Imaging Violence in Schizophrenia: A Systematic Review and Critical Discussion of the MRI Literature

Peak alpha frequency and electroencephalographic microstates are correlated with aggression in schizophrenia

Large scale retrospective studies have shown an association between schizophrenia and risk of violence. Overall, this increase in risk is small and does not justify or support stigmatizing public perceptions or media depictions of people with schizophrenia. Nonetheless, in some situations, some symptoms of schizophrenia can increase the risk of violent behavior. Prediction of this behavior would allow high impact preventive interventions. However, to date the neurobiological correlates of violent behavior in schizophrenia are not well understood, precluding the development of prognostic biomarkers. We used electroencephalography to measure alpha activity and microstates from 31 patients with schizophrenia and 18 age matched controls. Participants also completed multiple assessments of current aggressive tendencies and their lifetime history of aggressive acts. We found that individual alpha peak frequency was negatively correlated with aggression scores in both patients and controls (largest Spearman's r = -0.45). Furthermore, this result could be replicated in data taken from a single frontal channel suggesting that this may be possible to obtain in routine clinical settings (largest Spearman's r = -0.40). We also found that transitions between microstates corresponding to auditory and visual networks were inversely correlated with aggression scores. Finally, we found that, within patients, aggression was correlated with the degree of randomness between microstate transitions. This suggests that aggression is related to inappropriate switching between large scale brain networks and subsequent failure to appropriately integrate complicated environmental and internal stimuli. By elucidating some of the electrophysiological correlates of aggression, these data facilitate the development of prognostic biomarkers.

Brain structural alterations associated with impulsiveness in male violent patients with schizophrenia

BACKGROUND

Violence in schizophrenia (SCZ) is a phenomenon associated with neurobiological factors. However, the neural mechanisms of violence in patients with SCZ are not yet sufficiently understood. Thus, this study aimed to explore the structural changes associated with the high risk of violence and its association with impulsiveness in patients with SCZ to reveal the possible neurobiological basis.

METHOD

The voxel-based morphometry approach and whole-brain analyses were used to measure the alteration of gray matter volume (GMV) for 45 schizophrenia patients with violence (VSC), 45 schizophrenia patients without violence (NSC), and 53 healthy controls (HC). Correlation analyses were used to examine the association of impulsiveness and brain regions associated with violence.

RESULTS

The results demonstrated reduced GMV in the right insula within the VSC group compared with the NSC group, and decreased GMV in the right temporal pole and left orbital part of superior frontal gyrus only in the VSC group compared to the HC group. Spearman correlation analyses further revealed a positive correlation between impulsiveness and GMV of the left superior temporal gyrus, bilateral insula and left medial orbital part of the superior frontal gyrus in the VSC group.

CONCLUSION

Our findings have provided further evidence for structural alterations in patients with SCZ who had engaged in severe violence, as well as the relationship between the specific brain alterations and impulsiveness. This work provides neural biomarkers and improves our insight into the neural underpinnings of violence in patients with SCZ.

Machine Learning for prediction of violent behaviors in schizophrenia spectrum disorders: a systematic review

Background

Schizophrenia spectrum disorders (SSD) can be associated with an increased risk of violent behavior (VB), which can harm patients, others, and properties. Prediction of VB could help reduce the SSD burden on patients and healthcare systems. Some recent studies have used machine learning (ML) algorithms to identify SSD patients at risk of VB. In this article, we aimed to review studies that used ML to predict VB in SSD patients and discuss the most successful ML methods and predictors of VB.

Methods

We performed a systematic search in PubMed, Web of Sciences, Embase, and PsycINFO on September 30, 2023, to identify studies on the application of ML in predicting VB in SSD patients.

Results

We included 18 studies with data from 11,733 patients diagnosed with SSD. Different ML models demonstrated mixed performance with an area under the receiver operating characteristic curve of 0.56-0.95 and an accuracy of 50.27-90.67% in predicting violence among SSD patients. Our comparative analysis demonstrated a superior performance for the gradient boosting model, compared to other ML models in predicting VB among SSD patients. Various sociodemographic, clinical, metabolic, and neuroimaging features were associated with VB, with age and olanzapine equivalent dose at the time of discharge being the most frequently identified factors.

Conclusion

ML models demonstrated varied VB prediction performance in SSD patients, with gradient boosting outperforming. Further research is warranted for clinical applications of ML methods in this field.

Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium

Background

Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome.

Methods

This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale.

Results

Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control.

Conclusions

This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.

Neuroanatomical correlates of aggressiveness: a case-control voxel- and surface-based morphometric study

Aggression occurs across the population ranging on a symptom continuum. Most previous studies have used magnetic resonance imaging in clinical/forensic samples, which is associated with several confounding factors. The present study examined structural brain characteristics in two healthy samples differing only in their propensity for aggressive behavior. Voxel- and surface-based morphometry (SBM) analyses were performed on 29 male martial artists and 32 age-matched male controls. Martial artists had significantly increased mean gray matter volume in two frontal (left superior frontal gyrus and bilateral anterior cingulate cortex) and one parietal (bilateral posterior cingulate gyrus and precuneus) brain clusters compared to controls (whole brain: p < 0.001, cluster level: family-wise error (FWE)-corrected). SBM analyses revealed a trend for greater gyrification indices in martial artists compared to controls in the left lateral orbital frontal cortex and the left pars orbitalis (whole brain: p < 0.001, cluster level: FWE-corrected). The results indicate brain structural differences between martial artists and controls in frontal and parietal brain areas critical for emotion processing/inhibition of emotions as well as empathic processes. The present study highlights the importance of studying healthy subjects with a propensity for aggressive behavior in future structural MRI research on aggression.

