Adolescents and young adults differ in their neural response to and recognition of adolescent and adult emotional faces
Bibliographic record
Abstract
Peer relationships become increasingly important during adolescence. The success of these relationships may rely on the ability to attend to and decode subtle or ambiguous emotional expressions that are common in social interactions. However, most studies examining youths' processing and labeling of facial emotion have employed adult faces and faces that depict emotional extremes as stimuli. In this study, 40 adolescents and 40 young adults viewed blends of angry-neutral, fearful-neutral, and happy-neutral faces (e.g., 100% angry, 66% angry, 33% angry, neutral) portrayed by adolescent and adult actors as electroencephalogram (EEG) was recorded. Participants also labeled these faces according to the emotion expressed (i.e., angry, fearful, happy, or neutral). The Late Positive Potential (LPP), an event-related potential (ERP) component that reflects sustained attention to motivationally salient information, was scored from the EEG following face presentation. Among adolescents, as peer-age faces moved from ambiguous (33%) to unambiguous (100%) emotional expression, the LPP similarly increased. These effects were not found when adolescents viewed emotional face blends portrayed by adult actors. Additionally, while both adolescents and young adults showed greater emotion labeling accuracy as faces increased in emotional intensity from ambiguous to unambiguous emotional expression, adolescent participants did not show greater accuracy when labeling peer-compared to adult-age faces. Together, these data suggest that adolescents attend more to subtle differences in peer-age emotional faces, but they do not label these emotional expressions more accurately than adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".