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Competing theories of dyslexia posit that reading difficulties arise from impaired visual, auditory, phonological, or statistical learning mechanisms. Importantly, many theories posit that dyslexia reflects a cascade of impairments emanating from a single “core deficit”. Here we report two studies evaluating core deficit and multifactorial models. In Study 1, we use publicly available data from the Healthy Brain Network to test the accuracy of phonological processing measures for predicting dyslexia diagnosis and find that over 30% of cases are misclassified (sensitivity = 66.7%; specificity = 68.2%). In Study 2, we collect a battery of psychophysical measures of visual motion processing and standardized measures of phonological processing in 106 school‐aged children to investigate whether dyslexia is best conceptualized under a core‐deficit model, or as a disorder with heterogenous origins. Specifically, by capitalizing on the drift diffusion model to analyze performance on a visual motion discrimination experiment, we show that deficits in visual motion processing, perceptual decision‐making, and phonological processing manifest largely independently. Based on statistical models of how variance in reading skill is parceled across measures of visual processing, phonological processing, and decision‐making, our results challenge the notion that a unifying deficit characterizes dyslexia. Instead, these findings indicate a model where reading skill is explained by several distinct, additive predictors, or risk factors, of reading (dis)ability., Using predictors from a visual motion processing experiment and linguistic measures, we show that a single‐mechanism model of reading disability cannot account for the range of linguistic and sensory processing outcomes observed in children. We propose an additive risk factor model where different aspects of sensory, cognitive and language function each contribute independently to reading development.

Infants as young as 2 months can integrate audio and visual aspects of speech articulation. A shift of attention from the eyes towards the mouth of talking faces occurs around 6 months of age in monolingual infants. However, it is unknown whether this pattern of attention during audiovisual speech processing is influenced by speech and language experience in infancy. The present study investigated this question by analysing audiovisual speech processing in three groups of 4‐ to 8‐month‐old infants who differed in their language experience: monolinguals, unimodal bilinguals (infants exposed to two or more spoken languages) and bimodal bilinguals (hearing infants with Deaf mothers). Eye‐tracking was used to study patterns of face scanning while infants were viewing faces articulating syllables with congruent, incongruent and silent auditory tracks. Monolinguals and unimodal bilinguals increased their attention to the mouth of talking faces between 4 and 8 months, while bimodal bilinguals did not show any age difference in their scanning patterns. Moreover, older (6.6 to 8 months), but not younger, monolinguals (4 to 6.5 months) showed increased visual attention to the mouth of faces articulating audiovisually incongruent rather than congruent faces, indicating surprise or novelty. In contrast, no audiovisual congruency effect was found in unimodal or bimodal bilinguals. Results suggest that speech and language experience influences audiovisual integration in infancy. Specifically, reduced or more variable experience of audiovisual speech from the primary caregiver may lead to less sensitivity to the integration of audio and visual cues of speech articulation.

Many everyday actions are implicit gambles because imprecisions in our visuomotor systems place probabilities on our success or failure. Choosing optimal action strategies involves weighting the costs and gains of potential outcomes by their corresponding probabilities, and requires stable representations of one's own imprecisions. How this ability is acquired during development in childhood when visuomotor skills change drastically is unknown. In a rewarded rapid reaching task, 6‐ to 11‐year‐old children followed ‘risk‐seeking’ strategies leading to overly high point‐loss. Adults' performance, in contrast, was close to optimal. Children's errors were not explained by distorted estimates of value or probability, but may reflect different action selection criteria or immature integration of value and probability information while planning movements. These findings provide a starting point for understanding children's risk‐taking in everyday visuomotor situations when suboptimal choices can be dangerous. Moreover, children's risky visuomotor decisions mirror those reported for non‐motor gambles, raising the possibility that common processes underlie development across decision‐making domains.