Practice with inverted faces selectively increases the use of horizontal information
Bibliographic record
Abstract
Perceptual learning improves face recognition, and learning is highly specific and long-lasting (Hussain et al., Psych Sci 2011). Even inverted faces can benefit from learning (Hussain et al., Vis Res 2009). But what changes in our representations of faces with learning? Last year, we demonstrated that the preferential use of horizontal information ("horizontal tuning") is correlated with upright face identification accuracy and the size of the face inversion effect (Pachai et al., VSS 2011). In the current study, we asked whether perceptual learning for faces is associated with an increase in horizontal tuning. Specifically, we tested inverted faces in a 10AFC identification paradigm where stimuli were the average of 10 faces viewed through different filters. Information from the target face alone was visible only within orientation bandwidths ranging from 10 degrees to 180 degrees (full-face) in 10 degree steps, centred around horizontal or vertical. In the first session, observers completed 10 trials in each condition to measure initial horizontal tuning. In the following three sessions, observers completed 300 trials/session of full-face identification. The fifth session was identical to the first. Observers returned 3-5 days later to assess maintenance of learning and transfer of learning to a new face set. As expected, training significantly improved inverted full-face identification. Critically, training also improved accuracy for faces with narrow-band filters centred on horizontal, but not vertical, suggesting an increase in horizontal tuning. Tuning was maintained in the follow-up session, but did not transfer to novel faces. These results suggest that perceptual learning improves horizontal tuning for trained face stimuli while improving overall identification accuracy, further implicating the importance of horizontal information for accurate face identification regardless of picture-plane orientation, and suggesting that the relatively high efficiency of processing horizontal information for upright faces may be a result of learning across the lifespan. Meeting abstract presented at VSS 2012
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".