Response of Prefrontal Cortex to Executive Function Tasks in Early Childhood: An Exploratory Case Study for Childcare
Bibliographic record
Abstract
Executive function (EF) development is remarkable in early childhood. EF is an ability that provides a foundation for future success; accordingly, supporting children during their early childhood is crucial. So far, there have been many findings on EF in early childhood based on behavioral observation. This exploratory case study examines the measurement of prefrontal cortex activity during the performance of EF tasks using functional near-infrared spectroscopy (fNIRS). This study aims to explore the following hypothesis. (1) The prefrontal cortex during early childhood becomes more active as a task becomes more difficult. (2) However, brain activity decreases and stabilizes as time progresses. (3) The evaluation can be easily measured with two-channel fNIRS. Experimental results showed that the preschooler and the child in lower elementary school displayed high levels of brain activity in the order of increasing difficulty in terms of behavioral indicators. Moreover, the preschooler showed higher levels of reaction than the child in lower elementary school. This result is useful and will broaden the perspectives of scholars in the fields of psychology, pedagogy, and neuroscience, those involved in child support.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".