Holistic face processing induces perceptual shifts in face perception
Bibliographic record
Abstract
Numerous behavioral studies have demonstrated that face recognition depends on holistic processing, based especially on the famous composite face effect. The decline in hit rate when composite halves are aligned compared to when they are misaligned is taken to reflect interference from the whole-face configuration. However, whether this interference is due to a perceptual bias or reduced discriminative efficiency is still a matter of debate. To clarify the nature of this effect, we devised a new composite paradigm using ambiguous stimuli. We generated three series of morphed faces derived from merging pairs of celebrities. Ambiguous morphed top-halves were coupled with unmorphed bottom-halves, the two halves being aligned or misaligned. The task was to say which celebrity the ambiguous top-half most resembled. We plotted the frequency of response and response time as a function of the morphing level of the top-half and the identity of the unmorphed bottom-half. We examined whether, compared to the misaligned condition, the data in the aligned condition showed a decrease in slope of the psychophysical function, which would indicate reduced discriminative efficiency, or a change in intercept alone, which would indicate a perceptual bias. 30 healthy participants performed this task. Our results showed that the bottom-half altered responses to the top-half when faces were aligned but not when they were misaligned. More crucially, the change was due to a shift in the position of the psychophysical function (p<0.001) without a significant change in the slope of these functions. These results demonstrate that the composite illusion originates in a perceptual bias introduced from one face-half that affects the decision about the identity of the other face-half when they are aligned, and is not from decreased discriminative efficiency of judgments about that other face-half, due to reduced attention, interference, or other possible mechanisms that can degrade perception. 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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".