Objective Schizophrenia is a chronic and debilitating neuropsychiatric disorder. It has been suggested that impaired brain connectivity underlies the pathophysiology of schizophrenia. Network analysis has thus recently emerged in the field of schizophrenia research. Methods We investigated 48 schizophrenia patients and 24 healthy controls using network analysis and a machine learning method. A number of global and nodal network properties were estimated from graphs that were reconstructed using probabilistic brain tractography. These network properties were then compared between groups and used for machine learning to classify schizophrenia patients and healthy controls. Results In classifying schizophrenia patients and healthy controls via network properties, the support vector machine, random forest, naïve Bayes, and gradient boosting machine learning models showed an encouraging level of performance. The overall connectivity was revealed as the most significant contributing feature to this classification among the global network properties. Among the nodal network properties, although the relative importance of each region of interest was not identical, there were still some patterns. Conclusion In conclusion, the possibility exists to classify schizophrenia patients and healthy controls using network properties, and we have found that there is a provisional pattern of involved brain regions among patients with schizophrenia.

Background: Previous studies have reported functional and structural abnormalities in the thalamus and the pars triangularis of the infer ior frontal gyrus in patients with insomnia disorder. However, no studies have been conducted on the white-matter tracts between these 2 brain regions. We aimed to compare the white-matter integrity and structure of the left thalamus-pars triangularis tracts between patients with insomnia and controls, and to characterize the relationship between white-matter integrity and clinical features in patients with insomnia. Methods: In total, 22 participants with insomnia disorder and 27 controls underwent overnight polysomnography and brain magnetic resonance imaging, and then completed self-report clinical questionnaires and neurocognitive tests for spatial planning. Structural and diffusion measures such as fractional anisotropy, axial diffusivity, radial diffusivity and trace were analyzed in group comparison and correlation analyses. Results: The insomnia group showed significantly lower fractional anisotropy (F = 8.647, p = 0.02) and axial diffusivity (F = 5.895, p = 0.038) in the left thalamus-pars triangularis tracts than controls. In patients with insomnia, fractional anisotropy in the tracts was correlated with the results of the Stockings of Cambridge test (r = 0.451, p = 0.034), and radial diffusivity was correlated with Epworth Sleepiness Scale score (r = 0.437, p = 0.042). Limitations: Limitations included analyses of limited brain regions and the cross-sectional design. Conclusion: The insomnia group showed decreased integrity in the left thalamus-pars triangularis tracts, and integrity was correlated with cognition and daytime sleepiness. These results may imply that insomnia is characterized by disintegration of the white-matter tract between the left thalamus and inferior frontal gyrus.

No abstract

Schizophrenia is a heterogenous neuropsychiatric disorder with varying degrees of altered connectivity in a wide range of brain areas. Network analysis using graph theory allows researchers to integrate and quantify relationships between widespread changes in a network system. This study examined the organization of brain structural networks by applying diffusion MRI, probabilistic tractography, and network analysis to 48 schizophrenia patients and 24 healthy controls. T1-weighted MR images obtained from all participants were parcellated into 87 regions of interests (ROIs) according to a prior anatomical template and registered to diffusion-weighted images (DWI) of the same subjects. Probabilistic tractography was performed to obtain sets of white matter tracts between any two ROIs and determine the connection probabilities between them. Connectivity matrices were constructed using these estimated connectivity probabilities, and several network properties related to network effectiveness were calculated. Global efficiency, local efficiency, clustering coefficient, and mean connectivity strength were significantly lower in schizophrenia patients (p = 0.042, p = 0.011, p = 0.013, p = 0.046). Mean betweenness centrality was significantly higher in schizophrenia (p = 0.041). Comparisons of node wise properties showed trends toward differences in several brain regions. Nodal local efficiency was consistently lower in the basal ganglia, frontal, temporal, cingulate, diencephalon, and precuneus regions in the schizophrenia group. Inter-group differences in nodal degree and nodal betweenness centrality varied by region and showed inconsistent results. Robustness was not significantly different between the study groups. Significant positive correlations were found between t-score of color trails test part-1 and local efficiency and mean connectivity strength in the patient group. The findings of this study suggest that schizophrenia results in deterioration of the global network organization of the brain and reduced ability for information processing.

No abstract

We aimed to assess the effectiveness and safety of clonidine extended release (ER) treatment in Korean youth with ADHD and/or Tourette's disorder. We retrospectively reviewed the medical records of 29 children and adolescents treated with clonidine ER. The effectiveness were retrospectively measured at baseline and after 4 and 12 weeks based on the Clinical Global Impression-Severity (CGI-S) and Clinical Global Impression-Improvement (CGI-I) scores. Safety was evaluated at each visit based on spontaneous reports from the subjects or from their parents/guardians. Significant decreases in the CGI-S scores for both ADHD (F=23.478, p<0.001, partial η2=0.540) and tic symptoms (F=15.137, p<0.001, partial η2=0.443) were noted over 12 weeks. The most common adverse event was somnolence (n=9, 31.0%) and life-threatening adverse effects were not observed. Our results provide preliminary evidence for the effectiveness and safety of clonidine ER.

No abstract

Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.