Corticofugal Shaping of Frequency Tuning Curves in the Central Nucleus of the Inferior Colliculus of Mice
Bibliographic record
Abstract
Plasticity of the auditory cortex can be induced by conditioning or focal cortical stimulation. The latter was used here to measure how stimulation in the tonotopy of the mouse primary auditory cortex influences frequency tuning in the midbrain central nucleus of the inferior colliculus (ICC). Shapes of collicular frequency tuning curves (FTCs) were quantified before and after cortical activation by measuring best frequencies, FTC bandwidths at various sound levels, level tolerance, Q-values, steepness of low- and high-frequency slopes, and asymmetries. We show here that all of these measures were significantly changed by focal cortical activation. The changes were dependent not only on the relationship of physiological properties between the stimulated cortical neurons and recorded collicular neurons but also on the tuning curve class of the collicular neuron. Cortical activation assimilated collicular FTC shapes; sharp and broad FTCs were changed to the shapes comparable to those of auditory nerve fibers. Plasticity in the ICC was organized in a center (excitatory)-surround (inhibitory) way with regard to the stimulated location (i.e., the frequency) of cortical tonotopy. This ensures, together with the spatial gradients of distribution of collicular FTC shapes, a sharp spectral filtering at the core of collicular frequency-band laminae and an increase in frequency selectivity at the periphery of the laminae. Mechanisms of FTC plasticity were suggested to comprise both corticofugal and local ICC components of excitatory and inhibitory modulation leading to a temporary change of the balance between excitation and inhibition in the ICC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".