Modulating ocular dominance in the adult in real time.
Bibliographic record
Abstract
Using a dichoptic spatial phase combination paradigm that assesses the relative contribution that each eye makes to the binocular percept (ocular dominance), we have shown previously that 2.5 hours of patching, be it opaque or translucent, can result in a short-term enhancement of the patched eye’s contribution to binocularity. This suggests that it is differential pattern deprivation, rather than the differential luminance deprivation that is driving this ocular dominance change. Here we ask what aspects of the pattern stimulation are important for ocular dominance. Observers dichoptically viewed movies of 2-3 hrs duration in which the spatial information in one eye’s view had been altered (pattern deprivation). We measured each eye’s contribution to the binocular percept before and after movie viewing using the dichoptic spatial phase task. Scrambling the spatial phases in one eye’s view had no effect on ocular dominance, suggesting features constructed from phase-aligned components are unimportant in this regard. At the level at which these changes in dominance occurs only the Fourier amplitude spectrum is important. To verify this we show that graded changes to the magnitude of the amplitude spectrum result in graded changes in ocular dominance. To ascertain whether different parts of the amplitude spectrum are more important than others, we compared highpass with lowpass filtering and show that only the latter affects dominance. Finally, the ocular dominance change is not orientationally-dependent, suggesting the underlying mechanism is isotropic. Short-term changes in ocular dominance in adults can be obtained by altering the contrast of isotropic, high spatial frequency components seen by one eye. Meeting abstract presented at VSS 2015
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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) | 0.002 | 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".