ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2026
Latent Neurocognitive Mechanisms Underlying Quantity Discrimination in Children with and without Mathematical Learning Disabilities.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Mathematical learning disabilities (MLD) affect up to 14% of school-age children, yet the underlying neurocognitive mechanisms remain elusive. We developed drift diffusion model with dynamic performance monitoring (DDM-DPM), an innovative cognitive model that captures both external and internal sources of structural variability in task performance. Combining DDM-DPM with functional brain imaging, we examined symbolic and nonsymbolic quantity discrimination in female and male children with MLD and typically developing children matched on age, gender, and IQ. Children with MLD showed format-dependent alterations in response caution and posterror adjustment, despite similar observed performance measures between groups. The latent cognitive processes during symbolic quantity discrimination predicted broader mathematical abilities better than those during nonsymbolic quantity discrimination. Neuroimaging results revealed that reduced activity in middle frontal gyrus mediated deficits in response caution in symbolic format, while reduced activity in the anterior cingulate cortex mediated deficits in posterror adjustment in symbolic format in children with MLD. These findings provide novel support for a multidimensional deficit view of MLD that extends beyond basic number processing to include metacognitive processes. Our findings also provide novel support for and extend the access deficit model, which posits that individuals with MLD may have relatively intact quantity representations but struggle with numerical representations in symbolic formats. Our study highlights the value of integrating latent cognitive modeling with neuroimaging to reveal subtle mechanisms underlying learning disabilities and identify potential targets for intervention.
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