Eccentricity, but not color contrast, influences microsaccadic prevention of visual fading
Bibliographic record
Abstract
When the eyes remain still for an extended period of time, visual boundaries can appear to fade. This illusory phenomenon is traditionally attributed to slow neuronal adaptation to stable retinal input. Microsaccades – small, mostly involuntary ocular movements during gaze fixation – counteract fading, but it is unclear exactly how. They might simply refresh the retinal image to reverse adaptation or introduce a unique visual resampling signal that interacts with adapting neural populations. To better understand boundary fading both in itself and as a probe of microsaccade function, we investigated why a stronger boundary, determined by isoluminant color contrast and eccentricity (distance from the visual field center), takes longer to fade. A stronger boundary could either create a more robust cortical signal requiring greater adaptation, and/or enhance the preventive effect of microsaccades. To test these two possibilities we recorded microsaccades during a perceptual filling-in task. Human participants fixated centrally until they experienced illusory merging of two isoluminant colored surfaces, separated by a circular ring boundary, due to perceptual boundary fading. We fit linear mixed models of trial-wise fading time to color contrast, boundary eccentricity, and fixational eye movement dynamics. While both color contrast and eccentricity altered fading time, they did so differently. Higher color contrast extended overall fading time but did not influence the efficacy of individual microsaccades. Conversely, lower eccentricity prolonged fading exclusively via eye movements. These findings demonstrate that stimulus properties can differently influence slow adaptation and microsaccadic counteraction. We propose that microsaccades prevent visual fading via transient boundary stimulation that scales with cortical magnification but is invariant to boundary contrast.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".