Mapping Cortical Plasticity Following Noise Exposure Using c‐Fos Immunoreactivity
Bibliographic record
Abstract
Using in vivo electrophysiological recordings in rats, our lab has recently observed that high‐intensity noise exposure causes an increase in the number of neurons in the auditory and multisensory cortices that are responsive to visual stimuli (i.e., cortical crossmodal plasticity). To extend this work, the present study is evaluating our hypothesis that this noise‐induced crossmodal plasticity can also be assessed by mapping the activation of the immediate early gene, c‐Fos, across multiple cortical areas in response to visual stimuli. Adult male rats are exposed to a 120dB noise (0.8‐20kHz) for two hours, and the level of hearing loss is assessed with an auditory brainstem response (average hearing loss ~20dB). Fourteen days later, noise‐exposed rats (and age‐matched controls) were subjected to a visual stimulation protocol known to induce c‐Fos activation (200 light flashes; 1‐3 s ITI), followed by transcardial perfusion two hours post‐stimulation. Visually‐responsive neurons in the noise‐exposed rats and controls were confirmed with immunohistochemistry and fluorescent microscopy. If, as hypothesized, we observe an increase in the number of c‐Fos‐immunoreactive neurons in noise‐exposed rats, this would establish that molecular mapping represents a useful tool for studying cortical crossmodal plasticity.
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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 | 0.000 |
| 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 | 0.000 |
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".