Psychophysical evidence for impaired Magno, Parvo, and Konio-cellular pathways in dyslexic children
Bibliographic record
Abstract
PURPOSE: Dyslexia is one of the most common learning disabilities affecting millions of people worldwide. Although exact causes of dyslexia are not well-known, a deficit in the magnocellular pathway may play a role. We examined possible deficiency of magnocellular, as compared to parvocellular and koniocellular pathway function by measuring luminance and color perception. METHODS: Visual stimuli consisted of a series of natural images, divided into layers of luminance, red-green and blue-yellow, which probed magnocellular, parvocellular, and koniocellular pathways, respectively. Thirteen children with dyslexia and 13 sex- and age- matched controls performed three psychophysical tasks. In the first task, subjects were instructed to match the contrast of luminance (magno) and red-green (parvo) images to that of the blue-yellow (konio) images. In the second task, subjects detected the isoluminant point of red-green images to probe parvocellular pathway. In the third task, temporal processing was assessed by measuring reaction time and percentage of correct responses in an identification task using four categories of images, activating all three pathways. RESULTS: The dyslexic group had significantly elevated luminance and color contrast thresholds and higher isoluminant point ratio in comparison to the control group. Furthermore, they had significantly less correct responses than the control group for the blue-yellow images. CONCLUSION: We may suggest that dyslexic subjects might suffer from both magnocellular and parvocellular deficits. Moreover, our results show partial impairment of the koniocellular pathway. Thus, dyslexia might be associated with deficits in all three visual pathways.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".