Neuroscience, Departments of Neurobiology and Psychiatry and Biobehavioral Science, Jane and Terry Semel Institute for Neuroscience and Human Behavior
[3] University of California – Davis,Center for Neuroscience and Department of Neurobiology, Physiology, & Behavior
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Knowledge without awareness, or implicit knowledge, influences a variety of behaviors. It is unknown however, whether implicit knowledge of statistical structure informs visual perceptual decisions or whether explicit knowledge of statistical probabilities is required. Here, we measured visual decision-making performance using a novel task in which humans reported the orientation of two differently colored translational Glass patterns; each color associated with different orientation probabilities. The task design allowed us to assess participants’ ability to learn and use a general orientation prior as well as a color specific feature prior. Classifying decision-makers based on a questionnaire revealed that both implicit and explicit learners implemented a general orientation bias by adjusting the starting point of evidence accumulation in the drift diffusion model framework. Explicit learners additionally adjusted the drift rate offset. When subjects implemented a stimulus specific bias, they did so by adjusting primarily the drift rate offset. We conclude that humans can learn priors implicitly for perceptual decision-making and depending on awareness implement the priors using different mechanisms.
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