The Late Positive Potential as a Reliable Neural Marker of Cognitive Reappraisal in Children and Youth: A Brief Review of the Research Literature
Bibliographic record
Abstract
The mental health of young people is a growing public health concern. With socio-emotional difficulties in youth often resulting in psychiatric disorders later in life and most with mental health conditions rather stabilizing in time, it is essential to support healthy socio-emotional development. With a comprehensive definition of mental health, since emotion regulation (ER) plays a critical role in prevention, it becomes imperative to better understand how children effectively manage their emotions from an early age. Determining effective use of ER skills relies on adequate measurements. Typical methods of data collection in children present consistent shortcomings. This review addresses research findings considering the suitability of the late positive potential measured through electroencephalogram as a neural indicator of ER in children and youth. There is growing evidence, as reported in this review, that indicates that the late positive potential may be a reliable neural indicator of children's cognitive reappraisal abilities more specifically. Results generally suggest that the late positive potential amplitudes are sensitive to directed reappraisal in children. However, given the scant research, questions remain regarding developmental trends, methodology, interindividual variability, reappraisal of various stimuli, and how the late positive potential may relate to more traditional measures of ER. Directions for future research are provided, which are expected to address unanswered research questions and fill literature gaps. Taken together, the findings reviewed indicate that the late positive potential is generally sensitive to directed cognitive reappraisal in children and that there is promise of establishing this neural marker as an indicator of ER.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".