A Neural Code for Looming and Receding Motion Is Distributed over a Population of Electrosensory ON and OFF Contrast Cells
Bibliographic record
Abstract
Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. As such, contrast-detecting neurons (ON/OFF cells) are found in many sensory systems, responding respectively to increased or decreased intensity within their receptive field centers. This differential sensitivity suggests that ON and OFF cells initiate segregated streams of information for positive and negative sensory contrast. However, while recording in vivo from the ON and OFF cells of Apteronotus leptorhynchus, we report that the reversal of stimulus motion triggers paradoxical responses to electrosensory contrast. By considering the instantaneous firing rates of both ON and OFF cell populations, a bidirectionally symmetric representation of motion is achieved for both positive and negative contrast stimuli. Whereas the firing rates of the individual contrast detecting neurons convey scalar information, such as object distance, it is their sequential activation over longer timescales that track changes in the direction of movement.
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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".