Project DyAdd: Implicit learning in adult dyslexia and ADHD

Abstract

In this study of the project DyAdd, implicit learning was investigated through two paradigms in adults (18-55 years) with dyslexia (n = 36) or with attention deficit/hyperactivity disorder (ADHD, n = 22) and in controls (n = 35). In the serial reaction time (SRT) task, there were no group differences in learning. However, those with ADHD exhibited faster RTs compared to other groups. In the artificial grammar learning (AGL) task, the groups did not differ from each other in their learning (i.e., grammaticality accuracy or similarity choices). Further, all three groups were sensitive to fragment overlap between learning and test-phase items (i.e., similarity choices were above chance). Grammaticality performance of control participants was above chance, but that of participants with dyslexia and participants with ADHD failed to differ from chance, indicating impaired grammaticality learning in these groups. While the main indices of AGL performance, grammaticality accuracy and similarity choices did not correlate with the neuropsychological variables that reflected dyslexia-related (phonological processing, reading, spelling, arithmetic) or ADHD-related characteristics (executive functions, attention), or intelligence, the explicit knowledge for the AGL grammar (i.e., ability to freely generate grammatical strings) correlated positively with the variables of phonological processing and reading. Further, SRT reaction times correlated positively with full scale intelligence quotient (FIQ). We conclude that, in AGL, learning difficulties of the underlying rule structure (as measured by grammaticality) are associated with dyslexia and ADHD. However, learning in AGL is not related to the defining neuropsychological features of dyslexia or ADHD. Instead, the resulting explicit knowledge relates to characteristics of dyslexia.

Procedural and declarative learning in dyslexia

“…This pattern of differences between the groups may indicate that extraneous factors, such as impaired coordination or motor learning (Ramus, Pidgeon, & Frith, ), influence the performance of children with dyslexia on the serial reaction time tasks. This conjecture is in line with findings from some previous studies in children with dyslexia (Vakil, Lowe, & Goldfus, ) and adults (Henderson & Warmington, ; Laasonen et al, ). Finally, it should be noted that individual differences in procedural learning did not correlate with word or non‐word reading in either group.…”

“…This conjecture is in line with findings from some previous studies in children with dyslexia (Vakil, Lowe, & Goldfus, 2015) and adults (Henderson & Warmington, 2017;Laasonen et al, 2014). Finally, it should be noted that individual differences in procedural learning did not correlate with word or non-word reading in either group.…”

Evaluating the consequences of impaired monitoring of learned behavior in attention-deficit/hyperactivity disorder using a Bayesian hierarchical model of choice response time.

“…However, several previous studies have found no abnormalities in SRT performance or in reactions to conflict on the transfer block, as indexed by mean RTs, in this population (Karatekin et al, 2009; Laasonen et al, 2014; Vloet et al, 2010; but see Barnes et al, 2010 1 ). This is likely in part because the standard performance measure used in SRT is MRT.…”

Paired associate learning tasks and their contribution to reading skills

“…However, passive exposure to corresponding sound and letter sequences may also occur, resulting in associated orthographical and phonological representations that have been implicitly acquired and become part of an automatized procedure in the decoding process (Snowling, 1980). Children with reading difficulties exhibit lower performance on certain types of implicit learning tasks (Folia et al, 2008; Laasonen et al, 2014; Vicari et al, 2005). Thus, associative learning has been studied as a predictor of reading skills (Muter, Hulme, Snowling, & Stevenson, 2004).…”