Anterior cingulate hyperactivations during negative emotion processing among men with schizophrenia and a history of violent behavior
Bibliographic record
Abstract
BACKGROUND: Evidence suggests a 2.1-4.6 times increase in the risk of violent behavior in schizophrenia compared to the general population. Current theories propose that the processing of negative emotions is defective in violent individuals and that dysfunctions within the neural circuits involved in emotion processing are implicated in violence. Although schizophrenia patients show enhanced sensitivity to negative stimuli, there are only few functional neuroimaging studies that have examined emotion processing among men with schizophrenia and a history of violence. OBJECTIVE: The present study aimed to identify the brain regions with greater neurofunctional alterations, as detected by functional magnetic resonance imaging during an emotion processing task, of men with schizophrenia who had engaged in violent behavior compared with those who had not. METHODS: Sixty men were studied; 20 with schizophrenia and a history of violence, 19 with schizophrenia and no violence, and 21 healthy men were scanned while viewing positive, negative, and neutral images. RESULTS: Negative images elicited hyperactivations in the anterior cingulate cortex (ACC), left and right lingual gyrus, and the left precentral gyrus in violent men with schizophrenia, compared to nonviolent men with schizophrenia and healthy men. Neutral images elicited hyperactivations in the right and left middle occipital gyrus, left lingual gyrus, and the left fusiform gyrus in violent men with schizophrenia, compared to the other two groups. DISCUSSION: Violent men with schizophrenia displayed specific increases in ACC in response to negative images. Given the role of the ACC in information integration, these results indicate a specific dysfunction in the processing of negative emotions that may trigger violent behavior in men with schizophrenia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".