Projections from the medial geniculate body to primary auditory cortex in neonatally deafened cats
Bibliographic record
Abstract
In the present study, anatomical projections from the medial geniculate body (MGB) to primary auditory cortex (AI) were investigated in normal adult cats and in animals that were neonatally deafened with the ototoxic drug amikacin. Cochleotopic/tonotopic maps in AI (based on neural response characteristic frequency) were obtained with microelectrode recording techniques, and single or multiple injections of retrograde tracers (horseradish peroxidase and fluorescent dyes) were introduced into AI. The AI maps of the amikacin-treated cats had an abnormal cochleotopic organization, such that deprived cortical areas exhibited an expanded representation of intact regions of the damaged cochlea. However, retrograde tracer injections into different regions of AI produced a normal pattern of labeling in the ventral division of the medial geniculate body (MGBv). In both experimental and control animals, the main mass of labeled thalamic cells was found in the MGBv. Different isofrequency contours in AI receive input from different portions of the MGBv. Thus, cell arrays labeled by anterior AI injections were situated medially in MGBv, and injections into posterior AI labeled MGBv more laterally. Furthermore, the deafened cats did not develop a more divergent thalamocortical projection compared with normal control animals, indicating that an abnormal spread of the thalamocortical afferents across the frequency domain in AI (anterior-posterior axis) is not responsible for the altered cochleotopic map in these neonatally deafened animals. The relatively normal thalamocortical projection pattern suggests that, after neonatal cochlear lesions, the major reorganization of cochleotopic maps occurs at subthalamic levels.
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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 | 0.001 | 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) | 0.001 | 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".