2-Brain Regulation for Improved Neuroprotection during Early Development (2-BRAINED): a translational hyperscanning research project
Bibliographic record
Abstract
Introduction: Very preterm (VPT) birth is a major risk condition for child development and parental wellbeing, mainly due to multiple sources of stress (e.g., separation and pain exposure) during the neonatal intensive care unit (NICU) stay. Early video-feedback (VF) interventions proved effective in promoting VOT infants' development and parental wellbeing. Electroencephalography (EEG) hyperscanning allows the assessment of brain-to-brain co-regulation during live interaction between infants and parents, offering promising insights into the mechanisms behind the interactive benefits of early VF interventions. Goals: This study aimed to compare indices of brain-to-brain co-regulation between dyads of full-term (FT) and VPT infants interacting with their mothers and investigate the effect of an early post-discharge VF intervention on the brain-to-brain co-regulation indices of VPT dyads. Methods and analysis: VPT and FT dyads will be enrolled at birth, and the former will be randomly allocated to one of two arms: VF intervention or care as usual. Short-term effectiveness will be assessed through ratings of mother-infant interaction videotaped before and after the VF intervention or care as usual. Mothers of VPT and FT infants will report on their mental state, parenting stress and bonding, and infant temperament and sensory profile at 3 and 6 months (corrected age, CA). At 9 months CA, all dyads will participate in a lab-based EEG-hyperscanning paradigm to assess brain-to-brain co-regulation through phase-locking value (PLV) and other explorative indices. Ethics and dissemination: This study was funded by the Italian Ministry of Health and received approval by the Ethics Committee of Pavia (Italy) and participating hospitals. Research findings will be reported in scientific publications, presented at international conferences, and disseminated to the general public. Study registration number: GR-2021-12375213 (Italian Ministry of Health registry).
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".