Effects of oscillation phase on discrimination performance in a visual tilt illusion
Bibliographic record
Abstract
Summary Neural oscillations reflect fluctuations in the relative excitation/inhibition of neural systems 1–5 and are theorised to play a critical role in several canonical neural computations 6–9 and cognitive processes 10–14 . These theories have been supported by findings that detection of visual stimuli fluctuates with the phase of oscillations at the time of stimulus onset 15–23 . However, null results have emerged in studies seeking to demonstrate these effects in visual discrimination tasks 24–27 , raising questions about the generalisability of these phenomena to wider neural processes. Recently, we suggested that methodological limitations may mask effects of oscillation phase in higher-level sensory processing 28 . Thus, to test the generality of phasic influences requires a task that requires stimulus discrimination but depends on early sensory processing. Here, we examined the influence of oscillation phase in the visual tilt illusion, in which an oriented centre grating is perceived titled away from the orientation of a surround grating 29 . This illusion is produced by lateral inhibitory interactions in early visual processing 30–32 . We presented centre gratings at participants’ titrated subjective vertical angle and had participants report whether the grating appeared tilted leftward or rightward of vertical on each trial while measuring their brain activity with EEG. We observed a robust fluctuation in orientation perception across different phases of posterior alpha and theta oscillations, consistent with fluctuating illusion magnitude across the oscillatory cycle. These results confirm that oscillation phase affects complex processing involved in stimulus discrimination, consistent with their purported role in canonical computations that underpin cognition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".