The Accessory Optic System Contributes to the Spatio-Temporal Tuning of Motion-Sensitive Pretectal Neurons
Bibliographic record
Abstract
The nucleus of the basal optic root (nBOR) of the accessory optic system (AOS) and the pretectal nucleus lentiformis mesencephali (LM) are involved in the analysis of optic flow that results from self-motion and are important for oculomotor control. These neurons have large receptive fields and exhibit direction selectivity to large moving stimuli. In response to drifting sine wave gratings, LM and nBOR neurons are tuned to either low spatial/high temporal frequencies (SF, TF) or high SF/low TF stimuli. Given that velocity = TF/SF, these are referred to as "fast" and "slow" neurons, respectively. There is a heavy projection from the AOS to the pretectum, although its function is unknown. We recorded the directional and spatio-temporal tuning of LM units in pigeons before and after nBOR was inactivated by tetrodotoxin injection. After nBOR inactivation, changes in direction preference were observed for only one of 18 LM units. In contrast, the spatio-temporal tuning of LM units was dramatically altered by nBOR inactivation. Two major effects were observed. First, in response to motion in the preferred direction, most (82%) neurons showed a substantially reduced (mu = -67%) excitation to low SF/high TF gratings. Second, in response to motion in the anti-preferred direction, most (63%) neurons showed a dramatically reduced (mu = -78%) inhibition to high SF/low TF gratings. Thus the projection from the nBOR contributes to the spatio-temporal tuning rather than the directional tuning of LM neurons. We propose a descriptive model whereby LM receives inhibitory and excitatory input from "slow" and "fast" nBOR neurons, respectively.
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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".