Hidden hearing loss in tinnitus with normal hearing thresholds
Bibliographic record
Abstract
Tinnitus—the phantom ringing of the ears—is thought arise from neuroplastic changes in the central auditory system in response to peripheral hearing damage. However, a minority of tinnitus sufferers have clinically normal hearing thresholds. One explanation of these cases is that auditory nerve fibers with low firing thresholds (LT-ANFs) are intact, but ANFs with high thresholds (HT-ANFs) are not. HT-ANF damage would be “hidden” to the audiogram but evident in suprathreshold tests. To test this hypothesis, we measured the ability of tinnitus and control subjects with normal audiograms to detect amplitude modulation (AM) in a 5 kHz, suprathreshold tone in a narrowband noise. We also recorded by 32-channel EEG the “envelope following response” (EFR, generated subcortically) to the same AM tone in conditions of noise and no noise. Tinnitus subjects had worse AM detection thresholds and had smaller EFRs compared to controls. Simulations of ANF responses from the model of Zilany et al. (2014) found that in addition to ~100% loss of HT ANFs, a further ~30% loss of LT fibers was needed to account for the reduced EFRs of tinnitus subjects. ~30% of LT ANFs would not have been expected to affect hearing thresholds. [Work supported by NSERC of Canada.]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".