Differential speech and language characteristics across neurodegenerative disorders
Notice bibliographique
Résumé
Abstract Background Speech and language changes have been reported to occur across a range of neurodegenerative disorders, including Alzheimer’s Disease (AD), Frontotemporal Dementia (FTD) and Parkinson’s Disease (PD). Characterizing and quantifying such changes will enable the development of novel speech‐based measures to identify and monitor disease remotely and non‐invasively. In order to determine if such measures are disease‐specific, it is important to compare speech and language changes across different neurological conditions. In this study, we identify speech and language characteristics that are differentially affected across AD, FTD and PD populations. Method In this cross‐study comparison, we pooled data from normative studies of older adults (N = 299), and studies of individuals with a clinical diagnosis of AD (N = 895), FTD (N = 43) or PD (N = 42). In all studies, speech was recorded as participants performed a picture description task, in which they were shown a line drawing of a scene and asked to describe everything they saw in the picture. Speech samples were transcribed and analyzed, producing >500 acoustic and linguistic variables describing the characteristics of the speech sound and content. Speech variables were compared across groups using ANOVAs with a factor of diagnosis group, and significant group effects (p < 0.05) were further examined with pairwise group comparisons. Result Speech variables showing common or differential effects according to diagnosis were identified in this exploratory cross‐study comparison. Speech variables relating to the ease of speech production, including speech rate and number of pauses, were affected in all three diseases when compared to control participants. Select acoustic variables, including mean intensity and zero‐crossing rate, showed the greatest differences in PD compared to FTD or AD. Individuals with AD and FTD produced picture descriptions with less relevant information content. Select lexical variables, including pronoun and preposition use, were selectively affected in AD but not FTD or PD. Conclusion This study indicates that speech and language characteristics, derived from a picture description task, were differentially affected in AD, FTD, and PD. We found evidence for acoustic changes in PD, consistent with motor speech impairments, and linguistic changes in AD and FTD, consistent with cognitive impairments.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».