Cortical tonotopic map reorganization and its implications for treatment of tinnitus
Bibliographic record
Abstract
CONCLUSION: There appears to be a definite link between reorganization of the cortical tonotopic map and increased spontaneous firing rates. The results have implications for the reduction of noise-induced hearing loss and in the prevention of noise-induced tinnitus in humans. OBJECTIVES: To review animal and human studies related to neural correlates of tinnitus. Among those are increased spontaneous firing rate, enhanced neural synchrony, and reorganization of the cortical frequency-place (tonotopic) map. MATERIALS AND METHODS: To separate these issues one would want to have a situation where hearing loss is present but without reorganization of the cortical frequency-place map. For that purpose, noise-exposed cats were placed, immediately after the trauma and for at least 3 weeks, either in a quiet or in a high-frequency or low-frequency enriched acoustic environment. RESULTS: In exposed cats that were placed in the quiet environment there was an increase in spontaneous firing rate and synchrony of neurons in primary auditory cortex. In contrast, exposed cats placed in the high-frequency-enriched acoustic environment did not show any significant difference in spontaneous firing rate or synchrony compared to the non-traumatized controls.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".