The visual system must constantly generate meaning by combining noisy sensory information with efficient internal representations. However, as essential as these hidden representations are in shaping many aspects of cognition and behavior, they can be difficult to measure directly. In my work, I apply adaptive sampling techniques based on serial reproduction (in which the response of one participant becomes the stimulus for the next) to reveal shared visual memory representations in unprecedented detail. In this talk, I will present past and ongoing work examining the structure of visual memory priors using this experimental paradigm. I will then discuss how they have enabled new theoretical breakthroughs in our understanding of spatial memory. Finally, I will showcase new work revealing 3D memory priors, and comparing detailed human visual selectivity estimates to neural network attention.
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