Layer-specific enhancement of visual-evoked activity in the audiovisual cortex following a mild degree of hearing loss in adult rats
Bibliographic record
Abstract
Following adult-onset hearing impairment, crossmodal plasticity can occur within various sensory cortices, often characterized by increased neural responses to visual stimulation in not only the auditory cortex, but also in the visual and audiovisual cortices. In the present study, we used an established model of loud noise exposure in rats to examine, for the first time, whether the crossmodal plasticity in the audiovisual cortex that occurs following a relatively mild degree of hearing loss emerges solely from altered intracortical processing or if thalamocortical changes also contribute to the crossmodal effects. Using a combination of an established pharmacological 'cortical silencing' protocol and current source density analysis of the laminar activity recorded across the layers of the audiovisual cortex (i.e., the lateral extrastriate visual cortex, V2L), we observed layer-specific changes post-silencing in the strength of the residual visual, but not auditory, input in the noise exposed rats with mild hearing loss compared to rats with normal hearing. Furthermore, based on a comparison of the laminar profiles pre- versus post-silencing in both groups, we can conclude that noise exposure caused a re-allocation of the strength of visual inputs across the layers of the V2L cortex, including enhanced visual-evoked activity in the granular layer; findings consistent with thalamocortical plasticity. Finally, we confirmed that audiovisual integration within the V2L cortex depends on intact processing within intracortical circuits, and that this form of multisensory processing is vulnerable to disruption by noise-induced hearing loss. Ultimately, the present study furthers our understanding of the contribution of intracortical and thalamocortical processing to crossmodal plasticity as well as to audiovisual integration under both normal and mildly-impaired hearing conditions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".