Examining the Neural and Cognitive Processes Underlying Typical and Atypical Reading Ability
Notice bibliographique
Résumé
Although reading is an important and generative skill that is important for a child’s future academic, economic, and social success, it remains controversial how it develops and what leads to reading difficulties. Furthermore, due to the multiple and complex components involved during reading, the neuroanatomical mechanisms that support the behavioral differences of reading ability are currently not well understood. Therefore, the overarching goal of this thesis was to further the understanding of reading and reading difficulties by integrating aspects of their neuroscientific, cognitive, and educational accounts, as illustrated by functional magnetic resonance imaging (fMRI), eye tracking, and speech recording. To simplify the examination of the processes involved in reading, we focused on naming speed (NS) tasks, in which participants are required to name sets of simple stimuli as quickly and as accurately as possible, because these tasks have been shown to predict concurrent and future reading ability in both typically achieving readers and in poor readers. Using NS tasks, we examined improvements in behavioral performance associated with typical development from childhood to adulthood, and how this differed in children and adults with dyslexia. We also examined how behavioral and neural differences between typically achieving readers and readers with dyslexia were related, and how they were associated with compensatory strategies used by readers with dyslexia to account for their reading disability. Overall, the findings of the five studies presented in this thesis indicate how combining multiple techniques, such as fMRI, eye tracking, and speech recording, to study reading and reading deficits provides a better controlled, more global view of the processes that are involved and how these processes differ in individuals with reading difficulties. Future research that adopts this multidimensional approach to examining reading difficulties is important because it will not only lead to the optimization of current diagnostic criteria for dyslexia, but also has the potential to lead to the early identification of children who are biologically at risk for developing dyslexia. This in turn has the potential to lead to more effective and appropriate interventions which can positively impact and change the outcome trajectories for those with reading deficits.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».