Investigation of phase synchronization in functional brain networks of children with ADHD using nonlinear recurrence measure.

Measuring the phase synchronization between different brain regions in functional brain networks is a common approach to investigate many psychological disorders such as Attention Deficit Hyperactivity Disorder (ADHD). The emotional processing deficit in ADHD children is one of the main obstacles in their social interactions. In this study, the nonlinear Correlation between Probability of Recurrences (CPR) method is used for the first time to construct functional brain networks of 22 boys with ADHD and 22 healthy ones during watching four visual-emotional stimuli types. Topological features of brain networks, including shortest path length, clustering coefficient, and nodes strengths, are investigated in groups of ADHD and healthy. The results indicate a significantly (P-Values < 0.01) greater average clustering coefficient and lower shortest path length in the brain networks of ADHD individuals than the healthy ones. Accordingly, in the ADHD brain networks, the information exchange in both local and global scales is abnormally more than the healthy ones, leading to a hyper-synchronization in this group. The topological alterations of ADHD brain networks are mainly observed in the brain's frontal and occipital lobes, indicating impaired brain function of this group in emotional and visual processing. This survey demonstrates that the CPR method can be a good candidate for distinguishing the phase interactions of ADHD and healthy brain networks. Therefore, this study can contribute to further insights into the nonlinear dynamics analysis of brain networks in ADHD individuals.

Screening of Brain Tumors Using Functional Connectivity Patterns of Steady-State Visually Evoked Potentials.

Abstract Objective: The irregular growth and proliferation of cells in the brain and skull is named brain tumor, which is a special serious type of tumor due to its location. Nowadays, brain tumor is diagnosed by using imaging techniques such as computed tomography, positron emission tomography, single photon emission computed tomography, infrared imaging, magnetic resonance imaging (MRI), and functional MRI. However, these methods are not affordable to be used as screening tests. In contrast, electroencephalography has the ability of measuring biological signals, and it is a cost-effective and non-dangerous tool, being feasible to be used for screening purposes. The aim of this research was to evaluate the possibility of brain tumor detection, using functional connectivity features extracted from steady-state visually evoked potentials of eight brain tumor patients and four healthy control participants. Methods: For this purpose, after preprocessing, phase lag index was calculated as a functional connectivity measure. Afterward, four of the channels were chosen as the selected nodes, based on the highest number of strong connectivity (top 5%) as well as the most significant ones. The selected nodes were O1, O2, P3, and P4. As a final step, node strength was calculated for these selected nodes, which was used to classify the samples in the two groups, using Naïve Bayes, discriminant analysis (DA), k-nearest neighbors, support vector machines, and logistic regression methods. Results: The highest accuracy of 89.6% was obtained by using a DA classifier. This result shows that, in fact, brain tumor has the ability of changing brain functional connectivity. Conclusion: As the physiological alterations may occur sooner than the anatomical ones in tumor onset, detection of these alterations may be a useful measure for early diagnosis of this disease. This is still a primary study, but with the possibility of leading to further research, which can lead to the development of a method for the screening and early detection of brain tumor. Impact statement Imaging modalities are often used to diagnose brain tumors. However, these approaches are cost prohibitive for screening tests. Electroencephalography, a method that measures biological signals from the brain, on the other hand, is cost-effective, non-dangerous, and non-invasive, making it an ideal screening tool. The goal of this study is to analyze whether functional connectivity patterns taken from Steady-State Visually Evoked Potentials may be used to detect brain tumors at early stages. Since physiological changes occur before anatomical ones in tumor development, monitoring these alterations could be a useful tool to screen high-risk individuals, and also to an early diagnosis of the disease.

The neural correlation of sustained attention in performing conjunctive continuous performance task: an event-related potential study.

Owing to great improvements in cognitive neuroscience, the study of brain functions during different types of cognitive tasks has attracted much attention. Recording event-related potentials (ERPs) is an appropriate tool for such a purpose, as it is noninvasive and affordable. Attention is among the most studied cognitive processes. In this study, a visual version of the conjunctive continuous performance task-visual was used to examine the differences of cognitive processes in target and nontarget stimuli. Twenty healthy individuals (average age: 23 years) participated in the study. Electroencephalogram signals were recorded from all participants during conjunctive continuous performance task-visual. After preprocessing, the ERPs were calculated by averaging the epochs that were time-locked to the stimulus onset. Then, the ERPs of the two groups of target and nontarget stimuli, from the aspects of differences in the P300 and N200 morphological features, were analyzed in three midline channels: Pz, Fz, and Cz. According to the results, the P300 amplitudes were significantly larger in the target than those in the nontarget stimuli. The P300 latencies were also larger in the target than in the nontarget stimuli, but the difference was only significant in the Pz channel ERPs. For the N200 component, the negativity of amplitudes was significantly more enhanced in the target than in the nontarget stimuli. However, for the N200 latencies, no significant difference was found based on the data obtained from the groups. Furthermore, the findings suggest that the distribution of the P300 component is more centroparietal for the target stimuli, and more centrofrontal for the nontarget ones. In addition, the distribution of the N200 component is more frontoparietal for both the target and nontarget stimuli.