Abstract
Children with dyslexia have elevated psychophysical thresholds in global motion tasks. However, threshold estimates conflate multiple processes so it is unclear which processing stages are altered in dyslexia. The drift-diffusion framework offers the possibility to model accuracy and response time distributions to decompose performance into separate processing components, which can then be linked to neural measures. Within this framework, the decision-making process is modelled as an accumulation of noisy sensory information towards one of two decision bounds. The main parameters are drift-rate (reflecting the rate of evidence accumulation), boundary separation (reflecting response conservativeness), and non-decision time (reflecting sensory encoding and response generation). Here, 50 children with a dyslexia diagnosis and 50 typically developing children aged 6 to 14 years judged the direction of coherent motion and Gaussian motion stimuli as quickly and accurately as possible. High-density EEG data were collected for most participants. Dyslexic children were slightly slower to respond for both stimulus types and were less accurate for Gaussian motion stimuli. In our pre-registered analyses, we fitted hierarchical Bayesian diffusion models to the data, both with and without controlling for differences in age. When controlling for differences in age, there was evidence for a reduced drift-rate in dyslexic children compared to typical children for both stimulus types (coherent motion: BF10=4.57; Gaussian motion: BF10=4.28). The evidence for differences in other parameters was inconclusive. We also identified a response-locked EEG component which was maximal over centro-parietal electrodes, which had lower amplitudes in dyslexic children compared to typically developing children. The results suggest that dyslexic children are slower to extract sensory evidence from motion stimuli.