Aggression is associated with greater subsequent alcohol consumption: A shared neural basis in the ventral striatum

Clinical Markers of Physical Violence in Patients with Bipolar Disorder in Manic States

Purpose

Identifying patients with bipolar disorder (BD) in manic states (BD-M) who are at a high risk of physical violence is a matter of clinical concern. This retrospective institution-based study aimed to identify simple, rapid, and inexpensive clinical markers of physical violence in patients with BD-M.

Patients and Methods

The anonymized sociodemographic variables (sex, age, years of education, marital status) and clinical ones (weight, height, body mass index, blood pressure, the score of BRMS, number of BD episodes, psychotic symptoms, history of violence, biochemical parameters, and blood routine parameters) of 316 BD-M participants were collected, and the risk of physical violence was identified using the Brøset Violence Checklist (BVC). Difference tests, correlation analyses, and multivariate linear regression analysis were performed to identify clinical markers for the risk of physical violence.

Results

The participants were categorized into groups at low (49, 15.51%), medium (129, 40.82%), and high (138, 43.67%) risk of physical violence. The number of BD episodes, serum uric acid (UA), free thyroxine (FT4) levels, history of violence, and monocyte-to-lymphocyte ratio (MLR) differed significantly between groups (all P<0.05). The number of BD episodes (r=0.152), FT3 (r=0.131) and FT4 (r=0.132) levels, history of violence (r=0.206), and MLR (r=-0.132) were significantly correlated with the risk of physical violence (all P<0.05). The existence of history of violence, number of BD episodes, UA, FT4, and MLR were identified as clinical markers of the risk of physical violence in patients with BD-M (all P<0.05).

Conclusion

These identified markers are readily available at initial presentation and may help in the timely assessment and treatment of patients with BD-M.

Neural bases of frustration-aggression theory: A multi-domain meta-analysis of functional neuroimaging studies

BACKGROUND

Early evidence suggests that unexpected non-reward may increase the risk for aggressive behaviors. Despite the growing interest in understanding brain functions that may be implicated in aggressive behaviors, the neural processes underlying such frustrative events remain largely unknown. Furthermore, meta-analytic results have produced discrepant results, potentially due to substantial differences in the definition of anger/aggression constructs.

METHODS

Therefore, we conducted a coordinate-based meta-analysis, using the activation likelihood estimation algorithm, on neuroimaging studies examining reward omission and retaliatory behaviors in healthy subjects. Conjunction analyses were further examined to discover overlapping brain activations across these meta-analytic maps.

RESULTS

Frustrative non-reward deactivated the orbitofrontal cortex, ventral striatum and posterior cingulate cortex, whereas increased activations were observed in midcingulo-insular regions. Retaliatory behaviors recruited the left fronto-insular and anterior midcingulate cortices, the dorsal caudate and the primary somatosensory cortex. Conjunction analyses revealed that both strongly activated midcingulo-insular regions.

LIMITATIONS

Spatial overlap between neural correlates of frustration and retaliatory behaviors was conducted using a conjunction analysis. Therefore, neurobiological markers underlying the temporal sequence of the frustration-aggression theory should be interpreted with caution.

CONCLUSIONS

Nonetheless, our results underscore the role of anterior midcingulate/pre-supplementary motor area and fronto-insular cortex in both frustration and retaliatory behaviors. A neurobiological framework for understanding frustration-based impulsive aggression is provided.

'Can we predict aggression?'-Determining the predictors of aggression among individuals with substance use disorder in China undergoing enforced detoxification through machine learning

BACKGROUND

The general aggression model has shown that both individual and situational factors can predict aggression. However, past research has tended to discuss these two factors separately, which might lead to inconsistency. This study addresses this gap by examining the importance of each predictor of aggression in a Chinese compulsory drug treatment population and further explores the predictors of aggression in various substance use disorder populations.

METHOD

Analyses were conducted using a sample of 894 male participants (mean = 38.30, SD = 8.38) in Chinese compulsory drug rehab. A machine learning model named LightGBM was employed to make predictions. We then used a game-theoretic explanatory technique, SHAP, to estimate the effect of predictors.

RESULTS

In the full-sample model, psychological security, parental conflict, and impulsivity were the top 3 predictors. Depression, childhood abuse, and alexithymia positively predicted aggression, whereas psychological security, family cohesion, and gratitude negatively predicted aggression. There were significant differences in the predictive effects of depressants and stimulants. Although the importance of predictors varied between drug-use groups, several individual and situational factors were consistently the most important predictors.

LIMITATIONS

All participants in this study were male, and the data were acquired through self-reports from the participants. Domestic and nondomestic aggression are not distinguished. Additionally, our findings cannot support causal conclusions.

CONCLUSION

This study tested a series of classical theories of the predictors of aggression in China's compulsory drug treatment context and extended the ideas of the GAM to various substance use disorder groups. The findings have important implications for aggression treatment.

