The changing face of emotion: age-related patterns of amygdala activation to salient faces
Bibliographic record
Abstract
The present study investigated age-related differences in the amygdala and other nodes of face-processing networks in response to facial expression and familiarity. fMRI data were analyzed from 31 children (3.5-8.5 years) and 14 young adults (18-33 years) who viewed pictures of familiar (mothers) and unfamiliar emotional faces. Results showed that amygdala activation for faces over a scrambled image baseline increased with age. Children, but not adults, showed greater amygdala activation to happy than angry faces; in addition, amygdala activation for angry faces increased with age. In keeping with growing evidence of a positivity bias in young children, our data suggest that children find happy faces to be more salient or meaningful than angry faces. Both children and adults showed preferential activation to mothers' over strangers' faces in a region of rostral anterior cingulate cortex associated with self-evaluation, suggesting that some nodes in frontal evaluative networks are active early in development. This study presents novel data on neural correlates of face processing in childhood and indicates that preferential amygdala activation for emotional expressions changes with age.
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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".