Association between spectral EEG power and autism risk and diagnosis: Utilizing large scale data-platforms to advance our understanding of the early development of ASD
Notice bibliographique
Résumé
Background: Autism spectrum disorder (ASD) has its origins in the atypical development of brain networks.Infants who are at high familial risk for ASD and are later diagnosed with the condition have early brain overgrowth, altered development of white matter pathways, and atypical connectivity.Electroencephalography (EEG) oscillatory power is a measure of cortical activity and has also been associated with familial risk, and recently reported to be associated with ASD outcomes.However, infant-sibling studies are often constrained by relatively small sample sizes, and the field would benefit from a large data-platform of existing infant-sibling datasets, similar to other data-platforms that have been established in the broader autism research field.Methods: We established the EEG-Integrated Platform (EEG-IP), a large multi-site dataset with 432 participants, including 222 at high-risk (HR) for ASD and 193 at low-risk (LR) for ASD, from whom repeated measurements of resting EEG were collected between the ages of 3-36 months, along with comprehensive diagnostic assessments in toddlerhood.A latent growth curve model was applied to test whether familial risk status predicts developmental trajectories of spectral power development across the first 3 years of life, and then whether these trajectories predict ASD outcome.Results: Independent of ASD risk and outcome, change in spectral EEG power in all frequency bands during the first three years of life was significantly different from zero, most notably with increases in relative and absolute low-alpha and high-alpha power.Familial risk, but not a later diagnosis of ASD in toddlerhood, was associated with reduced absolute power in all frequency bands in early development, but not with differences in relative power.Discussion: This thesis investigated developmental changes in spectral power over the first three years of life using the largest infant-sibling sample to date, made possible by the EEG-IP dataplatform.Trajectories of spectral power throughout early development appears to be predicted by familial risk, however spectral power does not in turn predict diagnostic outcome above and beyond familial risk status.Absolute power, but not relative power appears to be impacted by familial risk status.Future research should examine the utility of oscillatory power as a biomarker of developmental outcomes that extend beyond diagnostic boundaries.
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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 | 0,000 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».