Activation of glucagon-like peptide-1 receptors reduces the acquisition of aggression-like behaviors in male mice

Aggression is a complex social behavior, which is provoked in the defense of limited resources including food and mates. Recent advances show that the gut-brain hormone ghrelin modulates aggressive behaviors. As the gut-brain hormone glucagon-like peptide-1 (GLP-1) reduces food intake and sexual behaviors its potential role in aggressive behaviors is likely. Therefore, we investigated a tentative link between GLP-1 and aggressive behaviors by combining preclinical and human genetic-association studies. The influence of acute or repeated injections of a GLP-1 receptor (GLP-1R) agonist, exendin-4 (Ex4), on aggressive behaviors was assessed in male mice exposed to the resident-intruder paradigm. Besides, possible mechanisms participating in the ability of Ex4 to reduce aggressive behaviors were evaluated. Associations of polymorphisms in GLP-1R genes and overt aggression in males of the CATSS cohort were assessed. In male mice, repeated, but not acute, Ex4 treatment dose-dependently reduced aggressive behaviors. Neurochemical and western blot studies further revealed that putative serotonergic and noradrenergic signaling in nucleus accumbens, specifically the shell compartment, may participate in the interaction between Ex4 and aggression. As high-fat diet (HFD) impairs the responsiveness to GLP-1 on various behaviors the possibility that HFD blunts the ability of Ex4 to reduce aggressive behaviors was explored. Indeed, the levels of aggression was similar in vehicle and Ex4 treated mice consuming HFD. In humans, there were no associations between polymorphisms of the GLP-1R genes and overt aggression. Overall, GLP-1 signaling suppresses acquisition of aggressive behaviors via central neurotransmission and additional studies exploring this link are warranted.

A meta-analysis on shared and distinct neural correlates of the decision-making underlying altruistic and retaliatory punishment

Individuals who violate social norms will most likely face social punishment sanctions. Those sanctions are based on different motivation aspects, depending on the context. Altruistic punishment occurs if punishment aims to re‐establish the social norms even at cost for the punisher. Retaliatory punishment is driven by anger or spite and aims to harm the other. While neuroimaging research highlighted the neural networks supporting decision‐making in both types of punishment in isolation, it remains unclear whether they rely on the same or distinct neural systems. We ran an activation likelihood estimation meta‐analysis on functional magnetic resonance imaging data on 24 altruistic and 19 retaliatory punishment studies to investigate the neural correlates of decision‐making underlying social punishment and whether altruistic and retaliatory punishments share similar brain networks. Social punishment reliably activated the bilateral insula, inferior frontal gyrus, midcingulate cortex (MCC), and superior and medial frontal gyri. This network largely overlapped with activation clusters found for altruistic punishment. However, retaliatory punishment revealed only one cluster in a posterior part of the MCC, which was not recruited in altruistic punishment. Our results support previous models on social punishment and highlight differential involvement of the MCC in altruistic and retaliatory punishments, reflecting the underlying different motivations.

Psychosocial Factors Predict the Level of Aggression of People with Drug Addiction: A Machine Learning Approach

This study aimed to identify the relevant psychosocial factors that can predict the aggression in people with drug addiction. A total of 896 male participants (Mean_age = 38.30 years) completed the survey. Gradient boosting regression, a machine learning algorithm, was used to find the relevant psychosocial variables, such as psychological security, psychological capital, interpersonal trust and alexithymia, that may be significantly related to aggressive behavior. Results showed that the five most important factors in the prediction of aggression are interpersonal trust, psychological security, psychological capital, parental conflict and alexithymia. A high level of interpersonal trust, psychological security and psychological capital can predict a low level of aggression in people with drug addiction, while a high level of parental conflict and alexithymia can predict a high level of aggression. Overall, the findings highlight the need to focus interventions according to the relation between these psychosocial factors and aggression in order to decrease violence.

Punch-Drunk or Drunken Boxing? The Etiology of Alcohol-Related Physical Violence through Adolescence and Young Adulthood

BACKGROUND

Alcohol-related physical violence (ARPV) can be a causal consequence of alcohol consumption, but only for specific individuals (e.g., those predisposed to violence). Studies have not accounted for the shared etiology explaining comorbidity between alcohol use and violent behavior as a potential third-variable explanation of ARPV. The current study examined genetically-informed associations between ARPV, heavy alcohol use (HAU) and overall physical violence (OPV) in adolescence and young adulthood, by testing two proposed theories of ARPV processes (HAU causes ARPV, causal relationships depend upon OPV) and how overarching shared covariance may account for these associations.

METHODS

Using the twin and sibling subsample from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a series of biometric models tested hypotheses individually in adolescence and young adulthood. This included estimating bivariate Cholesky and direction-of-causality models, and trivariate Cholesky, independent pathway, and common pathway models.

RESULTS

HAU had a causal effect on ARPV in adolescence and young adulthood. This effect was not moderated by OPV at either developmental stage. A shared etiology or common latent factor did not explain associations between ARPV, OPV, and HAU, even though ARPV strongly covaried independently with HAU and with OPV. Finally, OPV also had a causal effect on ARPV in adolescence, and in young adulthood for adolescent-onset drinkers.

