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.

Assessing the Effects of Alzheimer Disease on EEG Signals Using the Entropy Measure: A Meta-analysis.

Introduction: Alzheimer disease (AD) is the most prevalent neurodegenerative disorder and a type of dementia. About 80% of dementia in older adults is due to AD. According to multiple research articles, AD is associated with several changes in EEG signals, such as slow rhythms, reduction in complexity and functional associations, and disordered functional communication between different brain areas. This research focuses on the entropy parameter. Methods: In this study, the keywords "Entropy," "EEG," and "Alzheimer" were used. In the initial search, 102 articles were found. In the first stage, after investigating the Abstracts of the articles, the number of them was reduced to 62, and upon further review of the remaining articles, the number of articles was reduced to 18. Some papers have used more than one entropy of EEG signals to compare, and some used more than one database. So, 25 entropy measures were considered in this meta-analysis. We used the Standardized Mean Difference (SMD) to find the effect size and compare the effects of AD on the entropy of the EEG signal in healthy people. Funnel plots were used to investigate the bias of meta-analysis. Results: According to the articles, entropy seems to be a good benchmark for comparing the EEG signals between healthy people and AD people. Conclusion: It can be concluded that AD can significantly affect EEG signals and reduce the entropy of EEG signals. Highlights: Our primary question addressed in this study is "Can Alzheimer's Disease significantly affect EEG signals or not?" This paper is the first Meta-Analysis study that reveals the effects of Alzheimer's Disease on EEG signals and the caused reduction in the complexity of the EEG signal. According to the articles, results and funnel plots of this Meta-Analysis, entropy seems to be a good benchmark for comparing the EEG signals in healthy people and people who have Alzheimer's Disease. Plain Language Summary: Alzheimer's Disease is one of the most prevalent neurodegenerative disorder which can affect EEG signals. This study is the first Meta-Analysis in this regard and the results confirm that Alzheimer's Disease reduces the complexity of the EEG signals. We used 25 entropy measures applied in 18 articles. The materials in this Meta-Analysis are 1-SMD for finding the effect size and 2- Funnel plot for investigating the bias of Meta-Analysis.

Functional neuronal networks reveal emotional processing differences in children with ADHD.

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder that, in addition to inattention, excessive activity, or impulsivity, makes it difficult for children to process facial emotions and thus to interact with their peers. Here we analyze neuronal networks of children with this disorder by means of the phase-locking value (PLV) method. In particular, we determine the level of phase synchronization between 62 EEG channels of 22 healthy boys and 22 boys with ADHD, recorder whilst observing facial emotions of anger, happiness, neutrality, and sadness. We construct neuronal networks based on the gamma sub-band, which according to previous studies, shows the highest response to emotional stimuli. We find that the functional connectivity of the frontal and occipital lobes in the ADHD group is significantly (P-value < 0.01) higher than in the healthy group. More functional connectivity in these lobes shows more phase synchronization between the neurons of these brain regions, representing some problems in the brain emotional processing center in the ADHD group. The shortest path lengths in these lobes are also significantly (P-value < 0.01) higher in the ADHD group than in the healthy group. This result indicates less efficiency of information transmission and segregation in occipital and frontal lobes of ADHD neuronal networks, responsible for visual and emotional processing in the brain, respectively. We hope that our approach will help obtain further insights into ADHD with methods of network science.

Adding Tactile Feedback and Changing ISI to Improve BCI Systems' Robustness: An Error-Related Potential Study.

Nowadays, the brain-computer interface (BCI) systems attract much more attention than before, yet they have not found their ways into our lives since their accuracy is not satisfying. Error Related Potential (ErRP) is a potential that occurs in human brain signals when an unintended event happens, against ones' will and thoughts. An example is the occurrence of an error in BCI systems. Investigation of the ErRP could enable researchers to increase the accuracy of BCI systems by detecting instances of inaccuracy in the system. In this research the effects of two parameters on the ErRP are studied: (1) The Motor Imagery Time, also known as Inter-Stimulus Interval (ISI) and (2) different types of feedback (Visual and Tactile). The statistical analysis of the ErRP characteristics showed that feedback type meaningfully affects the ErRP in a cue-paced BCI system and it will affect the time of occurrence of this potential. To validate the proposed idea, different feature extraction, and classification techniques were used for the classification of the BCI system responses. It was shown that by proper selection of the parameters and features, the accuracy of the system could be improved. Tactile feedback together with higher ISI could increase the accuracy of finding erroneous trials up to 90%. The proposed method's accuracy was significantly higher (p-value < 0.05) compared to other methods of feature extraction.

