2026-02-09 スタンフォード大学
<関連情報>
- https://news.stanford.edu/stories/2026/02/math-learning-disability-brain-patterns-research
- https://med.stanford.edu/news/all-news/2026/02/math-learning-disability-affects-how-the-brain-tackles-problems-.html
- https://www.jneurosci.org/content/early/2026/01/30/JNEUROSCI.2385-24.2025
数学的学習障害のある子どもとない子どもの数量弁別を規定する潜在的な神経認知メカニズム Latent neurocognitive mechanisms underlying quantity discrimination in children with and without mathematical learning disabilities
Hyesang Chang, Percy K. Mistry, Yuan Zhang, Flora Schwartz and Vinod Menon
Journal of Neuroscience Published:9 February 2026
DOI:https://doi.org/10.1523/JNEUROSCI.2385-24.2025
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 non-symbolic 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 post-error adjustment, despite similar observed performance measures between groups. The latent cognitive processes during symbolic quantity discrimination predicted broader mathematical abilities better than those during non-symbolic 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 post-error 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.
Significance Statement Considerable debate exists regarding the nature of deficits in mathematical learning disabilities (MLD). By developing an innovative computational model that captures subtle aspects of decision-making processes, we reveal that children with MLD show specific difficulties in adapting their problem-solving strategies when working with numerical symbols. Using brain imaging, we found that these difficulties are linked to reduced activity in brain regions involved in monitoring and adjusting behavior. Importantly, these deficits were specific to symbolic number processing and predicted children’s broader mathematical abilities. Our findings suggest that MLD involves not only difficulties with basic number processing, but also problems in regulating cognitive strategies when working with numerical symbols. This insight could lead to more effective interventions for children struggling with mathematics.