Aberrant brain structure in patients with schizophrenia and violence: A meta-analysis

Previous studies have indicated that schizophrenia is associated with an increased risk of violence, which may constitute a public health concern, leading to poor treatment outcomes and stigmatization of patients. Investigating brain structural features of violence in schizophrenia could help us understand its specific pathogenesis and find effective biomarkers. Our study aimed at identifying reliable brain structural changes associated with violence in patients with schizophrenia by conducting a meta-analysis and meta-regression of magnetic resonance imaging studies. Specific brain changes in patients with schizophrenia and violence (VSZ) were studied, compared with patients with schizophrenia and violence (VSZ), patients with non-violent schizophrenia (NVSZ), and individuals with a history of violence only and health controls. Primary outcomes revealed that there was no significant difference of gray matter volume between patients with VSZ and patient with NVSZ. Compared with controls, patients with VSZ exhibited decreased gray matter volume in the insula, the superior temporal gyrus (STG), the left inferior frontal gyrus, the left parahippocampus, and the right putamen. Compared with individuals with a history of violence only, patients with VSZ exhibited decreased volume in the right insula and the right STG. Meta-regression analysis revealed a negative correlation between the duration of schizophrenia and the volume of the right insula in patients with VSZ. These findings may suggest a shared neurobiological basis for both violence and psychiatric symptoms. The impaired frontotemporal-limbic network may serve as a neurobiological basis for higher prevalence of violent behaviour in patients with schizophrenia. However, it is important to note that these changes are not unique to patients with VSZ. Further investigation is needed to explore the neural mechanism that drive the interaction between violent behaviour and specific aggression-related dimensions of schizophrenia.

Neurocognitive Suicide and Homicide Markers in Patients with Schizophrenia Spectrum Disorders: A Systematic Review

Suicide and homicide are considered important problems in public health. This study aims to identify the cognitive performance of suicidal and homicidal behaviors in people with schizophrenia spectrum disorders, as well as examining whether there are shared neuropsychological mechanisms. A systematic review of the recent literature was carried out from September 2012 to June 2022 using the Medline (via PubMed), Scopus, Embase, and Cochrane databases. Among the 870 studies initially identified, 23 were finally selected (15 related to suicidal behaviors and 8 to homicidal behaviors). The results evidenced a relationship between impairment of cognitive performance and homicidal behavior; meanwhile, for suicidal behaviors, no consistent results were found. High neuropsychological performance seems to act as a protective factor against violent behavior in people with schizophrenia spectrum disorders, but not against suicidal behavior; indeed, it can even act as a risk factor for suicidal behavior. To date, there is insufficient evidence that shared neurocognitive mechanisms exist. However, processing speed and visual memory seem to be affected in the presence of both behaviors.

Plasma neurofilament light chain protein is not increased in forensic psychiatric populations: a pilot study

Introduction

Neurofilament light chain protein (NfL) is a fluid biomarker of neural injury measurable in cerebrospinal fluid and blood. Patients with different neurodegenerative disorders and mild traumatic brain injury display elevated levels of NfL. However, so far, elevated levels of NfL have not been demonstrated in persons with psychiatric disorders. To our knowledge, the occurrence of NfL in the blood has not previously been studied in persons undergoing forensic psychiatric assessment or persons treated in forensic mental health services. Supposedly, these persons suffer from experiences and conditions with a higher risk of neural injury than other psychiatric patients.

Methods

In this pilot study, we investigated plasma levels of NfL in 20 persons undergoing forensic psychiatric assessment and 20 patients at a forensic psychiatric hospital. NfL values were compared with control groups of healthy individuals matched for age and sex.

Results

The prevalence of increased NfL in both forensic groups was low and did not differ compared with the controls. However, some persons undergoing forensic psychiatric assessment showed slightly elevated values.

Discussion

The slightly elevated values were observed in the group investigated closer in time to the index crime, when elevated NfL levels could be expected to be more prevalent due to acute conditions from the time of the offense. This gives reason to look further into this group.

Abnormalities in electroencephalographic microstates among violent patients with schizophrenia

Schizophrenia is often associated with a remarkably increased risk of violence, which has become a public health concern and brought a great economic burden. Recent studies have reported changes in the electroencephalograms (EEG) of patients with schizophrenia. The evidence for an association between EEG and violence in patients with schizophrenia is not conclusive. This study aimed to investigate EEG microstates in violent patients with schizophrenia. Forty-three violent patients with schizophrenia (the VS group) and 51 non-violent patients with schizophrenia (the NVS group) were included, and their EEG microstates were recorded using 21-Channel EEG recordings. The two groups were compared for differences of four microstate classes (A-D) with regards to three microstate parameters (duration, occurrence, and coverage). Compared with the NVS group, the VS group exhibited increased duration, occurrence, and coverage of microstate class A and decreased occurrence of microstate class B. The VS group also had lower probabilities of transitions from "B to C" and from "C to B", as compared with the NVS group. In addition, the MOAS score was positively correlated with the duration, occurrence, and coverage of microstate A. The present study found an abnormal pattern of EEG microstates in violent patients with schizophrenia, which might help clinicians identify patients with schizophrenia who might engaged in violence as well as develop intervention strategies at an early stage.

Effective Connectivity Between the Orbitofrontal Cortex and the Precuneus Differentiates Major Psychiatric Disorders: Results from a Transdiagnostic Spectral DCM Study

BACKGROUND & OBJECTIVE

We have previously identified aberrant connectivity of the left precuneus, ventrolateral prefrontal cortex, anterior cingulate cortex, and anterior insula in patients with either a paranoid (schizophrenia), or a depressive syndrome (both unipolar and bipolar). In the current study, we attempted to replicate and expand these findings by including a healthy control sample and separating the patients in a depressive episode into two groups: unipolar and bipolar depression. We hypothesized that the connections between those major nodes of the resting state networks would demonstrate different patterns in the three patient groups compared to the healthy subjects.

