Ethanol-induced changes in Westheimer functions consistent with decreases in lateral inhibition
Bibliographic record
Abstract
Several studies have shown that alcohol modifies inhibitory neural interactions. We used the visual system as a model to determine the possible perceptual consequences of alcohol-induced reductions in inhibition. The rationale is as follows: if alcohol reduces lateral inhibition, then any visual phenomena that rely on such inhibition should show characteristic and predictable changes. We have already shown changes consistent with reduced inhibition in simultaneous contrast and the Hermann Grid Illusion. In the present studies we extended this logic to the Westheimer paradigm. The shape of Westheimer functions is assumed to depend on the relative contribution of the inhibitory surround in centre-surround receptive fields. We obtained these functions under two conditions: 1. consumption of sufficient alcohol to raise subjects' BAC to .08%; 2.consumption of an equivalent volume of fruit juice. Subjects were required to detect a 0.02 s target flash superimposed on a luminance pedestal of varying diameter. The pedestal was superimposed on a background field whose luminance was set 1 log unit beneath that of the pedestal. Functions were obtained on backgrounds that were photopic (0.5 cd m−2), mesopic (0.05 cd m−2), and scotopic (0.005 cd m−2). We predicted that if ethanol reduced lateral inhibition, increment thresholds in the photopic and mesopic conditions should be increased at pedestal diameters within the sensitization and plateau portions of the Westheimer function. Because dark adaptation has been shown to eliminate lateral inhibition, we also predicted that the scotopic Westheimer function should be unaffected. Changes consistent with this prediction were obtained in each condition.
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 | 0.000 |
| 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".