Dichotic sound localization properties of duration-tuned neurons in the inferior colliculus of the big brown bat
Bibliographic record
Abstract
Electrophysiological studies on duration-tuned neurons (DTNs) from the mammalian auditory midbrain have typically evoked spiking responses from these cells using monaural or free-field acoustic stimulation focused on the contralateral ear, with fewer studies devoted to examining the electrophysiological properties of duration tuning using binaural stimulation. Because the inferior colliculus (IC) receives convergent inputs from lower brainstem auditory nuclei that process sounds from each ear, many midbrain neurons have responses shaped by binaural interactions and are selective to binaural cues important for sound localization. In this study, we used dichotic stimulation to vary interaural level difference (ILD) and interaural time difference (ITD) acoustic cues and explore the binaural interactions and response properties of DTNs and non-DTNs from the IC of the big brown bat (Eptesicus fuscus). Our results reveal that both DTNs and non-DTNs can have responses selective to binaural stimulation, with a majority of IC neurons showing some type of ILD selectivity, fewer cells showing ITD selectivity, and a number of neurons showing both ILD and ITD selectivity. This study provides the first demonstration that the temporally selective responses of DTNs from the vertebrate auditory midbrain can be selective to binaural cues used for sound localization in addition to having spiking responses that are selective for stimulus frequency, amplitude, and duration.
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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".