METHODS

Resting-state functional MRI was performed on a sample of 101 participants, of which 26 patients with schizophrenia (current psychotic episodes), 24 subjects with Bipolar Disorder (BD), 33 with Major Depressive Disorder (MDD) (both BD and MDD patients were in a current depressive episode), and 21 healthy controls. Spectral Dynamic Causal Modeling was used to calculate the coupling values between eight regions of interest, including the anterior precuneus (PRC), anterior hippocampus, anterior insula, angular gyrus, lateral Orbitofrontal Cortex (OFC), middle frontal gyrus, planum temporale, and anterior thalamus.

RESULTS & CONCLUSION

We identified disturbed effective connectivity from the left lateral orbitofrontal cortex to the left anterior precuneus that differed significantly between unipolar depression, where the influence was inhibitory, and bipolar depression, where the effect was excitatory. A logistic regression analysis correctly classified 75% of patients with unipolar and bipolar depression based solely on the coupling values of this connection. In addition, patients with schizophrenia demonstrated negative effective connectivity from the anterior PRC to the lateral OFC, which distinguished them from healthy controls and patients with major depression. Future studies with unmedicated patients will be needed to establish the replicability of our findings.

Correlation Between Aggressive Behavior and Impulsive and Aggressive Personality Traits in Stable Patients with Schizophrenia

Purpose

To explore the correlation between aggressive behavior and impulsive and aggressive personality traits in inpatients with schizophrenia.

Methods

In total, 367 inpatients with schizophrenia were divided into two groups: the aggressive group and the non-aggressive group. We assessed inpatients' psychotic symptoms as well as their aggressive and impulsive personality traits using the Positive and Negative Symptom Scale, the Barratt Impulsiveness Scale, and the Buss-Perry Aggression Questionnaire.

Results

Compared with the scores of inpatients in the non-aggressive group, the total Buss-Perry Aggression Questionnaire, subscale, and Barratt Impulsiveness Scale behavioral factor scores in those in the aggressive group were higher (p < 0.05). The results of logistic regression analysis suggested that a high Positive and Negative Symptom Scale positive factor score (odds ratio = 1.07) and a high Buss-Perry Aggression Questionnaire physical aggression score (odds ratio = 1.02) were risk factors for aggressive behavior.

Conclusion

Hospitalized patients with schizophrenia with more severe positive symptoms and aggressive traits may be more prone to aggressive behavior.

Prediction of violence in male schizophrenia using sMRI, based on machine learning algorithms

BACKGROUND

Violent behavior in patients with schizophrenia (SCZ) is a major social problem. The early identification of SCZ patients with violence can facilitate implementation of targeted intervention.

METHODS

A total of 57 male SCZ patients were recruited into this study. The general linear model was utilized to compare differences in structural magnetic resonance imaging (sMRI) including gray matter volume, cortical surface area, and cortical thickness between 30 SCZ patients who had exhibited violence and 27 SCZ patients without a history of violence. Based on machine learning algorithms, the different sMRI features between groups were integrated into the models for prediction of violence in SCZ patients.

RESULTS

After controlling for the whole brain volume and age, the general linear model showed significant reductions in right bankssts thickness, inferior parietal thickness as well as left frontal pole volume in the patients with SCZ and violence relative to those without violence. Among seven machine learning algorithms, Support Vector Machine (SVM) have better performance in differentiating patients with violence from those without violence, with its balanced accuracy and area under curve (AUC) reaching 0.8231 and 0.841, respectively.

CONCLUSIONS

Patients with SCZ who had a history of violence displayed reduced cortical thickness and volume in several brain regions. Based on machine learning algorithms, structural MRI features are useful to improve predictive ability of SCZ patients at particular risk of violence.

Child abuse and aggressiveness in individuals diagnosed with schizophrenia in Lebanon

OBJECTIVES

To identify individual and clinical risk factors of aggressiveness, including exposure to different forms of childhood trauma, in a sample of Lebanese patients with schizophrenia.

METHODS

A total of 131 patients diagnosed with schizophrenia participated in this cross-sectional study.

RESULTS

Higher physical (Beta = 0.24, p < 0.001) and sexual (Beta = 0.29, p = 0.003) abuse, alcohol drinking (Beta = 1.46, p = 0.008), having a history of head trauma (Beta = 1.10, p = 0.041), and male gender (Beta = -1.59, p = 0.009) were significantly associated with higher mean aggression scores.

PRACTICAL IMPLICATIONS

Our investigation of the factors linked to aggressiveness in patients with schizophrenia complement those of earlier findings, showing that the relationship between interacting individual and environmental risk factors and later aggressiveness is quite complex, and needs further longitudinal and prospective studies.

The age of violence: Mapping brain age in psychosis and psychopathy

Young chronological age is one of the strongest predictors for antisocial behaviour in the general population and for violent offending in individuals with psychotic disorders. An individual's age can be predicted with high accuracy using neuroimaging and machine-learning. The deviation between predicted and chronological age, i.e., brain age gap (BAG) has been suggested to reflect brain health, likely relating partly to neurodevelopmental and aging-related processes and specific disease mechanisms. Higher BAG has been demonstrated in patients with psychotic disorders. However, little is known about the brain-age in violent offenders with psychosis and the possible associations with psychopathy traits. We estimated brain-age in 782 male individuals using T1-weighted MRI scans. Three machine learning models (random forest, extreme gradient boosting with and without hyper parameter tuning) were first trained and tested on healthy controls (HC, n = 586). The obtained BAGs were compared between HC and age matched violent offenders with psychosis (PSY-V, n = 38), violent offenders without psychosis (NPV, n = 20) and non-violent psychosis patients (PSY-NV, n = 138). We ran additional comparisons between BAG of PSY-V and PSY-NV and associations with Positive and Negative Syndrome Scale (PANSS) total score as a measure of psychosis symptoms. Psychopathy traits in the violence groups were assessed with Psychopathy Checklist-revised (PCL-R) and investigated for associations with BAG. We found significantly higher BAG in PSY-V compared with HC (4.9 years, Cohen'sd = 0.87) and in PSY-NV compared with HC (2.7 years, d = 0.41). Total PCL-R scores were negatively associated with BAG in the violence groups (d = 1.17, p < 0.05). Additionally, there was a positive association between psychosis symptoms and BAG in the psychosis groups (d = 1.12, p < 0.05). While the significant BAG differences related to psychosis and not violence suggest larger BAG for psychosis, the negative associations between BAG and psychopathy suggest a complex interplay with psychopathy traits. This proof-of-concept application of brain age prediction in severe mental disorders with a history of violence and psychopathy traits should be tested and replicated in larger samples.

