September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Through the looking-glass: Visual sensitivity to chirality
Author Affiliations
  • Tal Boger
    Yale University
    Johns Hopkins University
  • Ziv Epstein
    MIT Media Lab
  • Matthew Groh
    MIT Media Lab
  • Chaz Firestone
    Johns Hopkins University
Journal of Vision September 2021, Vol.21, 2456. doi:https://doi.org/10.1167/jov.21.9.2456
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      Tal Boger, Ziv Epstein, Matthew Groh, Chaz Firestone; Through the looking-glass: Visual sensitivity to chirality. Journal of Vision 2021;21(9):2456. doi: https://doi.org/10.1167/jov.21.9.2456.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

If you woke up in Wonderland, could you tell? Wonderland, of course, is the mirror-reversed world discovered by Alice in Lewis Carroll's 1871 novel, "Through the Looking-Glass" — and so our question here is whether naive observers are sensitive to patterns that distinguish images from their mirror-reversals. Many patterns in the natural world are "chiral", such that their mirror images are not superimposable. In a series of large online studies (collecting nearly 100,000 judgments), participants were shown a flipped version and an original version of a natural image, and simply had to guess which was which with no other information. (No legible writing was present in the images.) Results revealed a striking sensitivity to chirality; participants were able to identify which image was flipped and which was normal at rates significantly above-chance, even without any obviously distinguishing features. In Experiment 1, we showed participants images from a large database of social media photos. We observed above-chance performance not only in average accuracy across participants, but also on the image-level: Over 80% of the 500 different images had above-chance performance. Experiment 2 revealed that this chiral sensitivity pervaded the space of natural images and was not specific to any one image class: When we showed participants images from published databases of objects, natural scenes, artificial scenes, and faces, we again observed above-chance performance. Taken together, our results show that humans can not only identify visual chirality but also generalize it across different types of images. Chirality plays a role in a wide variety of natural processes, including the growth of seashells, the organization of chemical structures, and even the handedness of bimanual species. Our work here suggests that chirality arises not only in the world around us but also in human visual processing.

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