Multidimensional Approach to Examining Aggression Vulnerability: Psychosocial Factors and Structural Variations in the Amygdala and Prefrontal Cortex
Author: Kok Tsz Wing, Marcus Jude Wong Shyuan
Project Overview
This project examines whether structural brain measures previously linked to aggression and emotion regulation — amygdala volume, medial orbitofrontal cortex (mOFC) gray matter volume and thickness, and rostral anterior cingulate cortex (rACC) gray matter volume — are associated with self-reported anger, hostility, and rejection sensitivity in a large healthy adult sample.
Using data from the Human Connectome Project Young Adult (HCP-YA) dataset (N = 1105 after quality control), bilateral FreeSurfer-derived brain volumes/thickness were normalised for intracranial volume and correlated with a battery of behavioural measures (perceived stress, self-efficacy, anger affect, anger hostility, anger aggression, perceived hostility, perceived rejection, inhibitory control via Flanker task, and NEO-FFI Agreeableness/Conscientiousness). False discovery rate (Benjamini-Hochberg) correction was applied across all brain-behaviour pairs.
Is aggression-related psychosocial factors (stress, self-efficacy, executive control, anger/hostility, and personality) associated with structural variation in the amygdala and prefrontal cortex, and is this association moderated by age and gender?
Background
Majority of aggression research rely on self-report measures and behavioural paradigms (Roberton et al., 2012)
-Studied in silots from biological/neural explanations for aggression
Existing neuroimaging research (Rosell & Siever, 2015; Siever, 2008) suggests that aggression is associated with:
-Poor emotional regulation ↔ emotion-processing systems (e.g., amygdala)
-Low inhibitory control ↔ reward-processing systems
-Maladaptive decision-making ↔ executive-control systems (e.g., prefrontal cortex)
BUT relevant brain systems are often studied independently
Research on amygdala volume and levels of agression and violence:
-Smaller amygdalar volumes have been found to have higher levels of aggression and violence
-Smaller amygdala volume has a higher correlation with violence (Johansen et al., 2011; Rosell and Siever, 2015)
-In affective psychoses/bipolar disorder specifically, studies have detected increased volumes of amygdala (Widmayer et al., 2018)
Research on PFC volume and aggression:
-Lower PFC volume (particularly orbitofrontal and dorsolateral regions) has been found to correlate with antisocial personality disorder (Raine et al., 2000; Yang & Raine, 2009)
-Increased risk of violent outcomes across personality disorder studies (Yu et al., 2012)
Key Findings
Broad screen: 4 brain measures × 11 behavioural measures (44 tests, FDR-corrected)
All correlations were weak (|r| ≤ 0.08), and none survived FDR correction (q < 0.05). The strongest uncorrected associations were:
| Brain Variable | Behavioural Variable | r | r² | p (uncorrected) | p (FDR) |
|---|---|---|---|---|---|
| rACC Gray Vol (norm) | Anger Aggression | 0.077 | 0.006 | 0.011 | 0.195 |
| Amygdala Vol (norm) | Flanker (unadjusted) | -0.076 | 0.006 | 0.012 | 0.195 |
| Amygdala Vol (norm) | Flanker (age-adjusted) | -0.075 | 0.006 | 0.013 | 0.195 |
| rACC Gray Vol (norm) | NEO-FFI Agreeableness | -0.068 | 0.005 | 0.026 | 0.285 |
Overall, no robust associations were found between structural brain measures and self-reported anger/hostility traits in this sample. Effect sizes were uniformly negligible (r² < 0.6%), suggesting that, at least for these regions and this measure-set, structural variation does not meaningfully explain individual differences in trait anger or hostility.
Composite variables and follow-up modelling
To address the multiple-comparisons problem and reduce dimensionality, two composite variables were constructed:
- Aggression/Hostility composite — the mean of z-scored Anger Affect, Anger Hostility, Anger Aggression, Perceived Hostility, and Perceived Rejection. Internal consistency was acceptable (Cronbach's α = 0.76), supporting treatment of these five items as a single underlying construct.
- Amygdala-PFC balance score — the z-scored amygdala volume minus the mean of z-scored mOFC and rACC gray matter volumes, reflecting a regulatory-circuit (amygdala vs. prefrontal control) hypothesis.