Aggression, Alexithymia and Sense of Coherence in a Sample of Schizophrenic Outpatients

Schizophrenia elevates the risk for aggressive behavior, and there is a need to better understand the associated variables predicting aggression for treatment and prevention purposes. The aim of the present study is to determine the relationship between alexithymia, sense of coherence and aggressive behavior in a sample of schizophrenic outpatients. Using a correlational research design, standardized self-report questionnaires assessed aggression (brief aggression questionnaire—BAQ), alexithymia (Toronto Alexithymia Scale—TAS) and sense of coherence (sense of coherence questionnaire—SOC) in a sample of 100 schizophrenic outpatients in clinical remission. Participants reported high levels of aggression and alexithymia along with reduced sense of coherence. Significant negative correlations were evidenced among scores on the SOC scale (p < 0.001) with both the TAS as well as with the BAQ scales. However, a positive correlation (p < 0.001) was observed between the TAS and BAQ scales. Regression indicated that 27% of the variation in the BAQ rating was explained by the TAS, while an additional 17.8% was explained by the sense of coherence. The difficulty identifying feelings of alexithymia and the comprehensibility and manageability components of sense of coherence significantly predicted anger, hostility and physical aggression. Sense of coherence mediated the relationship between alexithymia and aggression. From the path analysis, comprehensibility emerged as the key factor counterbalancing alexithymic traits and aggressive behaviors, and manageability effectuated higher anger control. The findings hold practical implications for the treatment and rehabilitation of schizophrenic patients.

Increased cingulo-orbital connectivity is associated with violent behaviours in schizophrenia

OBJECTIVE

Although schizophrenia patients are at a heightened risk of exhibiting violent behaviours compared to the general population, few functional neuroimaging studies have explored the aberrant neurocircuitry underpinning such behaviours. This study aimed to identify disrupted resting-state activity and functional connectivity in schizophrenia patients with a history of violence.

METHODS

Resting state functional magnetic resonance imaging data was collected from 62 schizophrenia patients and 25 healthy controls. Voxel-wise analyses of fractional amplitude of low frequency fluctuations (fALFF) were implemented to investigate disrupted regional patterns of spontaneous brain activity. Brain regions which yielded significant differences between groups were subsequently used as data-driven seeds for functional connectivity analyses. Finally, significant alterations (activity and connectivity) were correlated with lifetime violent behaviours.

RESULTS

When compared to healthy controls, schizophrenia patients exhibited reduced fALFF in multiple brain regions including the (subgenual) anterior cingulate cortex (ACC), posterior cingulate cortex, precuneus cortex and left lateral orbitofrontal cortex (OFC). Seed-to-voxel analyses yielded significantly enhanced connectivity between the ACC and left OFC. The heightened functional connectivity between the latter two regions predicted the number of violent behaviours reported by schizophrenia patients.

CONCLUSION

The current study demonstrated that the functional connectivity of brain regions associated with emotion regulation is impaired in schizophrenia and associated with violent antecedents among patients. This result is consistent with predominant theoretical models proposing that the OFC plays a critical role in the neurobiology of violence.

Associations between amygdala nuclei volumes, psychosis, psychopathy, and violent offending

The amygdala is involved in fear perception and aggression regulation, and smaller volumes have been associated with psychotic and non-psychotic violence. We explored the relationship between amygdala nuclei volumes in violent offenders with and without psychosis, and the association to psychopathy traits. 3T MRI scans (n = 204, males, 18-66 years) were obtained from psychotic violent offenders (PSY-V, n = 29), non-psychotic violent offenders (NPV, n = 19), non-violent psychosis patients (PSY-NV, n = 67), and healthy controls (HC, n = 89). Total amygdala and 9 amygdala nuclei volumes were obtained with FreeSurfer. Psychopathy traits were measured with the Psychopathy Checklist-revised (PCL-R). Multivariate analyses explored diagnostic differences in amygdala nuclei volumes and associations to psychosis, violence, and psychopathy traits. PSY-V had a smaller basal nucleus, anterior amygdaloid area, and cortical amygdalar transition area (CATA), whereas PSY-NV had a smaller CATA than HC. Volumes in NPV did not differ from HC, and there were no associations between PCL-R total or factor scores and any of the nuclei or whole amygdala volumes. The lower volumes of amygdala nuclei involved in fear modulation, stress responses, and social interpretation may point towards some mechanisms of relevance to violence in psychosis, but the results warrant replication in larger subject samples.

Aberrant Functional Connectivity of the Orbitofrontal Cortex Is Associated With Excited Symptoms in First-Episode Drug-Naïve Patients With Schizophrenia

BACKGROUND

Schizophrenia (SZ) is associated with the highest disability rate among serious mental disorders. Excited symptoms are the core symptoms of SZ, which appear in the early stage, followed by other stages of the disease subsequently. These symptoms are destructive and more prone to violent attacks, posing a serious economic burden to the society. Abnormal spontaneous activity in the orbitofrontal cortex had been reported to be associated with excited symptoms in patients with SZ. However, whether the abnormality appears in first-episode drug-naïve patients with SZ has still remained elusive.

