Expansion of the Functional Border of the Audiovisual Cortex Following Partial Hearing Loss in Adulthood
Bibliographic record
Abstract
Following damage to a major sense (e.g., hearing loss), crossmodal plasticity occurs whereby there is an increased responsiveness in the deprived cortex to the remaining, intact senses. Using a rat model and single‐unit electrophysiological recordings, our recent studies on hearing‐impaired animals have revealed that crossmodal plasticity is not restricted to the core auditory cortex; higher‐order auditory regions as well as visual and audiovisual cortices show differential effects following noise‐induced hearing loss. To our surprise, the cortical area showing the greatest relative degree of multisensory convergence transitioned away from the normal audiovisual area toward a neighboring, predominantly auditory area. Thus, our collective results suggest that crossmodal plasticity induced by adult‐onset hearing impairment manifests in higher‐order cortical areas as an expansion in the functional border of the audiovisual cortex. Our ongoing studies seek to determine the implications of this crossmodal plasticity on the rats' ability to perceive the precise timing of audiovisual stimuli using novel behavioral tasks that are consistent with studies of perceptual judgement in humans. Support or Funding Information Support provided by an NSERC Discovery Grant
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 | 0.000 |
| 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 | 0.000 |
| 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".