The Fusiform Face Area Plays a Greater Role in Holistic Processing for Own-Race Faces Than Other-Race Faces
Bibliographic record
Abstract
Own-race faces are recognized more effectively than other-race faces. This phenomenon is referred to as other-race effect (ORE). Existing behavioral evidence suggests that one of the possible causes of ORE is that own-race faces are processed more holistically than other-race faces. However, little is known about whether such differences in processing also produce distinctive neural responses in the cortical face processing network. To bridge this gap, the present study used fMRI methodology and the composite face paradigm to examine the response patterns of the traditional face-preferential cortical areas (i.e., the bilateral fusiform face areas [FFA] and the bilateral occipital face areas [OFA]) elicited by own-race faces and other-race faces. We found that the right FFA exhibited a neural composite face effect only for own-race faces but not for other-race faces, even with the absence of the race-related difference in behavior composite face effect. These findings suggest that the right FFA plays a greater role in holistic processing of individual own-race faces than other-race faces. They also suggest that the neural composite effect observed in the right FFA is not the exact neural counterpart of the behavioral face composite effect. The findings of the present study revealed that, along the pathway of the bottom-up face processing, own-race faces and other-race faces presented the holistic processing difference as early as when they were processed in the right 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".