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Although Australian languages have a fairly clear grammatical and phonological profile, the great length of time over which they developed makes reconstructing Proto-Australian challenging.
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Northcott et al. [ 19], in order to delineate the memory and phonological awareness profile of children with BECTS, evaluated 42 children and compared results to a proper control group.
This, therefore, suggests that the specific profile of phonological deficits may differ, to some extent, between children with dyslexia and those with SLI. Figure 3 reproduces the 2D space of Bishop and Snowling (2004) and Fig. 1B, with the four quadrants defined by deviance thresholds set a priori at −1.5 SD below the control mean.
SLI and dyslexic children show partly different profiles of phonological deficit along these two dimensions.
Furthermore, children with specific language impairment and dyslexia show partly distinct profiles of phonological deficit along these two dimensions.
To our knowledge, only one published study more specifically compared the profiles of phonological deficit between SLI and dyslexia, and suggested that rapid automatized naming was weaker in children with dyslexia than in children without (Bishop et al., 2009).
Thus, finding evidence for two distinct phonological dimensions and partly different profiles between SLI and dyslexia despite these issues would seem to indicate that the distinction must be robust.
In contrast, activation profiles associated with the phonological strategy featured predominantly activation of the superior temporal gyrus in the left hemisphere between 500 and 600 ms. Predominant activation of the left middle temporal gyrus, between 500 and 700 ms, was the key feature of the activation profile observed when the semantic elaboration strategy was utilized.
The second dyslexic subtype had a reverse cognitive profile compared to first subtype, i.e., while phonological and magnocellular-dorsal skills were comparable to controls, the children showed impairments in rapid naming and auditory attention shifting.
The simulations not only accounted fairly well for individual reading patterns but also captured the different dyslexia profiles discussed in the literature (i.e., surface, phonological, mixed, and mild dyslexia).
The three profiles differed in nonsymbolic and symbolic numerical magnitude processing as well as phonological processing, but not in digit naming or working memory.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com