Mechanisms of frequency-specific responses of ω neuron 1 in crickets (<i>Teleogryllus oceanicus</i>): a polysynaptic pathway for song?
Bibliographic record
Abstract
In crickets (Teleogryllus oceanicus), the auditory interneuron omega neuron 1 (ON1) responds to sounds over a wide range of frequencies but is most sensitive to the frequency of conspecific songs (4.5 kHz). Response latency is longest for this same frequency. We investigate the mechanisms that might account for the longer latency of ON1 to cricket-like sounds. Intracellular recordings revealed no evidence for appropriately timed postsynaptic inhibition of ON1 that might increase its latency, nor was latency affected by picrotoxin. The onset of excitatory postsynaptic potentials (EPSPs) was delayed for 4.5 kHz stimuli compared with ultrasound stimuli, pointing to a presynaptic locus for the latency difference. When ON1 is stimulated with high frequencies, discrete, apparently unitary EPSPs can be recorded in its dendrite, and these are latency-locked to spikes recorded simultaneously in the auditory nerve. This suggests that input to ON1 from high-frequency-tuned auditory receptor neurons is monosynaptic. In agreement with this, brief ultrasound stimuli evoke a single, short-latency EPSP in ON1. In contrast, the EPSP evoked by a brief 4.5 kHz stimulus consists of an early component, similar in latency to that evoked by ultrasound and possibly evoked by ultrasound-tuned receptors, and a later, dominant component. We interpret the early peak as arising from a monosynaptic afferent pathway and the late peak from a polysynaptic afferent pathway. Multiple-peak EPSPs, with timing similar to those evoked by sound stimuli, were also evoked by electrical stimulation of the auditory nerve.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".