Personality disorder symptomatology is associated with anomalies in striatal and prefrontal morphology
Bibliographic record
Abstract
Personality disorder symptomatology (PD-Sx) can result in personal distress and impaired interpersonal functioning, even in the absence of a clinical diagnosis, and is frequently comorbid with psychiatric disorders such as substance use, mood, and anxiety disorders; however, they often remain untreated, and are not taken into account in clinical studies. To investigate brain morphological correlates of PD-Sx, we measured subcortical volume and shape, and cortical thickness/surface area, based on structural magnetic resonance images. We investigated 37 subjects who reported PD-Sx exceeding DSM-IV Axis-II screening thresholds, and 35 age, sex, and smoking status-matched control subjects. Subjects reporting PD-Sx were then grouped into symptom-based clusters: N = 20 into Cluster B (reporting Antisocial, Borderline, Histrionic, or Narcissistic PD-Sx) and N = 28 into Cluster C (reporting Obsessive-Compulsive, Avoidant, or Dependent PD-Sx); N = 11 subjects reported PD-Sx from both clusters, and none reported Cluster A (Paranoid, Schizoid, or Schizotypal) PD-Sx. Compared to control, Cluster C PD-Sx was associated with greater striatal surface area localized to the caudate tail, smaller ventral striatum volumes, and greater cortical thickness in right prefrontal cortex. Both Cluster B and C PD-Sx groups also showed trends toward greater posterior caudate volumes and orbitofrontal surface area anomalies, but these findings did not survive correction for multiple comparisons. The results point to morphological abnormalities that could contribute to Cluster C PD-Sx. In addition, the observations parallel those in substance use disorders, pointing to the importance of considering PD-Sx when interpreting findings in often-comorbid psychiatric disorders.
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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 | 0.001 | 0.001 |
| 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".