Changes in relative regional cerebral glucose metabolism (rCMRglc) and their potential gender differences in abstinent methamphetamine (MA) users were explored. Relative rCMRglc, as measured by 18 F-fluorodeoxyglucose positron emission tomography, and frontal executive functions, as assessed by Wisconsin card sorting test (WCST), were compared between 35 abstinent MA users and 21 healthy comparison subjects. In addition, male and female MA users and their gender-matched comparison subjects were compared to investigate potential gender differences. MA users had lower rCMRglc levels in the right superior frontal white matter and more perseveration and nonperseveration errors in the WCST, relative to healthy comparison subjects. Relative rCMRglc in the frontal white matter correlated with number of errors in the WCST in MA users. In the subanalysis for gender differences, lower rCMRglc in the frontal white matter and more errors in the WCST were found only in male MA users, not in female MA users, relative to their gender-matched comparison subjects. The current findings suggest that MA use causes persistent hypometabolism in the frontal white matter and impairment in frontal executive function. Our findings also suggest that the neurotoxic effect of MA on frontal lobes of the brain might be more prominent in men than in women.

Previously, our group reported the altered white matter tract integrity of the left anterior cingulate in posttraumatic stress disorder (PTSD) in whole-brain exploration. Current study intended to explore whether the alteration was more prominent in any specific regions of the cingulum bundle. Diffusion tensor images of 21 PTSD subjects and 21 healthy comparison subjects were acquired. Eight isocubic regions of interest (ROIs), i.e. bilateral rostral, subgenual, dorsal, and upper cingulum bundle, were selected. Fractional anisotropy values in each ROI, which indicate the white matter tract integrity, were measured and compared between groups. Relative to comparison subjects, PTSD subjects had significantly smaller fractional anisotropy values in the left side of rostral, subgenual and dorsal cingulum bundle (26.7, 25.0, 22.2% decrease, respectively), but not in the right side ROIs. We report an asymmetrical alteration of the cingulum bundle in PTSD.

The objective of this study was to examine the integrity of whole-brain white matter in posttraumatic stress disorder patients. Twenty posttraumatic stress disorder patients who survived the Taegu subway fire incident and 20 healthy volunteers participated in this study. Statistical parametric mapping was used to evaluate the global differences in fractional anisotropy values between the two groups. The results show that posttraumatic stress disorder patients had significantly lower fractional anisotropy values in the left anterior cingulate regions. Posttraumatic stress disorder symptom severity negatively correlated to the level of decrease in anterior cingulate fractional anisotropy values. The outcome of the current study suggests that the disruption of the left anterior cingulate white matter tract integrity may play an important role in the pathophysiology of posttraumatic stress disorder.

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Abstract:Previous ensemble streamflow prediction (ESP) studies in Korea reported that modelling error significantly affects the accuracy of the ESP probabilistic winter and spring (i.e. dry season) forecasts, and thus suggested that improving the existing rainfall-runoff model, TANK, would be critical to obtaining more accurate probabilistic forecasts with ESP. This study used two types of artificial neural network (ANN), namely the single neural network (SNN) and the ensemble neural network (ENN), to provide better rainfall-runoff simulation capability than TANK, which has been used with the ESP system for forecasting monthly inflows to the Daecheong multipurpose dam in Korea. Using the bagging method, the ENN combines the outputs of member networks so that it can control the generalization error better than an SNN. This study compares the two ANN models with TANK with respect to the relative bias and the root-mean-square error. The overall results showed that the ENN performed the best among the three rainfall-runoff models. The ENN also considerably improved the probabilistic forecasting accuracy, measured in terms of average hit score, half-Brier score and hit rate, of the present ESP system that used TANK. Therefore, this study concludes that the ENN would be more effective for ESP rainfall-runoff modelling than TANK or an SNN.