Image-Invariant Responses in Face-Selective Regions Do Not Explain the Perceptual Advantage for Familiar Face Recognition
Bibliographic record
Abstract
The ability to recognize familiar faces across different viewing conditions contrasts with the inherent difficulty in the perception of unfamiliar faces across similar image manipulations. It is widely believed that this difference in perception and recognition is based on the neural representation for familiar faces being less sensitive to changes in the image than it is for unfamiliar faces. Here, we used an functional magnetic resonance-adaptation paradigm to investigate image invariance in face-selective regions of the human brain. We found clear evidence for a degree of image-invariant adaptation to facial identity in face-selective regions, such as the fusiform face area. However, contrary to the predictions of models of face processing, comparable levels of image invariance were evident for both familiar and unfamiliar faces. This suggests that the marked differences in the perception of familiar and unfamiliar faces may not depend on differences in the way multiple images are represented in core face-selective regions of the human brain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".