Hysteresis effects in stereopsis and binocular rivalry
Bibliographic record
Abstract
Neural hysteresis plays a fundamental role in stereopsis and reveals the existence of positive feedback at the cortical level (Wilson & Cowan, 1972). Using a model of cortical dynamics, we predicted that it should be possible to measure hysteresis as a function of orientation disparity in tilted gratings in which a transition is perceived between stereopsis and binocular rivalry. Methods. The patterns were 2 cpd or 4 cpd sinewave gratings with orientation disparities (0–40 deg) resulting in various degrees of tilt. A sequence of 40 pattern pairs was used, with the orientation disparity increased by a fixed increment in successive pairs. During each experimental trial a movie of the 40 pairs was shown at a rate of 0.5, 1 or 2 pairs per second. In separate trials the same movie was shown in reverse order. Two transition points were measured: the point at which the single tilted grating broke into two rivalrous gratings (T1), and the point at which the two rivalrous gratings merged into a single tilted grating (T2). Results. Transitions occurred at different orientation disparities (T1=24.7 deg, T2=17.8 deg at 2 cpd; T1=27.1 deg, T2=18.0 deg at 4 cpd) corresponding to a timing difference of 3.5–4.6 sec. This was consistent with hysteresis and far exceeded the effects which could be attributed to reaction time or adaptation. The results are consistent with a cortical model with positive feedback arising from recurrent inhibition between binocular units coding different disparities and orientations. Stereopsis and rivalry are two possible states of the network.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".