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
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".