Developmental dyscalculia is not associated with atypical brain activation: A univariate <scp>fMRI</scp> study of arithmetic, magnitude processing, and visuospatial working memory
Notice bibliographique
Résumé
Functional neuroimaging serves as a tool to better understand the cerebral correlates of atypical behaviors, such as learning difficulties. While significant advances have been made in characterizing the neural correlates of reading difficulties (developmental dyslexia), comparatively little is known about the neurobiological correlates of mathematical learning difficulties, such as developmental dyscalculia (DD). Furthermore, the available neuroimaging studies of DD are characterized by small sample sizes and variable inclusion criteria, which make it problematic to compare across studies. In addition, studies to date have focused on identifying single deficits in neuronal processing among children with DD (e.g., mental arithmetic), rather than probing differences in brain function across different processing domains that are known to be affected in children with DD. Here, we seek to address the limitations of prior investigations. Specifically, we used functional magnetic resonance imaging (fMRI) to probe brain differences between children with and without persistent DD; 68 children (8-10 years old, 30 with DD) participated in an fMRI study designed to investigate group differences in the functional neuroanatomy associated with commonly reported behavioral deficits in children with DD: basic number processing, mental arithmetic and visuo-spatial working memory (VSWM). Behavioral data revealed that children with DD were less accurate than their typically achieving (TA) peers for the basic number processing and arithmetic tasks. No behavioral differences were found for the tasks measuring VSWM. A pre-registered, whole-brain, voxelwise univariate analysis of the fMRI data from the entire sample of children (DD and TA) revealed areas commonly associated with the three tasks (basic number processing, mental arithmetic, and VSWM). However, the examination of differences in brain activation between children with and without DD revealed no consistent group differences in brain activation. In view of these null results, we ran exploratory, Bayesian analyses on the data to quantify the amount of evidence for no group differences. This analysis provides supporting evidence for no group differences across all three tasks. We present the largest fMRI study comparing children with and without persistent DD to date. We found no group differences in brain activation using univariate, frequentist analyses. Moreover, Bayesian analyses revealed evidence for the null hypothesis of no group differences. These findings contradict previous literature and reveal the need to investigate the neural basis of DD using multivariate and network-based approaches to brain imaging.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».