Encoding of Sound Localization Cues by an Identified Auditory Interneuron: Effects of Stimulus Temporal Pattern
Bibliographic record
Abstract
An important cue for sound localization is binaural comparison of stimulus intensity. Two features of neuronal responses, response strength, i.e., spike count and/or rate, and response latency, vary with stimulus intensity, and binaural comparison of either or both might underlie localization. Previous studies at the receptor-neuron level showed that these response features are affected by the stimulus temporal pattern. When sounds are repeated rapidly, as occurs in many natural sounds, response strength decreases and latency increases, resulting in altered coding of localization cues. In this study we analyze binaural cues for sound localization at the level of an identified pair of interneurons (the left and right AN2) in the cricket auditory system, with emphasis on the effects of stimulus temporal pattern on binaural response differences. AN2 spike count decreases with rapidly repeated stimulation and latency increases. Both effects depend on stimulus intensity. Because of the difference in intensity at the two ears, binaural differences in spike count and latency change as stimulation continues. The binaural difference in spike count decreases, whereas the difference in latency increases. The proportional changes in response strength and in latency are greater at the interneuron level than at the receptor level, suggesting that factors in addition to decrement of receptor responses are involved. Intracellular recordings reveal that a slowly building, long-lasting hyperpolarization is established in AN2. At the same time, the level of depolarization reached during the excitatory postsynaptic potential (EPSP) resulting from each sound stimulus decreases. Neither these effects on membrane potential nor the changes in spiking response are accounted for by contralateral inhibition. Based on comparison of our results with earlier behavioral experiments, it is unlikely that crickets use the binaural difference in latency of AN2 responses as the main cue for determining sound direction, leaving the difference in response strength, i.e., spike count and/or rate, as the most likely candidate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".