Brain Network Activity During Face Perception: The Impact of Perceptual Familiarity and Individual Differences in Childhood Experience
Bibliographic record
Abstract
An extended distributed network of brain regions supports face perception. Face familiarity influences activity in brain regions involved in this network, but the impact of perceptual familiarity on this network has never been directly assessed with the use of partial least squares analysis. In the present work, we use this multivariate statistical analysis to examine how face-processing systems are differentially recruited by characteristics of the targets (i.e. perceptual familiarity and race) and of the perceivers (i.e. childhood interracial contact). Novel faces were found to preferentially recruit a large distributed face-processing network compared with perceptually familiar faces. Additionally, increased interracial contact during childhood led to decreased recruitment of distributed brain networks previously implicated in face perception, salience detection, and social cognition. Current results provide a novel perspective on the impact of cross-race exposure, suggesting that interracial contact early in life may dramatically shape the neural substrates of face perception generally.
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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) | 0.001 | 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".