Inner Hair Cell Loss Disrupts Hearing and Cochlear Function Leading to Sensory Deprivation and Enhanced Central Auditory Gain
Bibliographic record
Abstract
There are three times as many outer hair cells (OHC) as inner hair cells (IHC), yet IHC transmit virtually all acoustic information to the brain as they synapse with 90-95% of type I auditory nerve fibers. Here we review a comprehensive series of experiments aimed at determining how loss of the IHC/type I system affects hearing by selectively destroying these cells in chinchillas using the ototoxic anti-cancer agent carboplatin. Eliminating IHC/type I neurons has no effect on distortion product otoacoustic emission or the cochlear microphonic potential generated by OHC; however, it greatly reduces the summating potential produced by IHC and the compound action potential (CAP) generated by type I neurons. Remarkably, responses from remaining auditory nerve fibers maintain sharp tuning and low thresholds despite innervating regions of the cochlea with ~80% IHC loss. Moreover, chinchillas with large IHC lesions have surprisingly normal thresholds in quiet until IHC losses exceeded 80%, suggesting that only a few IHC are needed to detect sounds in quiet. However, behavioral thresholds in broadband noise are elevated significantly and tone-in-narrow band noise masking patterns exhibit greater remote masking. These results suggest the auditory system is able to compensate for considerable loss of IHC/type I neurons in quiet but not in difficult listening conditions. How does the auditory brain deal with the drastic loss of cochlear input? Recordings from the inferior colliculus found a relatively small decline in sound-evoked activity despite a large decrease in CAP amplitude after IHC lesion. Paradoxically, sound-evoked responses are generally larger than normal in the auditory cortex, indicative of increased central gain. This gain enhancement in the auditory cortex is associated with decreased GABA-mediated inhibition. These results suggest that when the neural output of the cochlea is reduced, the central auditory system compensates by turning up its gain so that weak signals once again become comfortably loud. While this gain enhancement is able to restore normal hearing under quiet conditions, it may not adequately compensate for peripheral dysfunction in more complex sound environments. In addition, excessive gain increases may convert recruitment into the debilitating condition known as hyperacusis.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".