Spatial separation between two sounds affects first-spike latencies of responses elicited by the sounds in the rat’s auditory midbrain neurons
Bibliographic record
Abstract
The first-spike latency (FSL) is an important temporal characteristic of a neurophysiological response. We study the FSLs of sound-driven responses in individual neurons in the rat’s auditory midbrain. Responses were elicited by a train of stimuli created using multiple presentations of two tone bursts with different frequencies. Presentations of the two sounds were interleaved temporally in a random order. We found that the mean and the temporal variation of FSL of the response elicited by a sound was increased when the sound was presented more frequently or when it was moved from the ear that drove an excitatory response to the ear that drove an inhibitory effect. Furthermore, the FSL of response to one sound was dependent on the spatial location of the other sound. Results suggested that the timing of the first spike could be used by midbrain neurons to encode information related to the probability of occurrence and spatial location of a sound. It could also be used to gauge how the sound was related to the other sound in spatial location. These results enhance our understanding of neural bases of binaural hearing, especially in an environment with temporally separated competing sounds.
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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) | 0.000 | 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 | 0.001 |
| 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".