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Record W2030013301 · doi:10.3109/00016489.2011.648271

Resting neural activity patterns in auditory brainstem and midbrain in conductive hearing loss

2012· article· en· W2030013301 on OpenAlexafffund
Robert V. Harrison, Jaina Negandhi

Bibliographic record

VenueActa Oto-Laryngologica · 2012
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsHospital for Sick ChildrenSickKids FoundationUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsInferior colliculusCochlear nucleusBrainstemMidbrainNeuroscienceConductive hearing lossAuditory systemAudiologyContext (archaeology)Hearing lossBiologyThalamusNucleusCochlear nerveAuditory brainstem responseAnatomyCentral nervous systemMedicineCochlea

Abstract

fetched live from OpenAlex

CONCLUSIONS: Conductive hearing loss (CHL) lowers resting neural activity patterns in the auditory periphery. Such reductions of peripheral auditory activity may influence the developing central brain during early postnatal years when the system is still highly plastic. OBJECTIVES: A common cause of CHL in young children is otitis media; if chronic and/or episodic there may be a risk to speech and language development. In this clinical context we have investigated changes in neural activity patterns in the brainstem and midbrain in an animal model of CHL. METHODS: In a mouse model, a 50-60 dB CHL was produced by blocking the ear canals. We quantified resting neural activity patterns in the cochlear nucleus and inferior colliculus using c-fos immuno-labelling. This experimental group was compared with normal-hearing controls and with animals with bilateral cochlear ablation. RESULTS: Subjects with CHL had a statistically significant reduction in c-fos-labelled cells in the cochlear nucleus and central nucleus of the inferior colliculus compared with normal controls. This decreased c-fos expression suggests a change in resting neural activity generated at the inner hair cell synapse, leading to a reduction in activity levels in the ascending auditory pathways.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.303
Teacher spread0.218 · 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 teacher head, not a consensus.

Study designObservational
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

Citations13
Published2012
Admission routes2
Has abstractyes

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