Spatial separation between two sounds affects the timing of action potentials elicited by the sounds in the rat's auditory midbrain neurons
Bibliographic record
Abstract
Timing of action potentials (i.e., spikes) elicited by sounds is used by auditory neurons to encode and process acoustic information. In the presence of multiple sounds, the timing of sound-driven spikes is dependent on the temporal, spectral, and spatial relationships among the sounds. We used two tone bursts with different frequencies to form a train of stimuli that were presented at a random odor and a constant rate. Such a train was used to mimic two competing sounds that occurred at the same (50%) probability or a novel sound (i.e., a low probability oddball sound) that was interleaved with a frequently occurring background sound (i.e., a high probability standard sound). We used the rat as an animal model to study how the spatial relationship between two sounds affected the timing of spikes elicited by the sounds in individual neurons in the auditory midbrain. Results indicate that a lower probability of sound presentation led to a higher temporal precision of the timing of the first spike elicited by the sound and the timing could be affected by a spatial separation between two sounds. These results are important for understanding neural mechanisms responsible for hearing in a natural acoustic environment.
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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 | 0.001 | 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".