Abstract:
:Most current models assume that the perceptual and cognitive processes of visual word recognition and reading operate upon neuronally coded domain-general low-level visual representations - typically oriented line representations. We here demonstrate, consistent with neurophysiological theories of Bayesian-like predictive neural computations, that prior visual knowledge of words may be utilized to 'explain away' redundant and highly expected parts of the visual percept. Subsequent processing stages, accordingly, operate upon an optimized representation of the visual input, the orthographic prediction error, highlighting only the visual information relevant for word identification. We show that this optimized representation is related to orthographic word characteristics, accounts for word recognition behavior, and is processed early in the visual processing stream, i.e., in V4 and before 200 ms after word-onset. Based on these findings, we propose that prior visual-orthographic knowledge is used to optimize the representation of visually presented words, which in turn allows for highly efficient reading processes.
journal_name
Neuroimagejournal_title
NeuroImageauthors
Gagl B,Sassenhagen J,Haan S,Gregorova K,Richlan F,Fiebach CJdoi
10.1016/j.neuroimage.2020.116727subject
Has Abstractpub_date
2020-07-01 00:00:00pages
116727eissn
1053-8119issn
1095-9572pii
S1053-8119(20)30214-7journal_volume
214pub_type
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