Monaural and Binaural Inhibition Underlying Duration-Tuned Neurons in the Inferior Colliculus
Bibliographic record
Abstract
Duration-tuned neurons (DTNs) in the mammalian inferior colliculus (IC) arise from a combination of excitatory and inhibitory synaptic inputs. Previous research has shown that the inhibition responsible for creating DTNs has a shorter latency than that of excitation and lasts longer than the stimulus duration. We used monotic and dichotic paired tone stimulation and recorded responses of DTNs from the IC of the bat to assess the relative contributions of each ear in forming duration-tuned circuits. The stimulus consisted of a short best duration (BD) excitatory tone and a longer duration nonexcitatory (NE) tone. In the monotic condition, when the BD and NE tones were presented to the contralateral ear and were sufficiently close in time, the NE tone always suppressed spikes evoked by the BD tone. In the dichotic condition, when the BD tone was presented to the contralateral ear and the NE tone to the ipsilateral ear, half of DTNs no longer showed spike suppression to the NE tone. Of those DTNs with suppression in both conditions, the latency of the inhibition was shorter and the duration of the inhibition was longer in the monotic condition. Therefore, in the monotic condition, DTNs received a contralaterally evoked inhibitory input that preceded the excitatory input to the same neuron. In the dichotic condition, DTNs received an ipsilaterally evoked inhibitory input that was weaker, longer in latency, and shorter in duration than the inputs from the contralateral ear. These findings indicate that the neural mechanisms that create DTNs in the IC are monaural.
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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".