Altered white matter connectivity in young people exposed to childhood abuse: a tract-based spatial statistics (TBSS) and tractography study
Bibliographic record
Abstract
Background: Childhood abuse is associated with structural brain abnormalities. Few studies have investigated white matter tract abnormalities in medication-naive, drug-free individuals who experienced childhood abuse. We examined the association between childhood abuse and abnormalities in white matter tracts in that population, controlling for psychiatric comorbidities. Methods: We collected diffusion tensor imaging data for age- and sex-matched youth with childhood abuse, psychiatric controls (matched for psychiatric diagnoses) and healthy controls. Tract-specific analysis was conducted using tractography. Tract-based spatial statistics (TBSS) was used to assess group differences in fractional anisotropy (FA) at the whole-brain level. Results: We included 20 youth who experienced childhood abuse, 18 psychiatric controls and 25 healthy controls in our analysis. Tractography analysis showed abuse-specific reduced tract volume in the inferior longitudinal fasciculus (ILF) and inferior frontal-occipital fasciculus (IFoF) in the abuse group relative to both healthy and psychiatric controls. Furthermore, abnormalities in the left IFoF were associated with greater abuse severity. The TBSS analysis showed significantly reduced FA in a left-hemispheric cluster comprising the ILF, IFoF and corpus callosum splenium in the abuse group relative to healthy and psychiatric controls. Limitations: It is unclear to what extent pubertal development, malnutrition and prenatal drug exposure may have influenced the findings. Conclusion: Childhood abuse is associated with altered structure of neural pathways connecting the frontal, temporal and occipital cortices that are known to mediate affect and cognitive control. The abuse-specific deficits in the ILF and IFoF suggest that fibre tracts presumably involved in conveying and processing the adverse abusive experience are specifically compromised in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".