Decoding of faces and face components in face-sensitive human visual cortex
Bibliographic record
Abstract
A great challenge to the field of visual neuroscience is to understand how faces are encoded and represented within the human brain. Here we show evidence from functional magnetic resonance imaging (fMRI) for spatially distributed processing of the whole face and its components in face-sensitive human visual cortex. We used multi-class linear pattern classifiers constructed with a leave-one-scan-out verification procedure to discriminate brain activation patterns elicited by whole faces, the internal features alone, and the external head outline alone. Furthermore, our results suggest that whole faces are represented disproportionately in the fusiform cortex (FFA) whereas the building blocks of faces are represented disproportionately in occipitotemporal cortex (OFA). Faces and face components may therefore be organized with functional clustering within both the FFA and OFA, but with specialization for face components in the OFA and the whole face in the FFA.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".