Fast ensemble representations for abstract visual impressions

Allison Yamanashi Leib (), Anna Kosovicheva and David Whitney
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Allison Yamanashi Leib: University of California Berkeley, Whitney Lab, 3210 Tolman Hall, Berkeley, California 94720, USA
Anna Kosovicheva: Northeastern University, 360 Huntington Ave
David Whitney: University of California Berkeley, Whitney Lab, 3210 Tolman Hall, Berkeley, California 94720, USA

Nature Communications, 2016, vol. 7, issue 1, 1-10

Abstract: Abstract Much of the richness of perception is conveyed by implicit, rather than image or feature-level, information. The perception of animacy or lifelikeness of objects, for example, cannot be predicted from image level properties alone. Instead, perceiving lifelikeness seems to be an inferential process and one might expect it to be cognitively demanding and serial rather than fast and automatic. If perceptual mechanisms exist to represent lifelikeness, then observers should be able to perceive this information quickly and reliably, and should be able to perceive the lifelikeness of crowds of objects. Here, we report that observers are highly sensitive to the lifelikeness of random objects and even groups of objects. Observers’ percepts of crowd lifelikeness are well predicted by independent observers’ lifelikeness judgements of the individual objects comprising that crowd. We demonstrate that visual impressions of abstract dimensions can be achieved with summary statistical representations, which underlie our rich perceptual experience.

Date: 2016
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DOI: 10.1038/ncomms13186

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