119 research outputs found

    Aggression and Quantitative MRI Measures of Caudate in Patients With Chronic Schizophrenia or Schizoaffective Disorder

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    Caudate dysfunction is implicated in schizophrenia. However, little is known about the relationship between aggression and caudate volumes. Forty-nine patients received magnetic resonance imaging scanning in a double-blind treatment study in which aggression was measured. Caudate volumes were computed using a semiautomated method. The authors measured aggression with the Overt Aggression Scale and the Positive and Negative Syndrome Scale. Larger caudate volumes were associated with greater levels of aggression. The relationship between aggression and caudate volumes may be related to the iatrogenic effects of long-term treatment with typical anti-psychotic agents or to a direct effect of schizophrenic processes on the caudate

    Violent behaviour in early psychosis patients: Can we identify clinical risk profiles?

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    The objective of this study is to explore, within a sample of early psychosis patients (EPP), if subgroups regarding rate of violent behaviour (VB) against others can be identified on the basis of dynamic risk factors (treatment modifiable characteristics). In a sample of 265 EPP, treated at the Treatment and Early Intervention in Psychosis Program in Lausanne, we conducted a latent-class analysis on the basis of the main dynamic VB risk factors (substance use disorder [SUD], positive symptoms, insight, and impulsivity). VB were restricted to "serious violence" and were assessed through patients self-report, interview with relatives or forensic services and with a standardized instrument. The analysis confirmed the heterogeneity of the sample regarding rate of VB. Patients could be stratified within 4 subgroups, 3 of which were at increased risk of VB. The two groups with the highest rates of VB displayed specific clinical profiles. The first one was characterized by high levels of impulsivity, hostility, positive symptoms and SUD, and the second, by low level of insight and low social functioning. These patterns suggest that significant difficulties in social interaction may contribute to the emergence of aggressive reactions against others. Identification of EPP at increased risk of VB seems possible on the basis of dynamic risk factors. If confirmed prospectively, this could pave the way to the development of preventive strategies and specific interventions

    Quantitative MRI measures of orbitofrontal cortex in patients with chronic schizophrenia or schizoaffective disorder

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    The relationship between orbitofrontal cortex (OFC) volumes and functional domains in treatment-resistant patients with schizophrenia or schizoaffective disorder is poorly undestood. OFC dysfunction is implicated in several of the behaviors that are abnormal in schizophrenia. However, little is known about the relationship between these behaviors and OFC volumes. Forty-nine (49) patients received magnetic resonance imaging scanning as part of a double-blind treatment study in which psychiatric symptomatology, neuropsychological function, and aggression were measured. OFC volumes were manually traced on anatomical images. Psychiatric symptomatology was measured with the Positive and Negative Syndrome Scale (PANSS). Aggression was measured with the Overt Aggression Scale (OAS) and with the PANSS. Neuropsychological function was assessed using a comprehensive test battery. Larger right OFC volumes were associated with poorer neuropsychological function. Larger left OFC gray matter volumes and larger OFC white matter volumes bilaterally were associated with greater levels of aggression. These findings are discussed in the context of potential iatrogenic effects

    Neuroanatomical Abnormalities in Violent Individuals with and without a Diagnosis of Schizophrenia

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    Several structural brain abnormalities have been associated with aggression in patients with schizophrenia. However, little is known about shared and distinct abnormalities underlying aggression in these subjects and non-psychotic violent individuals. We applied a region-of interest volumetric analysis of the amygdala, hippocampus, and thalamus bilaterally, as well as whole brain and ventricular volumes to investigate violent (n = 37) and non-violent chronic patients (n = 26) with schizophrenia, non-psychotic violent (n = 24) as well as healthy control subjects (n = 24). Shared and distinct volumetric abnormalities were probed by analysis of variance with the factors violence (non-violent versus violent) and diagnosis (non-psychotic versus psychotic), adjusted for substance abuse, age, academic achievement and negative psychotic symptoms. Patients showed elevated vCSF volume, smaller left hippocampus and smaller left thalamus volumes. This was particularly the case for non-violent individuals diagnosed with schizophrenia. Furthermore, patients had reduction in right thalamus size. With regard to left amygdala, we found an interaction between violence and diagnosis. More specifically, we report a double dissociation with smaller amygdala size linked to violence in non-psychotic individuals, while for psychotic patients smaller size was linked to non-violence. Importantly, the double dissociation appeared to be mostly driven by substance abuse. Overall, we found widespread morphometric abnormalities in subcortical regions in schizophrenia. No evidence for shared volumetric abnormalities in individuals with a history of violence was found. Finally, left amygdala abnormalities in non-psychotic violent individuals were largely accounted for by substance abuse. This might be an indication that the association between amygdala reduction and violence is mediated by substance abuse. Our results indicate the importance of structural abnormalities in aggressive individuals

    Regionally Specific White Matter Disruptions of Fornix and Cingulum in Schizophrenia

