Active Signal Conduction through the Sensory Dendrite of a Spider Mechanoreceptor Neuron
Bibliographic record
Abstract
Rapid responses to sensory stimulation are crucial for survival. This must be especially true for mechanical stimuli containing temporal information, such as vibration. Sensory transduction occurs at the tips of relatively long sensory dendrites in many mechanoreceptors of both vertebrates and invertebrates, but little is known about the electrical properties of these crucial links between transduction and action potential generation. The VS-3 slit-sense organ of the spider Cupiennius salei contains bipolar mechanosensory neurons that allow voltage-clamp recording from the somata, whereas mechanotransduction occurs at the tips of 100- to 200-microm-long sensory dendrites. We studied the properties of VS-3 sensory dendrites using three approaches. Voltage-jump experiments measured the spread of voltage outward from the soma by observing total mechanically transduced charge recovered at the soma as a function of time after a voltage jump. Frequency-response measurements between pseudorandom mechanical stimulation and somatic membrane potential estimated the passive cable properties of the dendrite for voltage spread in the opposite direction. Both of these sets of data indicated that the dendritic cable would significantly attenuate and retard a passively propagated receptor potential. Finally, current-clamp observations of receptor potentials and action potentials indicated that action potentials normally start at the distal dendrites and propagate regeneratively to the soma, reducing the temporal delay of passive conduction.
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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".