Brain gray matter differences among forensic psychiatric patients with psychosis and incarcerated individuals without psychosis: A source-based morphometry study
Bibliographic record
Abstract
BACKGROUND: While psychosis is a risk factor for violence, the majority of individuals who perpetrate aggression do not present psychotic symptoms. Pathological aggressive behavior is associated with brain gray matter differences, which, in turn, has shown a relationship with increased psychopathic traits. However, no study, to our knowledge, has ever investigated gray matter differences in forensic psychiatric patients with psychosis compared with incarcerated individuals without psychosis matched on levels of psychopathic traits. Here, we employed source-based morphometry (SBM) to investigate gray matter differences in these two populations. METHODS: We scanned 137 participants comprising two offender subgroups: 69, non-psychotic incarcerated offenders and 68, psychotic, forensic psychiatric patients. Groups showed no difference in age, race, ethnicity, handedness, and Hare Psychopathy Checklist-Revised scores. Source-based morphometry was utilized to identify spatially distinct sets of brain regions where gray matter volumes covaried between groups. SBM is a data-driven, multivariate technique that uses independent components analysis to categorize groups of voxels that display similar variance patterns (e.g., components) that are compared across groups. RESULTS: SBM identified four components that differed between groups. These findings indicated greater loading weights in the superior, transverse, and middle temporal gyrus and anterior cingulate in the non-psychotic versus psychotic group; greater loading weights in the basal ganglia in the psychotic versus non-psychotic group; greater loading weights in the frontal pole, precuneus, and visual cortex among psychotic versus non-psychotic offenders; and greater loading weights in the thalamus and parahippocampal gyrus in psychotic versus non-psychotic groups. CONCLUSIONS: Two different offender groups that perpetrate violence and show comparable levels of psychopathic traits evidenced different gray matter volumes. We suggest that future studies of violent offenders with psychosis take psychopathic traits into account to refine neural phenotypes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".