Neglectful maternal caregiving involves altered brain plasticity in empathy-related areas
Bibliographic record
Abstract
Abstract The maternal brain undergoes functional and structural adaptations to sensitive caregiving that are critical for ensuring infant wellbeing. This study investigates brain structural alterations in neglectful caregiving and their impact on mother-child interactive behavior. High-resolution 3D volumetric images were obtained on 25 neglectful (NM) and 23 non-neglectful control (CM) mothers. Using Voxel-Based Morphometry, we compared gray and white matter volume (GMV/WMV) between the two groups. Mothers also completed an empathy scale and participated with their children in a standardized play task (Emotional Availability Scale, EA). NM, as compared to CM, showed GMV reductions in right insula, anterior/middle cingulate, and right inferior frontal gyrus (IFG), as well as WMV reductions in bilateral frontal regions. A GMV increase was observed in the right fusiform and cerebellum. Regression analyses showed a negative effect of fusiform GMV and a positive effect of right frontal WMV on EA Mediation analyses showed the mediating role of emotional empathy in the positive effect of insula and IFG, and the negative effect of cerebellum on EA. Neglectful mothering involves an altered plasticity in emotional empathy-related areas and in frontal areas associated with poor mother-child interactive bonding, indicating how critical the structural changes in these areas are for infant wellbeing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".