Dichoptic imbalance of luminance and its effects on the phase component of steady-state EEG signals
Bibliographic record
Abstract
A neutral density (ND) filter placed before one eye will produce a dichoptic imbalance in luminance, which attenuates responses to visual stimuli and generates a lag in neural signals from retina to cortex in the filtered eye (Wilson & Anstis, 1969, Am J Psychol, 82, 350-358). This, in turn, can induce disparity cues that lead to an illusory percept of depth (e.g., the Pulfrich effect). Here, we explored how the increased latency of the filtered eye alters neural responses to stimuli presented either monocularly or binocularly. We measured steady-state (SSVEPs) contrast response functions from the occipital pole at 6 different contrast values (0 to 96%) with 3 cycles/° sinusoidal gratings flickering at 5 Hz. To manipulate the balance of luminance between the eyes, neutral density filters (0.6, 1.2, and 1.8 ND) were placed in front of the dominant eye of observers while stimuli were presented at maximum contrast either to the filtered eye or to both eyes. The amplitude component of SSVEPs increased monotonically as a function of stimulus contrast and decreased as a function of filter strength in both monocular and binocular viewing conditions. For monocular stimuli, the ND filter increased the lag of the phase component of SSVEPs, up to a latency of 63 ms (95%CI +/- 31ms) at a filter of 1.8 ND. However, under binocular conditions, no apparent phase lag in the SSVEPs could be identified. This is indicative of a binocular combination process that suppresses the lagged input from the filtered eye. We explain these data with a computational model that implements a variable temporal impulse response function placed prior to a binocular contrast gain control mechanism, which, under binocular viewing conditions, suppresses the attenuated and lagged responses of the filtered eye. This model, additionally, offers insight on interocular interactions that may occur in amblyopia. Meeting abstract presented at VSS 2016
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 | 0.001 |
| 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".