Heart sounds play an important role in the diagnosis of cardiac conditions. Due to the low signal-to-noise ratio (SNR), it is problematic and time-consuming for experts to discriminate different kinds of heart sounds. Thus, objective classification of heart sounds is essential. In this study, we combined a conventional feature engineering method with deep learning algorithms to automatically classify normal and abnormal heart sounds. First, 497 features were extracted from eight domains. Then, we fed these features into the designed convolutional neural network (CNN), in which the fully connected layers that are usually used before the classification layer were replaced with a global average pooling layer to obtain global information about the feature maps and avoid overfitting. Considering the class imbalance, the class weights were set in the loss function during the training process to improve the classification algorithm’s performance. Stratified five-fold cross-validation was used to evaluate the performance of the proposed method. The mean accuracy, sensitivity, specificity and Matthews correlation coefficient observed on the PhysioNet/CinC Challenge 2016 dataset were 86.8%, 87%, 86.6% and 72.1% respectively. The proposed algorithm’s performance achieves an appropriate trade-off between sensitivity and specificity.

Over the past thirty years a number of studies have suggested that antidepressants can be effective in the treatment of depressive symptoms in patients with cancer. The aim of this paper was to review randomized controlled trials (RCTs) and to perform a meta-analysis in order to quantify their overall effect. Pubmed and the Cochrane libraries were searched for the time period between 1980 and 2010. Nine RCTs were identified and reviewed. Six of them (with a total of 563 patients) fulfilled the criteria for meta-analysis, but exhibited an unclear risk for bias. The estimated effect size was 1.56 with 95% CI: 1.07- 2.28 (p= 0.021). There were no differences in discontinuation rates between antidepressants and placebo groups (RR= 0.86 with 95% CI 0.47- 1.56, p=0.62). This meta-analysis suggests that antidepressants can be effective in treating depressive symptoms beside clinical depression. When considering the risk of side effects and interactions and the heterogeneity among the mostly small studies, a general recommendation cannot be made until well-controlled studies are conducted.

A variety of data indicate that the cerebellum participates in perceptual tasks requiring the precise representation of temporal information. Access to the word form of a lexical item requires, among other functions, the processing of durational parameters of verbal utterances. Therefore, cerebellar dysfunctions must be expected to impair word recognition. In order to specify the topography of the assumed cerebellar speech perception mechanism, a functional magnetic resonance imaging study was performed using the German lexical items “Boden” ([bodn], Engl. “floor”) and “Boten” ([botn], “messengers”) as test materials. The contrast in sound structure of these two lexical items can be signaled either by the length of the wordmedial pause (closure time, CLT; an exclusively temporal measure) or by the aspiration noise of wordmedial “d” or “t” (voice onset time, VOT; an intrasegmental cue). A previous study found bilateral cerebellar disorders to compromise word recognition based on CLT whereas the encoding of VOT remained unimpaired. In the present study, two series of “Boden—Boten” utterances were resynthesized, systematically varying either in CLT or VOT. Subjects had to identify both words “Boden” and “Boten” by analysis of either the durational parameter CLT or the VOT aspiration segment. In a subtraction design, CLT categorization as compared to VOT identification (CLT VOT) yielded a significant hemodynamic response of the right cerebellar hemisphere (neocerebellum Crus I) and the frontal lobe (anterior to Broca's area). The reversed contrast (VOT CLT) resulted in a single activation cluster located at the level of the supra-temporal plane of the dominant hemisphere. These findings provide first evidence for a distinct contribution of the right cerebellar hemisphere to speech perception in terms of encoding of durational parameters of verbal utterances. Verbal working memory tasks, lexical response selection, and auditory imagery of word strings have been reported to elicit activation clusters of a similar location. Conceivably, representation of the temporal structure of speech sound sequences represents the common denominator of cerebellar participation in cognitive tasks acting on a phonetic code.

Violent content in video games evokes many concerns but there is little research concerning its rewarding aspects. It was demonstrated that playing a video game leads to striatal dopamine release. It is unclear, however, which aspects of the game cause this reward system activation and if violent content contributes to it. We combined functional Magnetic Resonance Imaging (fMRI) with individual affect measures to address the neuronal correlates of violence in a video game.