METHODS

A total of 56 first-episode drug-naïve patients with SZ and 27 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) and positive and negative syndrome scale (PANSS). First, differences in fractional amplitude of low-frequency fluctuations (fALFF) between first-episode drug-naïve patients with SZ and healthy controls were examined to identify cerebral regions exhibiting abnormal local spontaneous activity. Based on the fALFF results, the resting-state functional connectivity analysis was performed to determine changes in cerebral regions exhibiting abnormal local spontaneous activity. Finally, the correlation between abnormal functional connectivity and exciting symptoms was analyzed.

RESULTS

Compared with the healthy controls, first-episode drug-naïve patients with SZ showed a significant decrease in intrinsic activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and the left orbitofrontal cortex. In addition, first-episode drug-naïve patients with SZ had significantly reduced functional connectivity values between the left orbitofrontal cortex and several cerebral regions, which were mainly distributed in the bilateral postcentral gyrus, the right middle frontal gyrus, bilateral paracentral lobules, the left precentral gyrus, and the right median cingulate. Further analyses showed that the functional connectivity between the left orbitofrontal cortex and the left postcentral gyrus, as well as bilateral paracentral lobules, was negatively correlated with excited symptoms in first-episode drug-naïve patients with SZ.

CONCLUSION

Our results indicated the important role of the left orbitofrontal cortex in first-episode drug-naïve patients with SZ and suggested that the abnormal spontaneous activity of the orbitofrontal cortex may be valuable to predict the occurrence of excited symptoms. These results may provide a new direction to explore the excited symptoms of SZ.

Structural Deficits in the Frontotemporal Network Associated With Psychopathic Traits in Violent Offenders With Schizophrenia

People with schizophrenia (SZ) are at increased risk of violence compared to the general population. However, the neural mechanisms of violent behavior in patients with SZ are still unclear due to the heterogeneity of the diseased population. In this study, we aimed to examine the neural correlates of violent behavior in SZ and to determine whether the structural deficits were related to psychopathic traits. A total of 113 participants, including 31 SZ patients with violent behavior (vSZ), 39 SZ patients without violent behavior (nvSZ), and 43 healthy controls (HC), completed the T1-weighted magnetic resonance imaging (MRI) scan and were analyzed using voxel-based morphometry approach. The psychopathic traits were assessed using the Psychopathy Checklist: Screening Version (PCL:SV). The results showed decreased gray matter volume (GMV) in the vSZ group in the right temporal lobe and bilateral inferior frontal gyri compared to HCs; while reduced GMV in the inferior parietal lobe, parahippocampal and orbital frontal gyri was found in the nvSZ group compared with HCs. Correlation analyses showed that psychopathic traits were negatively associated with the GMV in the right superior temporal and left fusiform gyri in the vSZ group, indicating that psychopathic traits, as reflected by the score of antisocial factor, might be related to structural deficits in the temporal lobe, which led to a propensity to violent behavior in patients with SZ. Our findings suggest that violent behavior in patients with SZ might have a personality background associated with the frontotemporal network aberrance. In future studies, we need to take a closer look at psychopathic traits for better understanding of the mechanism of interpersonal violence in patients with SZ and to explore whether the imaging findings from this study can serve as a biomarker to predict future violent behaviors and community living.

Identification of violent patients with schizophrenia using a hybrid machine learning approach at the individual level

Despite numerous risk factors associated with violence in patients with schizophrenia, predicting and preventing violent behavior is still a challenge. At present, machine learning (ML) has become a promising strategy for guiding individualized assessment. To build an effective model to predict the risk of violence in patients with schizophrenia, we proposed a hybrid ML method to improve the prediction capability in 42 violent offenders with schizophrenia and 33 non-violent patients with schizophrenia. The results revealed that the final model, which combined multimodal data, achieved the highest prediction performance with an accuracy of 90.67%. Specifically, the model, which fused three modalities of neuroimaging data, achieved a better accuracy than other fused models. In addition, the msot discriminative neuroimaging features involved in the prefrontal-temporal cognitive circuit and striatum reward system, indicating that dysfunction in cortical-subcortical circuits might be associated with high risk of violence in patients with schizophrenia. This study provides the first evidence supporting that the combination of specific multimodal neuroimaging and clinical data in ML analysis can effectively identify violent patients with schizophrenia. Furthermore, this work is crucial for the development of neuro-prediction models that could facilitate individualized treatment and interventions for violent behaviors in patients with schizophrenia.

Brain gray matter differences among forensic psychiatric patients with psychosis and incarcerated individuals without psychosis: A source-based morphometry study

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We employed source-based morphometry to examine grey matter differences in forensic psychiatric patients with psychosis versus incarcerated controls without psychosis.

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Compared to the psychotic group, the non-psychotic group demonstrated greater loading weights in the superior, transverse, and middle temporal gyrus and the anterior cingulate.

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Compared to the non-psychotic group, the psychotic group exhibited greater loading weights in the frontal pole, precuneus, basal ganglia, thalamus, parahippocampal gyrus, and visual cortex.

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Neuroimaging investigations of offenders with psychosis ought to control for the level of psychopathic traits present.

Background

While psychosis is a risk factor for violence, the majority of individuals who perpetrate aggression do not present psychotic symptoms. Pathological aggressive behavior is associated with brain gray matter differences, which, in turn, has shown a relationship with increased psychopathic traits. However, no study, to our knowledge, has ever investigated gray matter differences in forensic psychiatric patients with psychosis compared with incarcerated individuals without psychosis matched on levels of psychopathic traits. Here, we employed source-based morphometry (SBM) to investigate gray matter differences in these two populations.

