EEG Delta-Beta Coupling in 2-year-old Offspring of Pregnant Persons Receiving a Diet-and-Exercise Intervention: A Randomized Controlled Trial Follow-up
Bibliographic record
Abstract
Background: Delta-beta coupling (DBC) is a neural marker of emotion regulation (ER), with elevated DBC linked to cortical over-processing of emotional stimuli. This study investigates the effects of the Be Healthy in Pregnancy (BHIP) intervention, combining a high-protein, energy-controlled diet, nutrition counseling, and physical activity, on offspring DBC. Methods: Pregnant individuals received either the BHIP intervention or usual care. Twenty-four offspring at follow-up completed resting-state EEG at age two using a 128-channel system. DBC was quantified as the correlation coefficient between delta (2–4Hz) and beta (13–30Hz) power across epochs. Group differences were analyzed using Fisher’s Z-tests. Results: BHIP offspring exhibited significantly lower DBC in frontal (p=.017), central (p=.014), and parietal (p=.009) regions compared to controls. Conclusion: Reduced DBC reflects a neural profile linked to efficient ER, enabling context-appropriate cognitive resource allocation. These findings suggest prenatal diet and exercise potentially modulate neurodevelopment, warranting validation in larger, more diverse cohorts.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".