ReviewJournal of the Association for Research in Otolaryngology : JARO2021
The Panoramic ECAP Method: Estimating Patient-Specific Patterns of Current Spread and Neural Health in Cochlear Implant Users.
Review in Journal of the Association for Research in Otolaryngology : JARO, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.
- Cochlear implant re-mapping informed by measures of viability of the electrode-neural interface: a systematic review with meta-analysis.Scientific reports · 2025Pooled it
- Neural Hearing Loss: Mechanisms, Diagnosis and Treatment Horizons.Journal of the Association for Research in Otolaryngology : JARO · 2026Review
- From Physical Replacement to Biological Symbiosis: Evolutionary Paradigms and Future Prospects of Auditory Reconstruction Brain-Computer Interfaces.Micromachines · 2026Review
- Establishing reliable neural health measures in adult cochlear implant users.Frontiers in neuroscience · 2026Article
- Review
- A comparison of electrophysiological measures for characterizing the cochlear-implant electrode-neuron interface.JASA express letters · 2025Article
- An Integrated Spatial-Spectral Denoising Framework for Robust Electrically Evoked Compound Action Potential Enhancement and Auditory Parameter Estimation.Sensors (Basel, Switzerland) · 2025Article
- An Electrically Evoked Compound Action Potential Marker for Local Spiral Ganglion Neuron Degeneration: The Failure Index.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Comparing Patient-Specific Variations in Intra-Cochlear Neural Health Estimated Using Psychophysical Thresholds and Panoramic Electrically Evoked Compound Action Potentials (PECAPs).Journal of the Association for Research in Otolaryngology : JARO · 2025Article
- The Greenwood function shows close alignment with pitch perceived by cochlear implant patients with long, flexible electrode arrays and fine-structure stimulation.Frontiers in neuroscience · 2025Article
- Investigating the Effect of Blurring and Focusing Current in Cochlear Implant Users with the Panoramic ECAP Method.Journal of the Association for Research in Otolaryngology : JARO · 2024Article
- A new method for removing artifacts from recordings of the electrically evoked compound action potential: Single-pulse stimulation.medRxiv : the preprint server for health sciences · 2024Article
- Article
- The Effects of Stimulus Repetition Rate on Electrically Evoked Auditory Brainstem Potentials in Postlingually Deafened Adult Cochlear Implant Recipients.Journal of clinical medicine · 2023Article
- Models of Cochlea Used in Cochlear Implant Research: A Review.Annals of biomedical engineering · 2023Review
- Cochlear Health and Cochlear-implant Function.Journal of the Association for Research in Otolaryngology : JARO · 2023Review
- Effects of spectral smearing on speech understanding and masking release in simulated bilateral cochlear implants.PloS one · 2023Article
- Factors influencing the relationship between cochlear health measures and speech recognition in cochlear implant users.Frontiers in integrative neuroscience · 2023Article
- Tonotopic Selectivity in Cats and Humans: Electrophysiology and Psychophysics.Journal of the Association for Research in Otolaryngology : JARO · 2022Article
- Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
The knowledge of patient-specific neural excitation patterns from cochlear implants (CIs) can provide important information for optimizing efficacy and improving speech perception outcomes. The Panoramic ECAP ('PECAP') method (Cosentino et al. 2015) uses forward-masked electrically evoked compound action-potentials (ECAPs) to estimate neural activation patterns of CI stimulation. The algorithm requires ECAPs be measured for all combinations of probe and masker electrodes, exploiting the fact that ECAP amplitudes reflect the overlapping excitatory areas of both probes and maskers. Here we present an improved version of the PECAP algorithm that imposes biologically realistic constraints on the solution, that, unlike the previous version, produces detailed estimates of neural activation patterns by modelling current spread and neural health along the intracochlear electrode array and is capable of identifying multiple regions of poor neural health. The algorithm was evaluated for reliability and accuracy in three ways: (1) computer-simulated current-spread and neural-health scenarios, (2) comparisons to psychophysical correlates of neural health and electrode-modiolus distances in human CI users, and (3) detection of simulated neural 'dead' regions (using forward masking) in human CI users. The PECAP algorithm reliably estimated the computer-simulated scenarios. A moderate but significant negative correlation between focused thresholds and the algorithm's neural-health estimates was found, consistent with previous literature. It also correctly identified simulated 'dead' regions in all seven CI users evaluated. The revised PECAP algorithm provides an estimate of neural excitation patterns in CIs that could be used to inform and optimize CI stimulation strategies for individual patients in clinical settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.