The influence of magnocellular and parvocellular visual information on global processing in White and Asian populations
Bibliographic record
Abstract
Humans have the remarkable ability to efficiently group elements of a scene together to form a global whole. However, cross-cultural comparisons show that East Asian individuals process scenes more globally than White individuals. This experiment presents new insights into global processing, revealing the relative contributions of two types of visual cells in mediating global and local visual processing in these two groups. Participants completed the Navon hierarchical letters task under divided-attention conditions, indicating whether a target letter "H" was present in the stimuli. Stimuli were either 'unbiased', displayed as black letters on a grey screen, or biased to predominantly process low spatial frequency information using psychophysical thresholds that converted unbiased stimuli into achromatic magnocellular-biased stimuli and red-green isoluminant parvocellular-biased stimuli. White participants processed stimuli more globally than Asian participants when low spatial frequency information was conveyed via the parvocellular pathway, while Asian participants showed a global processing advantage when low spatial frequency information was conveyed via the magnocellular pathway, and to a lesser extent through the parvocellular pathway. These findings suggest that the means by which a global processing bias is achieved depends on the subcortical pathway through which visual information is transmitted, and provides a deeper understanding of the relationship between global/local processing, subcortical pathways and spatial frequencies.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".