The word length effect in virtual hemianopia, real hemianopia, and alexia
Bibliographic record
Abstract
Background: A characteristic feature of pure alexia is the word-length effect, in which reading speed increases with increasing word length. However, many alexic patients also have right hemianopia, which can itself can cause a hemianopic dyslexia. The degree to which hemianopia causes a word-length effect is therefore an important question. Objective: Our goal was to determine if a word-length effect could be generated under hemianopic conditions in the absence of damage to language processing areas. Method: 13 healthy adults read single words of 3 to 9 letters in length while eye movements were monitored with full-field viewing and then with gaze-contingent displays simulating right or left hemianopia. We also studied 6 patients with reading problems: two had hemianopic dyslexia without fusiform lesions, four had fusiform lesions causing alexia, two of which had associated hemianopia while two had full visual fields. Results: In healthy subjects, there was a small word-length effect with full-field viewing of 14ms/letter, which more than doubled to 37 ms/letter for right and 31ms/letter for left hemianopia. The upper 95% prediction limit was 51 ms/letter for full-field viewing and 160 ms/letter for right hemianopia. These results were corroborated by our patient sample. Our two patients with hemianopic dyslexia fell within the virtual hemianopic range (18.9, 95.1 ms/letter), while the two patients with fusiform lesions causing alexia and hemianopia had word-length effects well beyond this range (1536, 16500 ms/letter). The subjects with alexia without hemianopia had modest word-length effects that were abnormal compared to full-field viewing (53, 182 ms/letter). Conclusions: Hemianopic simulations show a small word-length effect of up to 160 ms/letter. Given that word-length effects of similar magnitude can be seen in alexia without hemianopia, in patients with hemifield loss in the central 5°, word-length effects should be larger before concluding that there is an additional component of alexia.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".