The role of allograph representations in font-invariant letter identification.

David Rothlein, Brenda Rapp
Author Information
  1. David Rothlein: Department of Veterans Affairs.
  2. Brenda Rapp: Department of Cognitive Science, Johns Hopkins University.

Abstract

The literate brain must contend with countless font variants for any given letter. How does the visual system handle such variability? One proposed solution posits stored structural descriptions of basic letter shapes that are abstract enough to deal with the many possible font variations of each letter. These font-invariant representations, referred to as allographs in this paper, while frequently posited, have seldom been empirically evaluated. The research reported here helps to address this gap with 2 experiments that examine the possible influence of allograph representations on visual letter processing. In these experiments, participants respond to pairs of letters presented in an atypical font in 2 tasks-visual similarity judgments (Experiment 1) and same/different decisions (Experiment 2). By using representational similarity analysis (RSA) in conjunction with linear mixed effect models (LMEM; RSA-LMEM) we show that the similarity structure of the responses to the atypical font is influenced by the predicted similarity structure of allograph representations even after accounting for font-specific visual shape similarity. Similarity due to symbolic (abstract) identity, name, and motor representations of letters are also taken into account providing compelling evidence for the unique influence of allograph representations in these tasks. These results provide support for the role of allograph representations in achieving font-invariant letter identification. (PsycINFO Database Record

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Grants

  1. P50 DC012283/NIDCD NIH HHS
  2. R01 DC006740/NIDCD NIH HHS

MeSH Term

Adult
Humans
Pattern Recognition, Visual
Psycholinguistics
Reading

Word Cloud

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