White Matter Deficits in Psychopathic Offenders and Correlation with Factor Structure
Bibliographic record
Abstract
Psychopathic offenders show a persistent pattern of emotional unresponsivity to the often horrendous crimes they perpetrate. Recent studies have related psychopathy to alterations in white matter. Therefore, diffusion tensor imaging followed by tract-based spatial statistics (TBSS) analysis in 11 psychopathic offenders matched to 11 healthy controls was completed. Fractional anisotropy was calculated within each voxel and comparisons were made between groups using a permutation test. Any clusters of white matter voxels different between groups were submitted to probabilistic tractography. Significant differences in fractional anisotropy were found between psychopathic offenders and healthy controls in three main white matter clusters. These three clusters represented two major networks: an amygdalo-prefrontal network, and a striato-thalamo-frontal network. The interpersonal/affective component of the PCL-R correlated with white matter deficits in the orbitofrontal cortex and frontal pole whereas the antisocial component correlated with deficits in the striato-thalamo-frontal network. In addition to replicating earlier work concerning disruption of an amygdala-prefrontal network, we show for the first time that white matter integrity in a striato-thalamo-frontal network is disrupted in psychopathic offenders. The novelty of our findings lies in the two dissociable white matter networks that map directly onto the two major factors of psychopathy.
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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".