Semantic fluency in aphasia: clustering and switching in the course of 1 minute
Notice bibliographique
Résumé
BACKGROUND: Verbal fluency tasks are included in a broad range of aphasia assessments. It is well documented that people with aphasia (PWA) produce fewer items in these tasks. Successful performance on verbal fluency relies on the integrity of both linguistic and executive control abilities. It remains unclear if limited output in aphasia is solely due to their lexical retrieval difficulties or has a basis in their executive control abilities. Analysis techniques, such as temporal characteristics of word retrieved, clustering and switching, are better positioned to inform the debate surrounding the lexical and/or executive control contribution for success in verbal fluency. AIMS: To investigate the differences in quantitative (i.e., number of correct words) and qualitative (i.e., switching, clustering and word-retrieval times) performances on animal fluency task as a function of time between PWA and healthy control speakers (CS). METHODS & PROCEDURES: Animal fluency data for 60 s were collected from 34 PWA and 34 CS, and responses were time stamped. The 60-s period was divided into four equal intervals of 15 s each (i.e., 15, 30, 45 and 60 s). The number of correct words, cluster size, number of switches, within-cluster pause and between-cluster pause were evaluated as a function of four 15-s time intervals between PWA and CS. OUTCOMES & RESULTS: Compared with CS, PWA produced fewer words, had smaller cluster sizes and switched a fewer number of times. A decrease in the number of switches correlated with an increase in between-cluster pause durations. PWA showed longer within- and between-cluster pauses than CS. The two groups showed specific differences in the temporal pattern of the responses: as time evolved both PWA and CS showed decreased productivity for the number of correct words, but PWA reached the asymptote earlier in the time course than CS, neither group showed a change in cluster size, and the number of switches decreased as a function of time only for CS. CONCLUSIONS & IMPLICATIONS: The findings suggest that for PWA the search and retrieval process is less productive and more effortful. This is indicated by smaller cluster size, fewer switches associated with increased between-cluster pause durations, as well as overall slowed retrieval times for the words. This shows that the difficulties with verbal fluency performance in aphasia have a strong basis in their lexical retrieval processes, as well as some difficulties in the executive component of the task.
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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 | 0,000 | 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 | 0,000 |
| 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) | 0,002 | 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 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 ».