Activation of the Anterior Prefrontal Cortex by Abacus Activity in Children: A Case Study on the Effect of Moderate Load Training on Working Memory
Bibliographic record
Abstract
Much attention has been paid to the enhancement of working memory, which can improve children’s lives. Part of the value of working memory training is that it activates the prefrontal cortex. Therefore, it is important to determine the parts of the prefrontal cortex that are activated by working memory training. While there is much evidence that mental abacus effectively trains working memory, few studies have assessed whether the abacus (Soroban) in Japan should be considered an effective training approach for working memory and if it activates the prefrontal cortex. Therefore, in this case study, a 16-channel functional near-infrared spectroscopy device (OEG-16H, Spectratech, Japan) was used to compare brain activation during the abacus task using the Wechsler Intelligence Scale for Children Working Memory Index tasks (i.e., digit span (forward), digit span (backward), letter–number sequencing, and picture span tasks). First-grade boys and fifth-grade girls participated in this study. The results revealed that the anterior part of the prefrontal cortex was specifically activated by the abacus task. These findings support the possibility that the abacus activity is an effective training approach for working memory.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".