Evaluating the N1-P2 interpeak latency of the eCAP and its inter-trial variability as potential indicators of neural synchrony in the cochlear nerve of cochlear implant users
Notice bibliographique
Résumé
ABSTRACT Objective This study evaluated interpeak latency (IPL) and its inter-trial variability (VIL) of the electrically evoked compound action potential (eCAP) as potential alternatives to the phase-locking value (PLV) for quantifying cochlear nerve (CN) synchrony in cochlear implant (CI) users. Design The IPL was assessed in postlingually deafened adults and three pediatric populations: children with auditory neuropathy spectrum disorder, cochlear nerve deficiency, and typical sensorineural hearing loss. VIL was evaluated only in adults. Their associations with temporal resolution and speech perception outcomes were evaluated. Frequency analysis was conducted to understand the impacts of eCAP recording noise on IPL, VIL, and PLV. Simulations of inter-trial jitter in the eCAP were performed to quantify how the IPL, VIL, and PLV metrics varied with increased temporal jitter. Results eCAP traces recorded in all patient groups showed a multi-peak issue affecting the accuracy of IPL and VIL assessments. Temporal resolution and speech perception outcomes were significantly correlated with VIL but not with IPL metrics. The PLV was impacted less by recording noise than either the IPL or the VIL. Simulation results revealed that the IPL was less sensitive to the amount of inter-trial jitter in the eCAP than were the VIL and the PLV. Conclusions The IPL is not a reliable indicator of CN synchrony. The VIL is indicative of neural synchrony in the CN but is affected more by the eCAP recording noise than the PLV. The PLV is therefore the preferred measure for quantifying neural synchrony in the CN in CI users. Statements and Declarations Conflict of Interest None. IRB information The data reported in this study were collected for the projects that were approved by the biomedical Institutional Review Board (IRB) of The Ohio State University (IRB study #: 2017H0131, 2018H0344 and 2018N0005; PI: Shuman He), and the IRB of the University of North Carolina at Chapel Hill (IRB study #: 12–1737; PI: Shuman He). Author Contributions SH designed this study, participated in data analysis, drafted and approved the final version of this paper. ICB participated in study design and data analysis, conducted computational modeling work, drafted and approved the final version of this paper. ZG participated in data analysis, provided critical comments, and approved the final version of this paper. RAA participated in data analysis and approved the final version of this paper. CRM participated in data collection and approved the final version of this paper. Data Availability Statement The data that support the findings of this study are available from the authors upon reasonable request with permissions from The Ohio State University and the University of North Carolina at Chapel Hill.
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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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 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 | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».