Glutamatergic and GABAergic Regulation of Neural Responses in Inferior Colliculus to Amplitude-Modulated Sounds
Bibliographic record
Abstract
Recordings were made from single neurons in the rat inferior colliculus in response to sinusoidally amplitude-modulated sounds (10-s duration) presented to the contralateral ear. Neural responses were determined for different rates of modulation (0.5 Hz to 1 kHz) at a depth of 100%, and modulation transfer functions were generated based on firing rate (MTFFR) and vector strength (MTFVS). The effects of AMPA, NMDA, and GABAA receptor antagonists were examined by releasing drugs iontophoretically through a multibarrel pipette attached to a single-barrel recording pipette. Both the AMPA receptor antagonist, 1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo[f]quinoxaline-7-sulfonamide disodium (NBQX), and the NMDA receptor antagonist, (+/-)-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP) resulted in a decrease in firing rate, and the GABAA receptor antagonist, bicuculline, produced an increase in the firing rate in most of the cells examined. In some cases, the shape of the MTFFR was modified slightly by receptor antagonists, but in most cases, the peak firing rate that determined a neuron's best modulation frequency remained the same. Also there were no changes during delivery of either excitatory or inhibitory antagonists in the maximum response synchrony at the peak of the MTFVS although some changes were noticed at off-peak modulation rates particularly with the AMPA receptor antagonist, NBQX.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".