ReviewiScience2023
En route to sound coding strategies for optical cochlear implants.
Review in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hearing loss is the most common human sensory deficit. Severe-to-complete sensorineural hearing loss is often treated by electrical cochlear implants (eCIs) bypassing dysfunctional or lost hair cells by direct stimulation of the auditory nerve. The wide current spread from each intracochlear electrode array contact activates large sets of tonotopically organized neurons limiting spectral selectivity of sound coding. Despite many efforts, an increase in the number of independent eCI stimulation channels seems impossible to achieve. Light, which can be better confined in space than electric current may help optical cochlear implants (oCIs) to overcome eCI shortcomings. In this review, we present the current state of the optogenetic sound encoding. We highlight optical sound coding strategy development capitalizing on the optical stimulation that requires fine-grained, fast, and power-efficient real-time sound processing controlling dozens of microscale optical emitters as an emerging research area.
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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.