Neural mechanisms of emotion regulation in childhood anxiety
Bibliographic record
Abstract
BACKGROUND: The present study was designed to examine the cortical processes that mediate cognitive regulation in response to emotion-eliciting stimuli in anxious children. METHODS: Electroencephalographic (EEG) activity was recorded from clinically anxious children (n = 29) and typically developing children (n = 34). Event-related potential components were recorded while children performed a go/no-go task using facial stimuli depicting angry, calm, and happy expressions. RESULTS: Anxious children had significantly greater posterior P1 and frontal N2 amplitudes, components associated with attention/arousal and cognitive control, respectively, than typically developing children. Anxious children also had significantly greater error-related negativities and correct-response negativities relative to typically developing children. For the anxious group only, there were no differences in neural activation between face (emotion) types or trial (Go vs. No-go) types. A regression analysis revealed that No-go N2 amplitudes for calm faces predicted self-reported anxiety levels. CONCLUSIONS: Anxious children appeared to show increased cortical activation regardless of the emotional content of the stimuli. Anxious children also showed greater medial-frontal activity regardless of task demands and response accuracy. Taken together, these findings suggest indiscriminate cortical processes that may underlie the hypervigilant regulatory style seen in clinically anxious individuals.
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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".