Journal
TRENDS IN COGNITIVE SCIENCES
Volume 22, Issue 9, Pages 764-779Publisher
ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tics.2018.06.002
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Funding
- Netherlands Organisation for Scientific Research (NWO Vidi grant)
- Netherlands Organisation for Scientific Research (NWO Research Talent grant)
- Netherlands Organisation for Scientific Research (NWO Rubicon grant)
- James S. McDonell Foundation (JSMF scholar award)
- EU Horizon 2020 Program (European Research Council starting grant) [678286]
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Perception and perceptual decision-making are strongly facilitated by prior knowledge about the probabilistic structure of the world. While the computational benefits of using prior expectation in perception are clear, there are myriad ways in which this computation can be realized. We review here recent advances in our understanding of the neural sources and targets of expectations in perception. Furthermore, we discuss Bayesian theories of perception that prescribe how an agent should integrate prior knowledge and sensory information, and investigate how current and future empirical data can inform and constrain computational frameworks that implement such probabilistic integration in perception.
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