The dark sides of the brain: A systematic review and meta-analysis of functional neuroimaging studies on trait aggression
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Bibliographic record
Abstract
Aggression is a worldwide issue that has significant consequences for both the victims and societies. However, aggression may vary in its underlying motivation (i.e., reactive versus proactive) and the forms in which it occurs (i.e., physical versus verbal). Yet, functional brain correlates differentiating these types remains largely unknown. A systematic search was conducted up to May 1st 2023, using PubMed, Google Scholar, and Web of Science, to identify relevant functional neuroimaging studies that included measures of General Aggression, Reactive Aggression, Proactive Aggression, Physical Aggression and Verbal Aggression. Coordinate-based meta-analysis was conducted using both spatial convergence (ALE) and effect-size (SDM-PSI) approaches. Sixty-seven functional neuroimaging studies met the inclusion criteria. Meta-analysis revealed similar yet distinct neural correlates for General Aggression (i.e., Amygdala, Precuneus, Intraparietal Sulcus, Angular and Middle Temporal Gyri), Reactive Aggression (i.e., Amygdala, Periaqueductal Grey, Posterior Insula, & Central Opercular Cortex), Proactive Aggression (i.e., Septal Area, & Amygdala), Physical Aggression (i.e., Dorsal Premotor Cortex, Dorsal Caudate, & Dorsal Anterior Cingulate Cortex), and Verbal (i.e., Dorsal Anterior Cingulate Cortex). Exploratory analyses revealed the importance of affective, cognitive and social cognition processes as well as serotoninergic, dopaminergic, and cholinergic systems in the neural underpinnings of aggressive behaviors. Our findings highlight the importance of examining the types of aggression (i.e., motivation and forms) within a transdiagnostic framework. Therefore, characterizing the neurobiological substrates of aggression may expand our search for targeted neuromodulation and pharmacological treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it