CONCLUSIONS

Causal theories of ARPV still hold when accounting for shared genetic and environmental variance. Further research on the exact role of violence (predispositions, environmental contexts) is required, as both phenotypes substantially (and separately) explain influences driving ARPV.

Supplemental data for this article is available online at https://doi.org/10.1080/10826084.2021.1887244.

Revenge is sweet: Investigation of the effects of Approach-Motivated anger on the RewP in the motivated anger delay (MAD) paradigm

Past research has found that neural activity associated with feedback processing is enhanced by positive approach-motivated states. However, no past work has examined how reward processing changes in the context of revenge. Using a novel aggression paradigm, we sought to explore the influence of approach-motivated anger on neural responses to feedback indicating the opportunity to seek revenge against an offending opponent by examining the reward positivity (RewP), an event-related potential indexing performance feedback. In Experiment 1, after receiving insulting feedback from an opponent, participants played a reaction time game with three trial types: revenge trials, aggravation trials, and no-consequence trials. Results revealed that RewP amplitudes were larger to revenge trial win feedback than no-consequence trial win feedback or revenge trial loss feedback. RewP amplitudes were larger to both aggravation trial win and loss feedback than on no-consequence trials. Experiment 2 examined the influence of approach-motivated anger during the acquisition of rewards on the RewP without the possibility of retribution from the offending individual. Participants played a reaction time game similar to Experiment 1, except instead of giving or receiving noise blasts, participants could win money from the insulter (revenge trials) or a neutral-party (e.g., bank). Results indicated that revenge wins elicited larger RewP amplitudes than bank wins. These results suggest that anger enhances revenge-related RewP amplitudes to obtaining revenge opportunities and further aggravation wins or losses. Anger appears to enhance the pleasurable feelings of revenge.

Neural mechanisms of the rejection-aggression link

Social rejection is a painful event that often increases aggression. However, the neural mechanisms of this rejection–aggression link remain unclear. A potential clue may be that rejected people often recruit the ventrolateral prefrontal cortex’s (VLPFC) self-regulatory processes to manage the pain of rejection. Using functional MRI, we replicated previous links between rejection and activity in the brain’s mentalizing network, social pain network and VLPFC. VLPFC recruitment during rejection was associated with greater activity in the brain’s reward network (i.e. the ventral striatum) when individuals were given an opportunity to retaliate. This retaliation-related striatal response was associated with greater levels of retaliatory aggression. Dispositionally aggressive individuals exhibited less functional connectivity between the ventral striatum and the right VLPFC during aggression. This connectivity exerted a suppressing effect on dispositionally aggressive individuals’ greater aggressive responses to rejection. These results help explain how the pain of rejection and reward of revenge motivate rejected people to behave aggressively.

Neural networks of aggression: ALE meta-analyses on trait and elicited aggression

There is considerable evidence that emotion dysregulation and self-control impairments lead to escalated aggression in populations with psychiatric disorders. However, convergent quantitative evidence on the neural network explaining how aggression arises is still lacking. To address this gap, peak activations extracted from extant functional magnetic resonance imaging (fMRI) studies were synthesized through coordinate-based meta-analyses. A systematic search in the PubMed database was conducted and 26 fMRI studies met the inclusion criteria. Three separate activation likelihood estimation (ALE) meta-analyses were performed on (1) individual differences in trait aggression (TA) studies, (2) individual differences in TA studies examining executive functioning, and (3) elicited aggression (EA) studies across fMRI behavioral paradigms. Ensuing clusters from ALE meta-analyses were further treated as seeds for follow-up investigations on consensus connectivity networks (CCN) delineated from meta-analytic connectivity modeling (MACM) and resting-state functional connectivity (RSFC) to further characterize their physiological functions. Finally, we obtained a data-driven functional characterization of the ensuing clusters and their networks. This approach offers a boarder view of the ensuing clusters using a boarder network perspective. In TA, aberrant brain activations were found only in the right precuneus. Follow-up analyses revealed that the precuneus seed was within the frontal-parietal network (FPN) associated with action inhibition, visuospatial processing and higher-level cognition. With further restricting to only experiments examining executive functioning, convergent evidence was found in the right rolandic operculum (RO), midcingulate cortex (MCC), precentral gyrus (PrG) and precuneus. Follow-up analyses suggested that RO, MCC and PrG may belong to a common cognitive control network, while the MCC seems to be the hub of this network. In EA, we only revealed a convergent region in the left postcentral gyrus. Follow-up CCN analyses and functional characterizations suggested that this region may also belong to the same cognitive control network found in the TA sub-analysis. Our results suggested that escalated aggression arises from abnormal precuneus activities within the FPN, disrupting the recruitment of other large-scale networks such as adaptive cognitive control network. Consequently, failure to recruit such a network results in an inability to generate adaptive responses, increasing the likelihood of acting aggressively.