Fixation stability during global motion discrimination tasks
Bibliographic record
Abstract
Introduction: Beyond the characteristic deficit in visual acuity in one eye, people with unilateral amblyopia (lazy eye) show deficits on a range of visual functions including motion perception at slow speeds. These deficits are usually attributed to the abnormal development of low-level visual motion processing mechanisms. However, unstable fixation has been reported in amblyopia, and may impact motion perception by degrading the input received by direction-selective neurons. Here we ask whether poor performance on slow motion tasks can be accounted for by poor fixation stability. To establish this relation in control observers, we assessed fixation stability in adults with healthy vision during a motion perception task. Methods: Participants (n = 24) performed a global motion direction discrimination task (left/right) with stimuli (600 ms duration) moving at a slow (1 deg/s) or fast (32 deg/s) speed. Dot coherence was controlled with a staircase procedure to obtain coherence thresholds. In a control condition, participants viewed stationary dot patterns. Participants were asked to fixate a central cross throughout the task. Eye movements were recorded with an Eyelink 1000+. Bivariate contour ellipse area and the number of microsaccades on each trial were calculated as indices of stability. Results: Fixation was more stable for the motion discrimination task at either speed, compared to stationary viewing. Participants' overall stability did not predict their coherence thresholds on the motion discrimination task for either speed. Conclusions: Healthy adults show no clear relationship between eye movement stability and global motion coherence thresholds. This suggests fixation instability may not solely account for the motion perception deficits observed in amblyopia. Meeting abstract presented at VSS 2018
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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 | 0.002 |
| 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".