Quantifying connectivity to auditory cortex: Implications for crossmodal plasticity and hearing restoration
Bibliographic record
Abstract
When one sensory modality is lost, compensatory advantages are observed in the remaining senses. There is evidence to suggest these advantages reflect recruitment of cortical areas that normally process sound. In the cat, crossmodal reorganization of auditory cortex appears to be field specific. While little or no activity is evoked in primary cortical regions by visual and somatosensory stimulation, higher-level fields confer increased peripheral acuity and improved visual motion detection. In order to better understand the changes in neural connections that underscore these functional adaptations, we have undertaken a series of detailed anatomical studies aimed at quantifying and comparing the patterns of connectivity in hearing and deaf animals. A retrograde neuronal tracer was deposited into auditory cortical areas, coronal sections were taken, and neurons showing positive retrograde labeling were counted and assigned to cortical and thalamic areas. Projections within and between sensory modalities were quantified; while some small-scale differences emerge, patterns of connectivity are overwhelmingly preserved across experimental groups within each cortical field examined. This structural preservation has implications for our understanding of the mechanisms that underlie crossmodal reorganization; moreover, it suggests that the connectivity necessary for resumption of auditory function may withstand even lengthy periods of deprivation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".