Excitation-inhibition imbalance in the auditory cortex causes sound recognition impairment in noisy environment in hidden hearing loss mice
Bibliographic record
Abstract
Noise–induced hidden hearing loss (HHL) is a type of hearing dysfunction caused by moderate noise exposure. It is clinically manifested as speech recognition impairment in noisy environments while the hearing threshold remains within the normal range. The mechanism by which noise exposure causes speech recognition impairment remains unclear. This study aimed to investigate the excitation–inhibition status in the auditory cortex of HHL mice and its roles in sound recognition disability in noisy environments. A model of HHL in mice was induced using 110 decibels (dB) of helicopter noise for 2 h, the sound recognition–avoidance decision (SRAD) behavioral test was used to evaluate sound recognition ability. The activation level of excitatory neurons and the expression of vesicular glutamate transporter 1 (VGluT1) and glutamate decarboxylase 67 (GAD67) in the auditory cortex were observed. Mice were administered α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor antagonist NBQX. The results showed increased cFos expression in the auditory cortex of HHL mice and an upregulated ratio of activated CaMKⅡ + neurons. Furthermore, the expression of VGluT1 and GAD67 increased in an imbalanced manner under an 80 dB noise stimulus for 2 h. The SRAD behavioral tests showed the HHL mice maintained normal sound recognition ability under quiet conditions but not in a noisy environment. The NBQX treatment improved sound recognition but did not restore normal status. This study suggested that the excitation–inhibition imbalance in the auditory cortex of mice with HHL might be the direct cause of sound recognition disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".