Parental Reflective Functioning correlates to brain activation in response to video-stimuli of mother–child dyads: Links to maternal trauma history and PTSD
Bibliographic record
Abstract
Parental Reflective Functioning is a parent's capacity to infer mental states in herself and her child. Parental Reflective Functioning is linked to the quality of parent-child attachment and promotes parent-child mutual emotion regulation. We examined neural correlates of parental reflective functioning and their relationship to physical abuse. Participants were mothers with (n = 26) and without (n = 22) history of childhood physical abuse. Parental reflective functioning was assessed by coding transcripts of maternal narrative responses on interviews. All mothers also underwent magnetic resonance imaging while watching video clips of children during mother-child separation and play. Parental reflective functioning was significantly lower among mothers with histories of childhood physical abuse. When mothers without history of childhood physical abuse watched scenes of separation versus play, brain activation was positively correlated with parental reflective functioning in the ventromedial prefrontal cortex, and negatively associated with the dorsolateral prefrontal cortex and insula. These associations were not present when limiting analyses to mothers reporting abuse histories. Regions subserving emotion regulation and empathy were associated with parental reflective functioning; yet these regions were not featured in maltreated mothers. These data suggest that childhood physical abuse exposure may alter the psychobiology that is linked to emotional comprehension and regulation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".