Joseph W. Houpt, Bethany L. Sussman, James T. Townsend, Sharlene D. Newman
Abstract
Developmental dyslexia is a complex and heterogeneous disorder characterized by unexpected difficulty in learning to read. Although it is considered to be biologically based, the degree of variation has made the nature and locus of dyslexia difficult to ascertain. Hypotheses regarding the cause have ranged from low-level perceptual deficits to higher order cognitive deficits, such as phonological processing and visual-spatial attention. We applied the capacity coefficient, a measure obtained from a mathematical cognitive model of response times to measure how efficiently participants processed different classes of stimuli. The capacity coefficient was used to test the extent to which individuals with dyslexia can be distinguished from normal reading individuals based on their ability to take advantage of word, pronounceable non-word, consonant sequence or unfamiliar context when categorizing character strings. Within subject variability of the capacity coefficient across character string types was fairly regular across normal reading adults and consistent with a previous study of word perception with the capacity coefficient-words and pseudowords were processed at super-capacity and unfamiliar characters strings at limited-capacity. Two distinct patterns were observed in individuals with dyslexia. One group had a profile similar to the normal reading adults while the other group showed very little variation in capacity across string-type. It is possible that these individuals used a similar strategy for all four string-types and were able to generalize this strategy when processing unfamiliar characters. This difference across dyslexia groups may be used to identify sub-types of the disorder and suggest significant differences in word level processing among these subtypes. Therefore, this approach may be useful in further delineating among types of dyslexia, which in turn may lead to better understanding of the etiologies of dyslexia.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 June 2017.
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