September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
How do we recognize letters as visual objects?
Author Affiliations
  • Teresa Schubert
    Harvard University
    Speaker:
  • David Rothlein
    VA Boston Healthcare System
  • Brenda Rapp
    Johns Hopkins University
Journal of Vision September 2019, Vol.19, 4a. doi:https://doi.org/10.1167/19.10.4a
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      Teresa Schubert, David Rothlein, Brenda Rapp; How do we recognize letters as visual objects?. Journal of Vision 2019;19(10):4a. doi: https://doi.org/10.1167/19.10.4a.

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

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Abstract

How do we recognize b and B as instances of the same letter? The cognitive mechanisms of letter recognition permit abstraction across highly different visual exemplars of the same letter (b and B), while also differentiating between highly similar exemplars of different letters (c and e). In this talk, I will present a hierarchical framework for letter recognition which involves progressively smaller reliance on sensory stimulus details to achieve abstract letter representation. In addition to abstraction across visual features, letter recognition in this framework also involves different levels of abstraction in spatial reference frames. This theory was developed based on data from individuals with acquired letter identification deficits (subsequent to brain lesion) and further supported by behavioral and neural research with unimpaired adult readers. I will relate this letter recognition theory to the seminal Marr & Nishihara (1978) framework for object recognition, arguing that letter recognition and visual object recognition require a number of comparable computations, leading to broadly similar recognition systems. Finally, I will compare and contrast neural evidence of cross-modal (visual and auditory letter name) representations for letters and objects. Overall, this talk will provide a theoretical and empirical framework within which to consider letter recognition as a form of object recognition.

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