101. Object representations are biased toward each other through statistical learning
- Author
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Jiaying Zhao and Ru Qi Yu
- Subjects
Statistical learning ,business.industry ,Cognitive Neuroscience ,05 social sciences ,Experimental and Cognitive Psychology ,Pattern recognition ,Cognition ,Space (commercial competition) ,Object (computer science) ,050105 experimental psychology ,Random order ,03 medical and health sciences ,0302 clinical medicine ,Arts and Humanities (miscellaneous) ,Visual memory ,Orientation (geometry) ,0501 psychology and cognitive sciences ,Artificial intelligence ,Implicit bias ,Psychology ,business ,030217 neurology & neurosurgery - Abstract
The visual system is remarkably efficient at extracting regularities from the environment through statistical learning. While such extraction has extensive consequences on cognition, it is unclear how statistical learning shapes the representations of the individual objects that comprise the regularities. Here we examine how statistical learning alters object representations. In three experiments, participants were exposed to either random arrays containing objects in a random order, or structured arrays containing object pairs where two objects appeared next to each other in fixed spatial or temporal configurations. After exposure, one object in each pair was briefly presented and participants judged the location or the orientation of the object without seeing the other object in the pair. We found that when an object reliably appeared next to another object in space, it was judged as being closer to the other object in space even though the other object was never presented (Experiments 1 and 2)....
- Published
- 2018
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