<i>Shaker</i>K<sup>+</sup>Channels Contribute Early Nonlinear Amplification to the Light Response in<i>Drosophila</i>Photoreceptors
Bibliographic record
Abstract
We describe the contribution of rapidly inactivating Shaker K+ channels to the dynamic membrane properties of Drosophila photoreceptors. Phototransduction was measured in wild-type and Shaker mutant (Sh14) Drosophila photoreceptors by stimulating with white noise-modulated light contrast and recording the resulting intracellular membrane potential fluctuations. A second-order Volterra kernel series was used to characterize the nonlinear dynamic properties of transduction in the two situations. First-order kernels were indistinguishable in wild-type and Sh14 photoreceptors, indicating that the basic light transduction machinery was always intact. However, second-order kernels of Shaker mutants lacked a large, early amplification, indicating a novel role for Shaker K+ channels in amplifying and accelerating the voltage response of wild-type photoreceptors. A cascade model of two nonlinear static components surrounding one linear dynamic component was able to partially reproduce the experimental responses. Parameters obtained by fitting the model to the experimental data supported the hypothesis that normal Shaker K+ channels contribute an early, positive nonlinearity that partially offsets a later attenuating nonlinearity caused by membrane shunting.
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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) | 0.001 | 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".