Methods

We scanned 137 participants comprising two offender subgroups: 69, non-psychotic incarcerated offenders and 68, psychotic, forensic psychiatric patients. Groups showed no difference in age, race, ethnicity, handedness, and Hare Psychopathy Checklist-Revised scores. Source-based morphometry was utilized to identify spatially distinct sets of brain regions where gray matter volumes covaried between groups. SBM is a data-driven, multivariate technique that uses independent components analysis to categorize groups of voxels that display similar variance patterns (e.g., components) that are compared across groups.

Results

SBM identified four components that differed between groups. These findings indicated greater loading weights in the superior, transverse, and middle temporal gyrus and anterior cingulate in the non-psychotic versus psychotic group; greater loading weights in the basal ganglia in the psychotic versus non-psychotic group; greater loading weights in the frontal pole, precuneus, and visual cortex among psychotic versus non-psychotic offenders; and greater loading weights in the thalamus and parahippocampal gyrus in psychotic versus non-psychotic groups.

Conclusions

Two different offender groups that perpetrate violence and show comparable levels of psychopathic traits evidenced different gray matter volumes. We suggest that future studies of violent offenders with psychosis take psychopathic traits into account to refine neural phenotypes.

Strategies to solve the reverse inference fallacy in future MRI studies of schizophrenia: a review

Few advances in schizophrenia research have been translated into clinical practice, despite 60 years of serum biomarkers studies and 50 years of genetic studies. During the last 30 years, neuroimaging studies on schizophrenia have gradually increased, partly due to the beautiful prospect that the pathophysiology of schizophrenia could be explained entirely by the Human Connectome Project (HCP). However, the fallacy of reverse inference has been a critical problem of the HCP. For this reason, there is a dire need for new strategies or research "bridges" to further schizophrenia at the biological level. To understand the importance of research "bridges," it is vital to examine the strengths and weaknesses of the recent literature. Hence, in this review, our team has summarized the recent literature (1995-2018) about magnetic resonance imaging (MRI) of schizophrenia in terms of regional and global structural and functional alterations. We have also provided a new proposal that may supplement the HCP for studying schizophrenia. As postulated, despite the vast number of MRI studies in schizophrenia, the lack of homogeneity between the studies, along with the relatedness of schizophrenia with other neurological disorders, has hindered the study of schizophrenia. In addition, the reverse inference cannot be used to diagnose schizophrenia, further limiting the clinical impact of findings from medical imaging studies. We believe that multidisciplinary technologies may be used to develop research "bridges" to further investigate schizophrenia at the single neuron or neuron cluster levels. We have postulated about future strategies for overcoming the current limitations and establishing the research "bridges," with an emphasis on multimodality imaging, molecular imaging, neuron cluster signals, single transmitter biomarkers, and nanotechnology. These research "bridges" may help solve the reverse inference fallacy and improve our understanding of schizophrenia for future studies.

Aggressive Behavior and Psychiatric Inpatients: a Narrative Review of the Literature with a Focus on the European Experience

PURPOSE OF REVIEW

We summarized peer-reviewed literature on aggressive episodes perpetrated by adult patients admitted to general hospital units, especially psychiatry or emergency services. We examined the main factors associated with aggressive behaviors in the hospital setting, with a special focus on the European experience.

RECENT FINDINGS

A number of variables, including individual, historical, and contextual variables, are significant risk factors for aggression among hospitalized people. Drug abuse can be considered a trans-dimensional variable which deserves particular attention. Although mental health disorders represent a significant component in the risk of aggression, there are many factors including drug abuse, past history of physically aggressive behavior, childhood abuse, social and cultural patterns, relational factors, and contextual variables that can increase the risk of overt aggressive behavior in the general hospital. This review highlights the need to undertake initiatives aimed to enhance understanding, prevention, and management of violence in general hospital settings across Europe.

White Matter Correlates of Hostility and Aggression in the Visuospatial Function Network in Patients With Schizophrenia

Background: Violent acts in patients with schizophrenia are often associated with their hostility and aggression levels. Poor visuospatial processing has been suggested as a possible risk factor of violence in schizophrenia. However, studies investigating the relationship between hostility, aggression, and the visuospatial function have been lacking. Here, we aimed to investigate brain dysconnectivity associated with hostility and aggression in schizophrenia, particularly focusing on the visuospatial function network. Methods: Eighty-eight participants with schizophrenia and 42 healthy controls were enrolled. The visuospatial function network regions of interest were analyzed using Tract-Based Spatial Statistics. The hostility item from the Positive and Negative Syndrome Scale (PANSS), aggressive, and agitated behavior item from the Scale for the Assessment of Positive Symptoms (SAPS), and the Rey Complex Figure Test (R-CFT) were measured. Results: Among the participants with schizophrenia, the SAPS aggressive and agitated behavior scores were significantly correlated with fractional anisotropies (FAs) of the white matter regions in the splenium of the corpus callosum (CC), left posterior thalamic radiations (PTR), and left posterior corona radiata (PCR). Exploratory correlational analysis revealed significant negative correlations between FAs of the splenium of the CC and R-CFT copy and immediate recall scores. In addition, three regions including CC, PTR, and PCR that significantly correlated with the aggression scores showed significant correlations with the total PANSS scores. Conclusion: Our main finding suggests that aggression of patients with schizophrenia may be associated with poor visuospatial ability and underlying white matter dysconnectivity. These may help enhance understanding aggression in patients with schizophrenia.

