Local efficiency analysis of restingstate functional brain network in methamphetamine users.

This study set out to assess restingstate functional connectivity (rs-FN) and graph theorybased local efficiency within the left and right hemispheres of methamphetamine (MA) users. Functional brain networks of 19 MA users and 21 control participants were analyzed using restingstate fMRI. Graph edges in functional networks of the brain were defined and recurrence plot was used. We found that MA abuse may be accompanied by alterations of rs-FN within the defaultmode network (DMN), executive control network (ECN), and the salience network (SN) in both hemispheres of the brain. Moreover, we observed that such effects of MA may be correlated with duration of MA abuse and MA abstinence in many components of the DMN and SN. The results would seem to suggest that MAinduced alterations of local efficiency may, in part, account for maladaptive decision making, deficits in executive function and control over drug seeking/taking, and relapse.

Modified models and simulations for estimating dynamic functional connectivity in resting state functional magnetic resonance imaging.

As understanding the nature of brain networks through dynamic functional connectivity (dFC) estimation is of paramount significant, the introduction and revision of blood-oxygen-level dependent (BOLD) signal simulation methods in brain regions and dFC estimation methods have gained significant ground in recent years. Based on the observation of BOLD signals with multivariate nonnormal distribution in functional magnetic resonance imaging (fMRI) images, we first propose a copula-based method for the production of these signals, in which nonnormal data are generated with a selected time-varying covariance matrix. Therefore, we can compare the performance of models in the cases where brain signals have a multivariate nonnormal distribution. Then, two kendallized exponentially weighted moving average (KEWMA) and kendallized dynamic conditional correlation (KDCC) multivariate volatility models are introduced which are based on two well-known and commonly used exponentially weighted moving average (EMWA) and dynamic conditional correlation (DCC) models. The results show that KDCC model can estimate conditional correlation significantly far better than the former ones (ie, DCC, standardized dynamic conditional correlation, EWMA, and standardized exponentially weighted moving average) on both types of data (ie, multivariate normal and nonnormal). In the next step, the bivariate normal distribution in Iranian resting state fMRI data is confirmed by using statistical tests, and it is shown that the dynamic nature of FC is not optimally detected using prevalent methods. Two alternative Portmanteau and rank-based tests are proposed for the examination of conditional heteroscedasticity in data. Finally, dFC in these data is estimated by employing the KDCC model.

Resting-state effective connectivity in the motive circuit of methamphetamine users: A case controlled fMRI study.

Methamphetamine (MA) and other psychostimulants target the motive circuit of the brain, which is involved in reward, behavioral sensitization, and relapse to drug-seeking/taking behavior. In spite of this fact, the data regarding the effective connectivity (EC) in this circuit among MA users is scarce. The present study aimed to assess resting-state EC in the motive circuit of MA users during abstinence using the fMRI technique. Seventeen MA users after abstinence and 18 normal controls were examined using a 3 T Siemens fMRI scanner. After extracting time series of the motive circuit, EC differences in the motive circuit were analyzed using dynamic causal modeling (DCM). The findings revealed that abstinent MA users had an enhanced EC from the prefrontal cortex (PFC) to the ventral palladium (VP) (PFC→VP) and on the mediodorsal thalamus (MD) self-loop (MD→MD), but they showed a decreased connectivity on the VP self-loop (VP→VP) compared to healthy controls. The findings suggest that abstinent MA users may suffer from a limited pathology in connectivity within the motive circuit involved in reward, behavioral sensitization, and relapse. The enhanced PFC→VP seems to be a compensatory mechanism to control or regulate the subcortical regions involved in reward and behavioral sensitization. Furthermore, the enhanced connectivity on the MD self-loop and the decreased connectivity on the VP self-loop in abstinent MA users may, at least partially, affect the output of the limbic system, which can be seen in the behavioral sensitization and relapse processes. Nonetheless, further investigation in this area is strongly recommended to elucidate the exact mechanisms involved.

Causes of Death Among 379 Patients With Hemophilia: A Developing Country's Report.

There are steps to achieve an optimum life for patients with hemophilia in developing countries, and awareness of the pattern of death in patients with hemophilia is a prerequisite for any health-care program. Owing to the lack of any data on the pattern of death in patients with hemophilia from developing countries, the current study was done to address common causes of death, and the spectrum of causes of death among individuals with hemophilia A and B. To address the pattern of death in northeast of Iran, we retrospectively collected demographic data regarding deceased patients with hemophilia A and B. Overall, among 379 people with hemophilia A and B, there were 46 deaths. Thirty-two deaths happened in the severe forms of the diseases. The obtained results show the patterns of death in the patients studied are not as parallel as some reports from the developed countries. Traumatic and spontaneous bleeding events were the main causes of death. The trend of death shows a decrease in the current decade post better therapeutic facilities. Evaluation of causes of death in hemophilia can be a useful indicator for managing the efficacy of health care in the current patients.