Graph complexity as measured by topological entropy has been previously shown to affect performance on artificial grammar learning tasks among typically developing children. The aim of this study was to examine the effect of graph complexity on implicit sequential learning among children with developmental dyslexia. Our goal was to determine…

There is a long held view that chunks play a crucial role in artificial grammar learning performance. We compared chunk strength influences on performance, in high and low topological entropy (a measure of complexity) grammar systems, with dyslexic children, age-matched and reading-level-matched control participants. Findings show that age-matched…

The importance of feedback for learning has been firmly established over the past few decades. The question of whether feedback plays a significant role in the statistical learning abilities of adults with dyslexia, however, is currently unresolved. Here, we examined the role of feedback in grammaticality judgment, type of structural knowledge,…

The aim of the present study was to investigate implicit learning processes among adults with developmental dyslexia (DD) using a visual linguistic artificial grammar learning (AGL) task. Specifically, it was designed to explore whether the intact learning reported in previous studies would also occur under conditions including minimal training…