Peripheral GABAergic inhibition of spider mechanosensory afferents
Bibliographic record
Abstract
Spider mechanosensory neurons receive an extensive network of efferent synapses onto their sensory dendrites, somata and distal axonal regions. The function of these synapses is unknown. Peripheral synapses are also found on crustacean stretch-receptor neurons but not on mechanosensory afferents of other species, although inhibitory GABAergic synapses are a common feature of centrally located axon terminals. Here we investigated the effects of GABA receptor agonists and antagonists on one group of spider mechanosensory neurons, the slit sense organ VS-3, which are accessible to current- and voltage-clamp recordings. Bath application of GABA activated an inward current that depolarized the membrane and increased the membrane conductance leading to impulse inhibition. VS-3 neuron GABA receptors were activated by muscimol and inhibited by picrotoxin but not bicuculline, and their dose-response relationship had an EC(50) of 103.4 microm, features typical for insect ionotropic GABA receptors. Voltage- and current-clamp analysis confirmed that, while the Na(+) channel inhibition resulting from depolarization can lead to impulse inhibition, the increase in membrane conductance (i.e. 'shunting') completely inhibited impulse propagation. This result argues against previous findings from other preparations that GABA-mediated inhibition is caused by a depolarization that inactivates Na(+) conductance, and it supports those findings that assign this role to membrane shunting. Our results show that GABA can rapidly and selectively inhibit specific mechanoreceptors in the periphery. This type of peripheral inhibition may provide spiders with a mechanism for distinguishing between signals from potential prey, predators or mates, and responding with appropriate behaviour to each signal.
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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) | 0.001 | 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".