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Human visual motion perception shows hallmarks of Bayesian structural inference

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Yang,  S
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Computational Principles of Intelligence, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Yang, S., Bill, J., Drugowitsch, J., & Gershman, S. (submitted). Human visual motion perception shows hallmarks of Bayesian structural inference.


Cite as: http://hdl.handle.net/21.11116/0000-0007-6210-8
Abstract
Motion relations in visual scenes carry an abundance of behaviorally relevant information, but little is known about the computations underlying the identification of visual motion structure by humans. We addressed this gap in two psychophysics experiments and found that participants identified hierarchically organized motion relations in close correspondence with Bayesian structural inference. We demonstrate that, for our tasks, a choice model based on the Bayesian ideal observer can accurately match many facets of human structural inference, including task performance, perceptual error patterns, single-trial responses, participant-specific differences, and subjective decision confidence, particularly when motion scenes are ambiguous. Our work can guide future neuroscience experiments to reveal the neural mechanisms underlying higher-level visual motion perception.