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    Limbic circuitry disruptions have been implicated in the psychopathology and cognitive deficits of schizophrenia, which may involve white matter disruptions of the major tracts of the limbic system, including the fornix and the cingulum. Our study aimed to investigate regionally specific abnormalities of the fornix and cingulum in schizophrenia using diffusion tensor imaging (DTI). We determined the fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) profiles along the fornix and cingulum tracts using a fibertracking technique and a brain mapping algorithm, the large deformation diffeomorphic metric mapping (LDDMM), in the DTI scans of 33 patients with schizophrenia and 31 age-, gender-, and handedness-matched healthy controls. We found that patients with schizophrenia showed reduction in FA and increase in RD in bilateral fornix, and increase in RD in left anterior cingulum when compared to healthy controls. In addition, tract-based analysis revealed specific loci of these white matter differences in schizophrenia, that is, FA reductions and AD and RD increases occur in the region of the left fornix further from the hippocampus, FA reductions and RD increases occur in the rostral portion of the left anterior cingulum, and RD and AD increases occur in the anterior segment of the left middle cingulum. In patients with schizophrenia, decreased FA in the specific loci of the left fornix and increased AD in the right cingulum adjoining the hippocampus correlated with greater severity of psychotic symptoms. These findings support precise disruptions of limbic-cortical integrity in schizophrenia and disruption of these structural networks may contribute towards the neural basis underlying the syndrome of schizophrenia and clinical symptomatology

    Your Resting Brain CAREs about Your Risky Behavior

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    Research on the neural correlates of risk-related behaviors and personality traits has provided insight into mechanisms underlying both normal and pathological decision-making. Task-based neuroimaging studies implicate a distributed network of brain regions in risky decision-making. What remains to be understood are the interactions between these regions and their relation to individual differences in personality variables associated with real-world risk-taking.We employed resting state functional magnetic resonance imaging (R-fMRI) and resting state functional connectivity (RSFC) methods to investigate differences in the brain's intrinsic functional architecture associated with beliefs about the consequences of risky behavior. We obtained an individual measure of expected benefit from engaging in risky behavior, indicating a risk seeking or risk-averse personality, for each of 21 participants from whom we also collected a series of R-fMRI scans. The expected benefit scores were entered in statistical models assessing the RSFC of brain regions consistently implicated in both the evaluation of risk and reward, and cognitive control (i.e., orbitofrontal cortex, nucleus accumbens, lateral prefrontal cortex, dorsal anterior cingulate). We specifically focused on significant brain-behavior relationships that were stable across R-fMRI scans collected one year apart. Two stable expected benefit-RSFC relationships were observed: decreased expected benefit (increased risk-aversion) was associated with 1) stronger positive functional connectivity between right inferior frontal gyrus (IFG) and right insula, and 2) weaker negative functional connectivity between left nucleus accumbens and right parieto-occipital cortex.Task-based activation in the IFG and insula has been associated with risk-aversion, while activation in the nucleus accumbens and parietal cortex has been associated with both risk seeking and risk-averse tendencies. Our results suggest that individual differences in attitudes toward risk-taking are reflected in the brain's functional architecture and may have implications for engaging in real-world risky behaviors

    Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

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    Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies

    Differential Development of Human Brain White Matter Tracts

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    Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted ‘U-shape’), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples

    Correlations between Diffusion Tensor Imaging (DTI) and Magnetic Resonance Spectroscopy (1H MRS) in schizophrenic patients and normal controls

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    <p>Abstract</p> <p>Background</p> <p>Evidence suggests that white matter integrity may play an underlying pathophysiological role in schizophrenia. N-acetylaspartate (NAA), as measured by Magnetic Resonance Spectroscopy (MRS), is a neuronal marker and is decreased in white matter lesions and regions of axonal loss. It has also been found to be reduced in the prefrontal and temporal regions in patients with schizophrenia. Diffusion Tensor Imaging (DTI) allows one to measure the orientations of axonal tracts as well as the coherence of axonal bundles. DTI is thus sensitive to demyelination and other structural abnormalities. DTI has also shown abnormalities in these regions.</p> <p>Methods</p> <p>MRS and DTI were obtained on 42 healthy subjects and 40 subjects with schizophrenia. The data was analyzed using regions of interests in the Dorso-Lateral Prefrontal white matter, Medial Temporal white matter and Occipital white matter using both imaging modalities.</p> <p>Results</p> <p>NAA was significantly reduced in the patient population in the Medial Temporal regions. DTI anisotropy indices were also reduced in the same Medial Temporal regions. NAA and DTI-anisotropy indices were also correlated in the left medial temporal region.</p> <p>Conclusion</p> <p>Our results implicate defects in the medial temporal white matter in patients with schizophrenia. Moreover, MRS and DTI are complementary modalities for the study of white matter disruptions in patients with schizophrenia.</p
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