Early species sensitivity of face and eye processing: an adaptation study
Bibliographic record
Abstract
The current study employed a rapid adaptation procedure to investigate the response profile of the early face-sensitive N170 ERP component to human and animal faces. Adaptors (S1) consisting of full faces, isolated eye regions and eyeless faces of humans, apes, dogs and cats were rapidly followed by a full human face as test stimulus (S2). All stimuli were equated in luminance, contrast and spatial frequencies. In response to adaptor stimuli (S1), human faces yielded significantly lower N170 amplitudes than human eyes, as classically reported, whereas no difference was found between animal eyes and faces. In response to S2 and in line with the adaptation mechanism, an attenuation of N170 amplitude was found for all types of face-related adaptors relative to house adaptors irrespective of species. Eye stimuli elicited stronger adaptation than face stimuli for humans, apes and cats, but not for dogs. These results support a differential role of eyes in early face processing for humans compared to animal species. Their significance is discussed in light of a recent model of face processing stipulating eye- and face-selective neuronal populations (Itier, 2007).
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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 | 0.000 |
| 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".