Biological Psychiatry

Aggressive behavior shows striking gender differences. Cross-cultural research shows that men are more likely to engage in physical aggression, while women tend to use indirect forms of aggressive behavior. Aggression is a multifactorial phenomenon influenced by situational, genetic, psychological and other factors. Despite being a transdiagnostic feature in numerous mental disorders, gender-specific differences and the underlying influencing factors have not yet been sufficiently investigated. Many findings originate from older publications and methodologically sound and in particular behavior-based investigations are rare. This article provides a narrative literature review that summarizes the current state of research on gender differences in aggression in selected mental disorders, including substance use disorders, psychotic disorders and borderline personality disorder. The implications for future research and the clinical practice are discussed.

While anyone can behave aggressively, some people are more prone to aggression than others. We present a neuro-cognitive model and consider several inter-individual differences that confer risk for aggression. Forms of atypical cognitive function include a hyperreactive acute threat response, poor emotion regulation, and mechanisms involved in choosing when to aggress. We show dysfunction in the neural systems mediating these functions may account for aggression in people high in psychopathy/callous unemotional traits, irritability/anger, hostility, impulsivity, and low in frustration tolerance. We then review promising interventions including psychological therapies and pharmaceuticals that might influence the neuro-cognitive underpinnings of these constructs. Although there is no overwhelming “one size fits all” approach to treating aggression, identifying the neural mechanisms implicated in these traits may improve individualized treatments.

Brain–computer interfaces (BCIs) can be used to monitor and provide real-time feedback on brain signals, directly influencing external systems, such as virtual environments (VE), to support self-regulation. We piloted a novel immersive, first-person shooting BCI-VE during which the avatars’ movement speed was directly influenced by neural activity in the supplementary motor area (SMA). Previous analyses revealed behavioral and localized neural effects for active versus reduced contingency neurofeedback in a randomized controlled trial design. However, the modeling of neural dynamics during such complex tasks challenges traditional event-related approaches. To overcome this limitation, we employed a data-driven framework utilizing group-level independent networks derived from BOLD-specific components of the multi-echo fMRI data obtained during the BCI regulation. Individual responses were estimated through dual regression. The spatial independent components corresponded to established cognitive networks and task-specific networks related to gaming actions. Compared to reduced contingency neurofeedback, active regulation induced significantly elevated fractional amplitude of low-frequency fluctuations (fALFF) in a frontoparietal control network, and spatial reweighting of a salience/ventral attention network, with stronger expression in SMA, prefrontal cortex, inferior parietal lobule, and occipital regions. These findings underscore the distributed network engagement of BCI regulation during a behavioral task in an immersive virtual environment.

Psychopathy is one of the greatest risk factors for serious and persistent violence. In order to detect its neurobiological substrates, we examined 39 male psychopathic subjects and matched controls using structural MR imaging and the Psychopathy Check-List (PCL-R). Individual brain region volumes were calculated using the Julich-Brain and AAL3 atlases. Associations of region volumes with the PCL-R dimensions among psychopathic subjects and differences between both groups were analysed. PCL-R factor 2 assessing lifestyle and antisocial behaviour showed in the psychopathic sample negative associations with volumes of several regions, including pons, nuclei of basal ganglia, thalamus, basal forebrain (CH-4), cerebellar regions and areas in orbitofrontal, dorsolateral-frontal and insular cortices. These findings suggest dysfunctions in specific frontal-subcortical circuits, which are known to be relevant for behavioral control. In contrast, the interpersonal-affective PCL-R factor 1 showed only weak positive and negative associations with orbitofrontal, dorsolateral-frontal and left hippocampal areas (CA1, subiculum), among others, indicating that involved brain regions might be affected to a variable degree in different individuals. The group comparison yielded a significantly reduced total brain volume in psychopathic subjects relative to controls, while pronounced regional focuses of volume differences were found only in the right subiculum, suggesting an interindividually variable pattern of structural deviations in the brains of psychopathic subjects. In conclusion, these findings are compatible with the dimensionality of the PCL-R construct, and suggest a particulary strong association of antisocial behavior to smaller volumes in widespread subcortical-cortical brain regions.

Physiological responses derived from audiovisual perception during assisted driving are associated with the regulation of the autonomic nervous system (ANS), especially in emergencies. However, the interaction of event-related brain activity and the ANS regulating peripheral physiological indicators (i.e., heart rate variability (HRV) and respiratory rate) is unknown, making it difficult to study the neural mechanism during takeover from the assistance system. In this paper, we established a mapping between the ANS regulation and brain activations of driving events in function magnetic resonance imaging (fMRI)-conditioned audiovisual warnings experiment to add physiological fingerprints for assisted driving. Firstly, we used the general linear model (GLM) to obtain brain activation clusters of driving events and brain activation clusters of peripheral physiological indicators in different frequency bands. Secondly, we redefined the input parameters based on the driving events to calculate the GLM to obtain the brain activation clusters of event-related physiological indicators. Finally, the relationship between the main activation clusters of driving events and the activation of event-related physiological indicators was quantified by the statistical test of the mean-time course of voxels within the region. The results showed that related areas of the brain responsible for movement, visceral autonomic regulation, auditory, and vision actively responded to the audiovisual warnings of automatic driving. The mappings created using them revealed that the correlation between driving event-related activation of brain regions and respiration worked at the onset of audiovisual warnings, especially between the intermediate (IM) and low frequency (LF) bands. For pre-emergency and takeover in audiovisual warnings, the correlations of HRV were dominant, with significant differences among LF, IM and high frequency (HF) bands. At different periods of audiovisual warnings, HRV and respiration play different roles in physiological fingerprints. Compared to respiratory indicators, HRV has higher sensitivity to emergency situations. This study investigates the interaction between driving-related network activity and ANS regulation, revealing the profound connection between driving behavior and neural activity, and contributing to the research of driving assistance systems.

Background Emotion regulation mediated by cognitive reappraisal can induce activity changes in brain areas and fluctuations in peripheral physiological indicators regulated by the autonomic nervous system (ANS). However, little is known about the relationship between emotional and ANS regulation in major depressive disorder (MDD). In specific, the intermediate band (IM; 0.12–0.18 Hz) is thought to reflect relaxation and emotion processing.