Single-Photon Emission Computed Tomography and Positron Emission Tomography Studies of Antisocial Personality Disorder and Aggression: a Targeted Review
Bibliographic record
Abstract
This paper aims to provide a comprehensive discussion of single-photon emission computed tomography (SPECT) and positron emission tomography (PET) studies of antisocial personality disorder (ASPD) and aggression. Among ASPD males with high impulsivity, the density of brainstem serotonin (5-HT) transporters shows a relationship with impulsivity, aggression, and ratings of childhood trauma. 5-HT 1B receptor (R) binding in the striatum, anterior cingulate cortex, and orbitofrontal cortex (OFC) correlated with anger, aggression, and psychopathic traits in another study of violent offenders, most of whom were diagnosed with ASPD. Finally, the density of monoamine oxidase-A (MAO-A), a mitochondrial enzyme that degrades 5-HT, norepinephrine, and dopamine (DA), was reported as lower in the OFC and ventral striatum of ASPD. Among non-clinical populations, 5-HT 4 R binding, as an index of low cerebral 5-HT levels, has been associated with high trait aggression, but only in males. Furthermore, evidence suggests that individuals with high-activity MAO-A genetic variants compared with low-activity MAO-A allelic variants release more DA in the ventral caudate and putamen when exposed to violent imagery. There are very few PET or SPECT studies that exclusively sample individuals with ASPD. However, among ASPD samples, there is evidence of regional serotonergic abnormalities in the brain and alteration of neural MAO-A levels. Future studies should consider employing additional molecular probes that could target alternative neurotransmitter systems to investigate ASPD. Furthermore, examining different typologies of aggression in clinical and non-clinical populations using SPECT/PET is another important area to pursue and could shed light on the neurochemical origins of these traits in ASPD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".