Adolescent females exposed to child maltreatment exhibit atypical EEG coherence and psychiatric impairment: Linking early adversity, the brain, and psychopathology
Bibliographic record
Abstract
Although the relation between child maltreatment and psychiatric impairment is well documented and preliminary evidence has linked child maltreatment with aberrant cortical connectivity of the left hemisphere, no investigations have attempted to examine these relations in the same study. Here, we examined the links among early adversity, brain connectivity, and functional outcomes. We collected resting regional EEG intra- and interhemispheric alpha-band (7.5-12.5 Hz) coherence and measures of general psychiatric impairment from a cohort of 38 adolescent females exposed to child maltreatment (M age = 14.47) and 24 adolescent females not exposed to child maltreatment (M age = 14.00). Maltreated youths exhibited more left hemisphere EEG coherence than the control youths, suggesting a suboptimal organization of cortical networks. Maltreated participants also showed reduced frontal (anterior) interhemispheric coherence. These differences in brain circuitry remained statistically significant even after controlling for group differences in pubertal status and socioeconomic status. Measures of functional brain connectivity were associated with several subtypes of abuse and neglect. It was important that atypical left hemisphere EEG coherence mediated the effects of child maltreatment on levels of psychiatric impairment. The findings are discussed in the context of models linking early adversity to brain function and psychopathology.
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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 | 0.001 |
| 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) | 0.001 | 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".