Background. The present study examined biases in visual attention for emotional material in children and adolescents with post-traumatic stress disorder (PTSD) and healthy controls.Methods. The participants carried out an attentional deployment task in which probe detection latency data were used to determine the distribution of visual attention for threat-related and depression-related material.Results. The results showed that children and adolescents with PTSD, relative to controls, selectively allocated processing resources towards socially threatening stimuli and away from depression-related stimuli. This attentional avoidance of depression-related information in the PTSD participants declined with age.Conclusions. The results of the study are interpreted as a consolidation and extension of previous research on attentional bias and emotional disorder in younger participants.

In this study, 1968 high-school students were selected randomly through clustering, who responded to the Persian version of four measures: the Internet Addiction Test (IAT), UCLA Loneliness Scale, Rosenberg Self-Esteem Scale, and Matson Evaluation of Social Skills. Of the sample, 977 students were Internet users, who were classified into 37 Internet addicts, 304 possible Internet addicts, and 636 moderate users. Since possible addicts, moderate users, and nonusers can all be considered nonaddicts, to make a comprehensive and controlled comparison between addicts and nonaddicts, 37 possible addicts, 37 moderate users and 37 nonusers were matched with the Internet addicts. Results suggest that Internet addicts are lonelier and have lower self-esteem and poorer social skills than moderate users, but not necessarily than possible addicts or nonusers.

Background. Investigators have used various experimental paradigms such as the Stroop colour naming test to study how adults with different emotional disorders process emotional information. However, to date, little research has been carried out on younger subjects.Method. In the current experiment, children and adolescents with post-traumatic stress disorder (PTSD) and control subjects aged 9–17 years, participated in a modified Stroop colour naming task.Results. The results indicated that the children and adolescents with PTSD showed increased Stroop interference for trauma-related material relative to neutral words and to the performance of the controls.Conclusions. These findings indicate that attentional bias to trauma-congruent information is a function of PTSD in young age groups. The results are discussed with respect to the literature on information processing in PTSD.

The automatic diagnosis of Alzheimer’s disease plays an important role in human health, especially in its early stage. Because it is a neurodegenerative condition, Alzheimer’s disease seems to have a long incubation period. Therefore, it is essential to analyze Alzheimer’s symptoms at different stages. In this paper, the classification is done with several methods of machine learning consisting of -nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), linear discrimination analysis (LDA), and random forest (RF). Moreover, novel convolutional neural network (CNN) architecture is presented to diagnose Alzheimer’s severity. The relationship between Alzheimer’s patients’ functional magnetic resonance imaging (fMRI) images and their scores on the MMSE is investigated to achieve the aim. The feature extraction is performed based on the robust multitask feature learning algorithm. The severity is also calculated based on the Mini-Mental State Examination score, including low, mild, moderate, and severe categories. Results show that the accuracy of the KNN, SVM, DT, LDA, RF, and presented CNN method is 77.5%, 85.8%, 91.7%, 79.5%, 85.1%, and 96.7%, respectively. Moreover, for the presented CNN architecture, the sensitivity of low, mild, moderate, and severe status of Alzheimer patients is 98.1%, 95.2%,89.0%, and 87.5%, respectively. Based on the findings, the presented CNN architecture classifier outperforms other methods and can diagnose the severity and stages of Alzheimer’s disease with maximum accuracy.

The adverse impact of posttraumatic stress disorder (PTSD) on the developing mind in adolescence can extend well into adulthood. The developmental malleability of cognitive control capacity in this age group, however, may hold particular promise for cognitive training interventions. The present study investigated the effects of affective working memory (aWMT) compared to placebo-training on cognitive and affective functioning in adolescents with PTSD. 30 treatment-seeking adolescents trained for 20 days on either an affective dual n-back task (aWMT; n = 15) or a feature match task (placebo; n = 15). The aWMT group showed greater pre-to post-training increases in cognitive control as measured by the GoNogo task as well as improvements in symptoms of PTSD and increased use of adaptive emotion regulation strategies. These preliminary findings are promising given the potential for free and easy dissemination of the aWMT in schools and online.