Profiling the differences of gut microbial structure between schizophrenia patients with and without violent behaviors based on 16S rRNA gene sequencing

Understanding the violence behaviors in schizophrenia patients has always been the focus of forensic psychiatry. Although many studies show gut microbiota could regulate behavior, to our knowledge, no studies have profiled the gut microbiota structure in schizophrenia patients with violence. We profiled the characteristics of gut microbiota structure in 26 schizophrenia patients with violence (V.SCZ) by comparing with that of 16 schizophrenia patients without violence (NV.SCZ) under the control of confounders, and found the differences of gut microbiota structure between the two groups. Violence was assessed by the MacArthur Community Violence Instrument. Psychiatric symptoms were assessed by the Positive and Negative Syndrome Scale. The 16S rRNA gene sequencing was used to identify and relatively quantify gut microbial composition. Bioinformatics analysis was used to find differential gut microbial composition between the V.SCZ and NV.SCZ groups. Fifty-nine differential microbial taxonomic compositions were found between the two groups. Fifteen gut microbial compositions were the key microbial taxonomic compositions responsible for the differences between the V.SCZ and NV.SCZ groups, including five enriched microbial taxonomic compositions (p_Bacteroidetes, c_Bacteroidia, o_Bacteroidales, f_Prevotellaceae, s_Bacteroides_uniformis), and ten impoverished microbial taxonomic compositions (p_Actinobacteria, c_unidentified_Actinobacteria, o_Bifidobacteriales, f_ Enterococcaceae, f_Veillonellaceae, f_Bifidobacteriaceae, g_Enterococcus, g_Candidatus_Saccharimonas, g_Bifidobacterium, and s_Bifidobacterium_pseudocatenulatum). This study profiled the differences of gut microbiota between schizophrenia patients with violence and without violence. These results could enrich the etiological understanding of violence in schizophrenia and might be helpful to violence management in the future.

An overlapping pattern of cerebral cortical thinning is associated with both positive symptoms and aggression in schizophrenia via the ENIGMA consortium

BACKGROUND

Positive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample.

METHOD

To study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls.

RESULTS

The result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression.

CONCLUSION

These findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia.

Dysregulation of amino acids and lipids metabolism in schizophrenia with violence

BACKGROUND

Many studies have related biochemical characteristics to violence and have reported schizophrenia could elevated the risk of violent behaviour. However, the metabolic characteristics of schizophrenia patients with violence (V.SC) are unclear.

METHODS

To explore the metabolic characteristics of schizophrenia with violence and to identify potential biomarkers, untargeted metabolomics was performed by using gas chromatography time-of-flight mass spectrometry to analyse the plasma metabolites of fifty-three V.SC and twenty-four schizophrenia patients without violence (NV.SC). Multivariate and univariate analyses were performed to identify differential metabolites and biomarkers. Violence was assessed by the MacArthur Violence Assessment Study method. Psychiatric symptoms were assessed by the Positive and Negative Syndrome Scale.

RESULTS

Multivariate analysis was unable to distinguish V.SC from NV.SC. Glycerolipid metabolism and phenylalanine, tyrosine and tryptophan biosynthesis were the differential metabolic pathways between V.SC and NV.SC. We confirmed ten metabolites and five metabolites as metabolic biomarkers of V.SC by random forest and support vector machine analysis, respectively. The biomarker panel, including the ratio of L-asparagine to L-aspartic acid, vanillylmandelic acid and glutaric acid, yielded an area under the receiver operating characteristic curve of 0.808.

CONCLUSIONS

This study gives a holistic view of the metabolic phenotype of schizophrenia with violence which is characterized by the dysregulation of lipids and amino acids. These results might provide information for the aetiological understanding and management of violence in schizophrenia; however, this is a preliminary metabolomics study about schizophrenia with violence, which needs to be repeated in future studies.

Violent Behavior Is Associated With Emotion Salience Network Dysconnectivity in Schizophrenia

Background: Despite individuals with schizophrenia being at an elevated risk of violence compared to the general population, limited efforts have been invested in investigating the neurobiological etiology explaining the increase. Among the few studies examining functional disruptions pertaining to violent schizophrenia patients using fMRI, only one study has considered functional connectivity. The current state of knowledge does not allow to infer deficits in functional connectivity specific to distinct cognitive/emotional states that have been associated with the emergence of violence in schizophrenia, such as negative emotion processing. This study sought to identify disrupted connectivity among men with schizophrenia and a history of violence (SCZ+V), compared to men with schizophrenia without a history of violence (SCZ-V) and healthy controls, during negative emotion processing using fMRI. Methods: Twenty SCZ+V, 19 SCZ-V, and 21 healthy men were scanned while viewing negative images. Results: Negative images elicited an increased connectivity between the dorsal anterior cingulate cortex (dACC) and the bilateral rostral prefrontal cortex (rPFC), as well as a decreased functional connectivity between the frontal regions (bilateral rPFC and dACC) and the putamen and hippocampus in SCZ+V men as compared to SCZ-V men and healthy controls. Concurrently, the centrality of the dACC within the network was reduced in SCV+V subjects. Conclusions: These results suggest an inefficient integration of the information by the dACC between frontal and limbic regions in SCZ+V men during negative emotion processing and highlight the importance of the ACC in the neurobiological bases of violent behavior in schizophrenia.

Hippocampal subfield and amygdala nuclei volumes in schizophrenia patients with a history of violence

Schizophrenia (SCZ) is associated with an increased risk of violence compared to the general population. Previous studies have indicated smaller hippocampal and amygdala volumes in violent than non-violent psychotic patients^. However, little is known about volumetric differences at the subdivision level of these structures. In the present study, hippocampal subfields and amygdala nuclei volumes were estimated with FreeSurfer from 3 T MRI of SCZ patients with (SCZ-V, n = 24) and without (SCZ-NV, n = 51) a history of severe violence and 90 healthy controls (HC). Volumetric differences between groups were explored with a general linear model covarying for confounders, in addition to follow-up analyses in patient groups controlling for clinical characteristics such as antipsychotic medication, duration of illness and illicit substance use. SCZ-V had smaller total hippocampal volume and smaller CA1, HATA, fimbria, and molecular layer of DG volumes compared to HC. Total amygdala volume together with basal nucleus, accessory basal nucleus, CTA, and paralaminar nucleus volumes were smaller in SCZ-V compared to HC. In SCZ-NV, compared to HC, the observed smaller volumes were limited to basal and paralaminar nucleus. There were no significant differences in hippocampal subfield and amygdala nuclei volumes between SCZ-V and SCZ-NV. Follow-up analyses showed that the results in patient groups were not affected by clinical characteristics. The results suggest that smaller hippocampal subfield and amygdala nuclei volumes may be relevant to violence risk in SCZ. However, the neurobiological signature of violence in SCZ should be further investigated in larger cohorts.

