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Record W2986827522 · doi:10.7554/elife.06576.012

Author response: Tinnitus and hyperacusis involve hyperactivity and enhanced connectivity in auditory-limbic-arousal-cerebellar network

2015· peer-review· en· W2986827522 on OpenAlexaff
Yu‐Chen Chen, Xiaowei Li, Lijie Liu, Jian Wang, Chun‐Qiang Lu, Ming Yang, Yun Jiao, Fengchao Zang, Kelly E. Radziwon, Guang‐Di Chen, Wei Sun, Vijaya Prakash Krishnan Muthaiah, Richard Salvi, Gao‐Jun Teng

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHyperacusisTinnitusAuditory cortexAudiologyNeurosciencePsychologyInferior colliculusHearing lossAmygdalaMedial geniculate bodyMedicine

Abstract

fetched live from OpenAlex

One in three adults over the age of 65 will experience a significant loss of hearing. This is often worsened by related conditions, such as: tinnitus, an unexplained constant buzzing or ringing sound; and hyperacusis, whereby everyday sounds are perceived as too loud or painful. Most hearing loss is caused by damage to the sound-sensitive cells within a structure in the inner ear called the cochlea. Some studies have also identified regions of the brain that show abnormal activity in people with tinnitus and hyperacusis. However, the results from different patients have often been inconsistent and sometimes contradictory, and so it remains unclear what exactly causes these conditions. To overcome this problem, Chen et al. made use of the fact that tinnitus and hyperacusis are common short-term side effects of certain drugs and measured the brain activity in rats before and after they were given one such drug. Before receiving the drug, the rats had first been trained to expect to receive a food pellet from the left side of their cage when they heard a steady buzzing sound. The rats were also trained to expect a food pellet from their right if they heard nothing at all. Shortly after receiving the drug, the rats often failed to respond correctly in the ‘quiet tests’ and behaved like they were already experiencing a constant buzzing sound, as would be expected if they had tinnitus. Further tests confirmed that the drug also triggered behavior in the rats that is typical of people with hyperacusis. Chen et al. then discovered that the drug treatment reduced the nerve signals that are sent from a rat's cochlea. Moreover, the drug treatment greatly increased the activity in response to sound within parts of the rat's brain; these and other parts of the brain also became overactive in drug-treated rats in the absence of sound. Finally, further experiments revealed that drug-treated rats had stronger connections between these brain regions than in normal rats. Chen et al. used these results to propose a model to explain the underlying causes of tinnitus and hyperacusis. However, because the drug treatment only induces short-term hearing impairment, further studies are needed to see if this model also applies when these conditions are long-term.

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)0.001
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0140.009
Insufficient payload (model declined to judge)0.0760.030

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 head0.089
GPT teacher head0.350
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2015
Admission routes1
Has abstractyes

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