Reading words and seeing style: The neuropsychology of word, font and handwriting perception
Bibliographic record
Abstract
Reading is considered to be primarily a function of the left hemisphere. However, it is also possible to process text for attributes other than the identity of words and letters, such as the style of font or handwriting. Older anecdotal observations have suggested that processing of handwriting style may involve the right hemisphere. There is also some fMRI evidence of sensitivity to style in either right or left visual word form areas in the fusiform gyri. We created a test that, using the same set of text stimuli, required subjects first to sort text on the basis of word identity and second to sort text on the basis of script style. We presented two versions, one using various computer fonts and the other using the handwriting of different individuals, and measured accuracy and completion times. For testing we selected four subjects with unilateral fusiform lesions and problems with object processing who had been well characterized by neuropsychological testing and structural and/or functional MRI. We found that one alexic subject with left fusiform damage performed well when sorting by script style but had markedly prolonged reading times when sorting by word identity. In contrast, two prosopagnosic subjects with right lateral fusiform damage that eliminated the fusiform face area and likely the right visual word form area were impaired in sorting for script style, but performed better when sorting for word identity. Another prosopagnosic subject with right medial occipitotemporal damage sparing areas in the lateral fusiform gyrus performed well on both tasks. The contrast in the performance of patients with right versus left fusiform damage suggests an important distinction in hemispheric processing that reflects not the type of stimulus but the nature of the processing operations required.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".