Cortical mechanisms of emotion regulation in young children responding to angry, neutral, and happy faces
Bibliographic record
Abstract
The study of neural mechanisms underlying emotion regulation is currently of great interest to developmental psychologists. In order to assess normative patterns and individual differences in mechanisms of emotion regulation mediated by the frontal cortices, we examined young children's event-related potentials (ERPs) across varying emotional conditions. EEG was recorded from thirteen 4–6-year-old children, who viewed on-screen pictures of angry, neutral, and happy faces while engaged in a go/no-go task. Peak medial-frontal ERPs following picture and response cue onset were compared across emotion face types and correlated with trait anxiety. As predicted, angry faces generated the largest and fastest ERPs. Source analysis indicated centromedial and right-inferior frontal sources contributing to the ERPs for angry faces. Following the response cue, ERPs were largest when responses were withheld. Finally, more anxious children showed faster ERPs for angry faces. These results are interpreted in terms of early-developing attentional mechanisms recruited to regulate anxiety.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".