Subthreshold Membrane Conductances Enhance Directional Selectivity in Vertebrate Sensory Neurons
Bibliographic record
Abstract
Directional selectivity, in which neurons respond preferentially to one "preferred" direction of movement over the opposite "null" direction, is a critical computation that is found in the central nervous systems of many animals. Such responses are generated using two mechanisms: spatiotemporal convergence via pathways that differ in the timing of information from different locations on the receptor array and the nonlinear integration of this information. Previous studies have showed that various mechanisms may act as nonlinear integrators by suppressing the response in the null direction. Here we show, through a combination of mathematical modeling and in vivo intracellular recordings, that subthreshold membrane conductances can act as a nonlinear integrator by increasing the response in the preferred direction of motion only, thereby enhancing the directional bias. Such subthreshold conductances are ubiquitous in the CNS and therefore may be used in a wide array of computations that involve the enhancement of an existing bias arising from differential spatiotemporal filtering.
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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".