An OLS regression tested whether the Amygdala-PFC balance score predicted the Aggression/Hostility composite, including interactions with sex and age:
Aggression_composite ~ Amyg_PFC_balance * Gender_num + Amyg_PFC_balance * Age_mid_z + Age_mid_z + Gender_num
| Predictor | Coefficient | p-value |
|---|---|---|
| Amyg_PFC_balance (main effect) | 0.044 | 0.145 |
| Gender_num | -0.198 | < 0.001 |
| Amyg_PFC_balance × Gender_num | -0.075 | 0.070 |
| Age_mid_z | -0.052 | 0.019 |
| Amyg_PFC_balance × Age_mid_z | 0.040 | 0.048 |
The overall model was significant (R² = 0.033, F = 7.29, p < 0.001), driven mainly by the sex and age main effects rather than the brain-balance measure itself. The main effect of the Amygdala-PFC balance score on aggression was null, but exploratory interactions suggest this relationship may be moderated by age (p = 0.048) and possibly sex (p = 0.070). Given the small effect sizes and lack of correction for these additional exploratory tests, these findings are preliminary and would need replication in an independent sample.
Dataset
Human Connectome Project Young Adult (HCP-YA) dataset. Data access requires a data use agreement via ConnectomeDB: https://db.humanconnectome.org
Raw data files (unrestricted_hcp_freesurfer.csv, HCP_YA_subjects_*.csv) are not included in this repository due to data use agreement restrictions. Download from ConnectomeDB and place in your working directory before running.
Repository Contents
Project_aggression.ipynb — full analysis notebook (data cleaning, normalisation, outlier handling, z-scoring, correlation analyses, FDR correction, composite construction)
How to Run
Obtain access to and download the required HCP-YA FreeSurfer and behavioural CSV files from ConnectomeDB Place the CSV files in the same directory as the notebook (or update the file paths in the data-loading cell) Run all cells in Project_aggression.ipynb in order
Dependencies
Python packages: pandas, numpy, matplotlib, seaborn, scipy, statsmodels
References
Anderson, C. A., & Bushman, B. J. (2002). Human aggression. Annual Review of Psychology, 53, 27–51. https://doi.org/10.1146/annurev.psych.53.100901.135231
Heilbron, N., & Prinstein, M. J. (2008). A review and reconceptualization of social aggression: Adaptive and maladaptive correlates. Clinical Child and Family Psychology Review, 11(4), 176–217. https://doi.org/10.1007/s10567-008-0037-9
Jones, S. E., Miller, J. D., & Lynam, D. R. (2011). Personality, antisocial behavior, and aggression: A meta-analytic review. Journal of Criminal Justice, 39(4), 329–337. https://doi.org/10.1016/j.jcrimjus.2011.03.004
Krämer, U. M., Jansma, H., Tempelmann, C., & Münte, T. F. (2011). Executive control in trait aggression: An fMRI study of inhibitory control using the Flanker task. Social Cognitive and Affective Neuroscience, 6(2), 180–188. https://doi.org/10.1093/scan/nsq072
Mesurado, B., Vidal, E. M., & Mestre, A. L. (2018). Negative emotions and behaviour: The role of regulatory emotional self-efficacy. Journal of Adolescence (London, England.), 64, 62–71. https://doi.org/10.1016/j.adolescence.2018.01.007
Pawliczek, C. M., Derntl, B., Kellermann, T., Kohn, N., Gur, R. C., & Habel, U. (2013). Inhibitory control and trait aggression: Neural and behavioral correlates during an emotional go/no-go task. Social Cognitive and Affective Neuroscience, 8(6), 728–735. https://doi.org/10.1093/scan/nss065
Roberton, T., Daffern, M., & Bucks, R. S. (2012). Emotion regulation and aggression. Aggression and Violent Behavior, 17(1), 72–82. https://doi.org/10.1016/j.avb.2011.09.006
Rosell, D. R., & Siever, L. J. (2015). The neurobiology of aggression and violence. CNS Spectrums, 20(3), 254–279. https://doi.org/10.1017/S109285291500019X
Siever, L. J. (2008). Neurobiology of aggression and violence. The American Journal of Psychiatry, 165(4), 429–442. https://doi.org/10.1176/appi.ajp.2008.07111774
Smith, K., Jones, A., Daly, N., Widdrington, H., Garofalo, C., & Gillespie, S. M. (2026). Emotion regulation and aggression: A systematic review and meta‐analysis. Aggressive Behavior, 52(1), e70055-n/a. https://doi.org/10.1002/ab.70055