Neurophysiological Correlates of Emotion Regulation in Children and Adolescents
Bibliographic record
Abstract
Psychologists consider emotion regulation a critical developmental acquisition. Yet, there has been very little research on the neural underpinnings of emotion regulation across childhood and adolescence. We selected two ERP components associated with inhibitory control-the frontal N2 and frontal P3. We recorded these components before, during, and after a negative emotion induction, and compared their amplitude, latency, and source localization over age. Fifty-eight children 5-16 years of age engaged in a simple go/no-go procedure in which points for successful performance earned a valued prize. The temporary loss of all points triggered negative emotions, as confirmed by self-report scales. Both the frontal N2 and frontal P3 decreased in amplitude and latency with age, consistent with the hypothesis of increasing cortical efficiency. Amplitudes were also greater following the emotion induction, only for adolescents for the N2 but across the age span for the frontal P3, suggesting different but overlapping profiles of emotion-related control mechanisms. No-go N2 amplitudes were greater than go N2 amplitudes following the emotion induction at all ages, suggesting a consistent effect of negative emotion on mechanisms of response inhibition. No-go P3 amplitudes were also greater than go P3 amplitudes and they decreased with age, whereas go P3 amplitudes remained low. Finally, source modeling indicated a developmental decline in central-posterior midline activity paralleled by increasing activity in frontal midline regions suggestive of the anterior cingulate cortex. Negative emotion induction corresponded with an additional right ventral prefrontal or temporal generator beginning in middle childhood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".