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Record W2494656067 · doi:10.1523/eneuro.0207-16.2016

Type II Cochlear Ganglion Neurons Do Not Drive the Olivocochlear Reflex: Re-Examination of the Cochlear Phenotype in Peripherin Knock-Out Mice

2016· article· en· W2494656067 on OpenAlexfundno aff
Stéphane F. Maison, Leslie D. Liberman, M. Charles Liberman

Bibliographic record

VenueeNeuro · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication DisordersUniversité Laval
KeywordsPeripherinSpiral ganglionReflexPhenotypeCochleaMedicineAudiologyNeuroscienceBiologyGeneticsGene

Abstract

fetched live from OpenAlex

The cochlear nerve includes a small population of unmyelinated sensory fibers connecting outer hair cells to the brain. The functional role of these type II afferent neurons is controversial, because neurophysiological data are sparse. A recent study (Froud et al., 2015) reported that targeted deletion of peripherin, a type of neurofilament, eliminated type II afferents and inactivated efferent feedback to the outer hair cells, thereby suggesting that type II afferents were the sensory drive to this sound-evoked, negative-feedback reflex, the olivocochlear pathway. Here, we re-evaluated the cochlear phenotype in mice from the peripherin knock-out line and show that (1) type II afferent terminals are present in normal number and (2) olivocochlear suppression of cochlear responses is absent even when this efferent pathway is directly activated by shocks. We conclude that type II neurons are not the sensory drive for the efferent reflex and that peripherin deletion likely causes dysfunction of synaptic transmission between olivocochlear terminals and their peripheral targets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.039
GPT teacher head0.283
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2016
Admission routes1
Has abstractyes

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