Forward modelling reveals dynamics of neural orientation tuning to unconscious visual stimuli during binocular rivalry
Bibliographic record
Abstract
Abstract When different visual stimuli are presented to the two eyes, they typically compete for access to conscious perception, a phenomenon known as binocular rivalry . Previous studies of binocular rivalry have shown that neural responses to consciously suppressed stimuli are markedly diminished in magnitude, though they may still be encoded to some extent. Here we employed multivariate forward modelling of human electroencephalography (EEG) data to quantify orientation-selective responses to visual gratings during binocular rivalry. We found robust orientation tuning to both conscious and unconscious gratings. This tuning was enhanced for the suppressed stimulus well before it was available for conscious report. The same pattern was evident in the overall magnitude of neural responses, and it emerged even earlier than the changes in neural tuning. Taken together, our findings suggest that rivalry suppression affects broadband, non-orientation selective aspects of neural activity before refining fine-grained feature-selective information.
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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 | 0.001 |
| 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".