Performance of children with developmental dyslexia on high and low topological entropy artificial grammar learning task.

Performance of children with developmental dyslexia on high and low topological entropy artificial grammar learning task.
Ann Dyslexia. 2016 Oct 19;
Authors: Katan P, Kahta S, Sasson A, Schiff R
Abstract
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 whether children's performance depends on the complexity level of the grammar system learned. We conducted two artificial grammar learning experiments that compared performance of children with developmental dyslexia with that of age- and reading level-matched controls. Experiment 1 was a high topological entropy artificial grammar learning task that aimed to establish implicit learning phenomena in children with developmental dyslexia using previously published experimental conditions. Experiment 2 is a lower topological entropy variant of that task. Results indicated that given a high topological entropy grammar system, children with developmental dyslexia who were similar to the reading age-matched control group had substantial difficulty in performing the task as compared to typically developing children, who exhibited intact implicit learning of the grammar. On the other hand, when tested on...

Source: Annals of Dyslexia - October 18, 2016 Category: Neurology Authors: Katan P, Kahta S, Sasson A, Schiff R Tags: Ann Dyslexia Source Type: research