Volumetric Abnormalities in Violent Schizophrenia Patients on the General Psychiatric Ward

BACKGROUND

In recent years, neuroimaging has been used increasingly to explore the biological underpinnings of violence carried out by schizophrenia patients (SPs). Studies have focused mostly on patients with a history of carrying out severe physical assaults, or comorbid with substance abuse/personality disorder (SA/PD). As a result, participants were unrepresentative and the interpretation of brain-structure changes was confusing. Here, we concentrated on SPs on a general psychiatric ward with a history of relatively lower violence, and individuals comorbid with SA or PD were excluded. We expected to identify the characteristics of brain morphometry in this population, and to explore whether the morphometric changes were universal.

METHODS

Forty-eight violent schizophrenia patients (VSPs), twenty-seven non-VSPs (nVSPs) and 28 nonviolent healthy controls (HCs) were investigated. Voxel-based morphometry was used to evaluate the gray matter volume (GMV) of all study participants. Whole-brain analyses were used to reveal group effects and differences between any two groups. Correlation analyses were undertaken between significant brain regions and behavioral measurements in the VSP group.

RESULTS

Patients showed a significantly smaller GMV in widespread frontal, temporal, and limbic regions compared with HCs. No region was found in which the two patient groups had significantly larger volumes compared with that in HCs. A significant decrease in the GMV of the right fusiform gyrus was found in the VSP group compared with that in the nVSP group (p = 0.004), where the GMV of this region had a negative correlation with the Physical Aggression [subscale of the Modified Overt Aggression Scale (MOAS)] or Hostility score. The VSP group showed a trend of GMV decrease in the left middle temporal cortex compared with that in the nVSP group (p = 0.077). Negative correlation was also found between the GMV of left inferior temporal gyrus/left Superior frontal gyrus, medial and the Hostility score.

CONCLUSIONS

Our results provide initial evidence demonstrating the generalizability of GMV abnormalities in SPs engaged in varying levels of violence, even when SA or PD have not been implicated. GMV reduction was correlated with only the Physical Aggression subscale score of the MOAS, suggesting that this change in brain morphology may be dependent upon different types of violent actions.

Biological Aspects of Aggression and Violence in Schizophrenia

Although the majority of patients with schizophrenia are not actually violent, an increased tendency toward violent behaviors is known to be associated with schizophrenia. There are several factors to consider when identifying the subgroup of patients with schizophrenia who may commit violent or aggressive acts. Comorbidity with substance abuse is the most important clinical indicator of increased aggressive behaviors and crime rates in patients with schizophrenia. Genetic studies have proposed that polymorphisms in the promoter region of the serotonin transporter gene and in the catechol-O-methyltransferase gene are related to aggression. Neuroimaging studies have suggested that fronto-limbic dysfunction may be related to aggression or violence. By identifying specific risk factors, a more efficient treatment plan to prevent violent behavior in schizophrenia will be possible. Management of comorbid substance use disorder may help prevent violent events and overall aggression. Currently, clozapine may be the only effective antipsychotic medication to repress aggressive behavior. With the current medical field moving toward tailored medicine, it is important to identify vulnerable schizophrenia populations and provide efficient treatment.

Inferior frontal gyrus gray matter volume is associated with aggressive behavior in schizophrenia spectrum disorders

We aimed to assess potential gray matter (GM) alterations for aggressive patterns of behavior in a sample of in- and outpatients with schizophrenia spectrum disorders. Eighty-four patients previously participating in brain volumetric studies were included. Aggression was assessed using the Modified Overt Aggression Scales (MOAS) based upon review of clinical records of the hospital register. Multiple regression analyses for total MOAS and each MOAS subscale separately were conducted correcting for age, sex, history of addiction, chlorpromazine equivalents, illness duration, and total intracranial volume. Significant effects were reported in two cases; the total MOAS scores and MOAS verbal aggression scores were associated with GM volume in left inferior frontal gyrus. From the demographic/clinical characteristics, only the number of episodes correlated with the subscales and the total MOAS scores. Our results highlight the role of GM volume in left inferior frontal gyri in patients with history of aggression. This evidence ties in well with previous data reporting involvement of these regions in response control and semantic networks.

A preliminary study of cortical morphology in schizophrenia patients with a history of violence

Clinical studies of patients with schizophrenia and a history of violence are challenging both from an ethical and practical perspective, and the neurobiological underpinnings remain largely unknown. We here present a comprehensive account of the brain cortical characteristics associated with violence in schizophrenia. We obtained 3T MRI scans and thorough clinical characterization of schizophrenia patients with a history of violence (murder, attempted murder, criminal assault, SCZ-V, n = 11), schizophrenia patients with no history of violence (SCZ-NV, n = 17), and healthy controls (HC, n = 19). Cortical thickness, area, and folding were analyzed vertex-wise across the cortical mantle (FreeSurfer). SCZ-V had significantly increased cortical folding in the visual and orbitofrontal cortex, and reduced cortical thickness within the precentral-, parietal-, temporal-, and fusiform cortex compared to SCZ-NV, as well as widespread regional thinning and increased folding compared to HC. There were no group differences in cortical area. A major limitation is the small subject sample. If replicated, the results from this pilot study suggest cortical abnormalities in areas involved in sensory processing, emotion recognition, and reward to be of importance to the neurobiology of violence in schizophrenia.