Individual differences in visual lexical decision are highly correlated with orientation tuning
Bibliographic record
Abstract
Recent research has brought attention to the importance of the orientation tuning of visual information. For instance, in face recognition, participants show higher efficiency for horizontal information (e.g. Pachai, Sekuler & Bennett, 2013). Here, we investigated whether this also applies to visual word recognition. Fifteen participants performed a lexical decision task. Each trial began with a fixation cross displayed for 500ms, immediately followed by a stimulus (about 2 degrees of visual angle) that remained on screen until response. The stimuli consisted of 300 high lexical frequency five-letter French words and 300 pseudo-words, which we generated by replacing one letter in each word (either the second, third, or fourth). Fast Fourier Transforms of stimuli were performed to preserve only vertical or horizontal information. Gaussian white noise was added to the reconstructed output to maintain performance at 75% in each condition. The threshold was estimated using QUEST (Watson & Pelli, 1983). Efficiency was calculated for each condition by comparing human performance with that of an ideal (template-matching) observer. Both the human and the ideal observers needed less signal for vertical compared to horizontal information. However, the ideal to human ratios show that, at the group level, experienced readers have similar efficiency for both orientations, (Mvertical= .0112, Mhorizontal= .0113, t(14)= -.09, ns). To better characterize orientation tuning, we correlated efficiency with reading speed; this was measured in another lexical decision task using 100 unaltered stimuli (50 words). Interestingly, we found that reaction times are strongly correlated with the difference between horizontal and vertical efficiency (r= -.6, p<.05). Our results suggest that faster readers perform better with horizontal than vertical information, while the reverse holds for slower readers. Further investigation on the issue should examine the possible link between individual differences and sensitivity to crowding, as vertical information appears to constrain its spread. Meeting abstract presented at VSS 2014
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".