Speech recognition is a complex human behavior in the course of which listeners must integrate the detailed phonetic information present in the acoustic signal with their general linguistic knowledge. It is commonly assumed that this process occurs effortlessly for most people, but it is still unclear whether this also holds true in the case of developmental dyslexia (DD), a condition characterized by perceptual deficits. In the present study, we used a dual-task setting to test the assumption that speech recognition is effortful for people with DD. In particular, we tested the Ganong effect (i.e., lexical bias on phoneme identification) while participants performed a secondary task of either low or high cognitive demand. We presumed that reduced efficiency in perceptual processing in DD would manifest in greater modulation in the performance of primary task by cognitive load. Results revealed that this was indeed the case. We found a larger Ganong effect in the DD group under high than under low cognitive load, and this modulation was larger than it was for typically developed (TD) readers. Furthermore, phoneme categorization was less precise in the DD group than in the TD group. These findings suggest that individuals with DD show increased reliance on top-down lexically mediated perception processes, possibly as a compensatory mechanism for reduced efficiency in bottom-up use of acoustic cues. This indicates an imbalance between bottom-up and top-down processes in speech recognition of individuals with DD.

Developmental Language Disorder (DLD) is presumed to arise due to a malfunctioning procedural memory system alongside a preserved/enhanced declarative memory system. Despite accumulating evidence supporting this notion, there is a major gap in our understanding of procedural learning functions in DLD. Prior research has tended to focus on the impaired outcomes of procedural learning in DLD but has not yet systematically studied the learning process that leads to these differences. Without fine-grained assessment of online processing during learning, it is impossible to ascertain the cause of poorer learning outcomes in DLD. Here we capitalized on perceptual category learning combined with computational models that characterize the strategies employed during learning to unravel the nature of procedural learning disruption in DLD. Children with DLD and typically developed (TD) children completed two well-matched nonspeech auditory category learning challenges to draw upon presumed procedural (information-integration) versus declarative (rule-based) learning systems. We observed impaired information-integration category learning and intact rule-based category learning in the DLD group compared to the TD group. Quantitative model-based analyses revealed reduced use of, and slower shifting to, optimal procedural-based strategies in DLD and slower shifting to but similarly efficient use of optimal hypothesis-testing strategies. The dissociation is consistent with the procedural deficit hypothesis and multiple category learning systems. To the extent that perceptual category learning via procedural memory systems is a basic building block upon which linguistic skills are formed, the present findings promote our understanding of the difficulties children with DLD face in forming stable linguistic representations.