Brain connectivity analysis in fathers of children with autism.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder in which changes in brain connectivity, associated with autistic-like traits in some individuals. First-degree relatives of children with autism may show mild deficits in social interaction. The present study investigates electroencephalography (EEG) brain connectivity patterns of the fathers who have children with autism while performing facial emotion labeling task. Fifteen biological fathers of children with the diagnosis of autism (Test Group) and fifteen fathers of neurotypical children with no personal or family history of autism (Control Group) participated in this study. Facial emotion labeling task was evaluated using a set of photos consisting of six categories (mild and extreme: anger, happiness, and sadness). Group Independent Component Analysis method was applied to EEG data to extract neural sources. Dynamic causal connectivity of neural sources signals was estimated using the multivariate autoregressive model and quantified by using the Granger causality-based methods. Statistical analysis showed significant differences (p value < 0.01) in the connectivity of neural sources in recognition of some emotions in two groups, which the most differences observed in the mild anger and mild sadness emotions. Short-range connectivity appeared in Test Group and conversely, long-range and interhemispheric connections are observed in Control Group. Finally, it can be concluded that the Test Group showed abnormal activity and connectivity in the brain network for the processing of emotional faces compared to the Control Group. We conclude that neural source connectivity analysis in fathers may be considered as a potential and promising biomarker of ASD.

Elbow angle generation during activities of daily living using a submovement prediction model.

The present study aimed to develop a realistic model for the generation of human activities of daily living (ADL) movements. The angular profiles of the elbow joint during functional ADL tasks such as eating and drinking were generated by a submovement-based closed-loop model. First, the ADL movements recorded from three human participants were broken down into logical phases, and each phase was decomposed into submovement components. Three separate artificial neural networks were trained to learn the submovement parameters and were then incorporated into a closed-loop model with error correction ability. The model was able to predict angular trajectories of human ADL movements with target access rate = 100%, VAF = 98.9%, and NRMSE = 4.7% relative to the actual trajectories. In addition, the model can be used to provide the desired target for practical trajectory planning in rehabilitation systems such as functional electrical stimulation, robot therapy, brain-computer interface, and prosthetic devices.

The Effects of Upper Limb Motor Recovery on Submovement Characteristics among the Patients with Stroke: A Meta-Analysis.

OBJECTIVE: To evaluate the evidence related to the effect of upper limb motor recovery on submovement characteristics, including duration, amplitude, overlap, interpeak distance, and the number of submovements in stroke patients using a meta-analysis. TYPE OF STUDY: Meta-analysis. LITERATURE SURVEY: The literature search was restricted to articles written in English published from inception to October 2018 in Web of Science, PubMed, Science Direct, IEEE Explore, MEDLINE, CDSR, Scopus, Compendex, Wiley Online Library, Springer Link, and REHABDATA. METHODOLOGY: Studies were included if they encompassed adult participants with a clinical diagnosis of stroke who underwent upper limb rehabilitation and if they assessed and reported submovement characteristics as the outcome measures in pre- and posttreatment stages. Changes in submovement characteristics between pre- and postinterventions were compared using the standardized mean difference (SMD). Finally, a test for heterogeneity and publication bias was implemented for all meta-analyses. SYNTHESIS: Among the 188 retrieved articles, seven of them (one randomized controlled trial, six pre-post) involving 259 patients were selected for meta-analysis. Based on the results, the overall observed changes in all meta-analyses were statistically significant. In total, submovement amplitude (SMD 0.624, 95% confidence interval [CI] [0.356, 0.893]), duration (SMD 0.61, 95% CI [0.332, 0.888]), and overlap (SMD 0.928, 95% CI [0.768, 1.088]) increased whereas interpeak distance (SMD -0.278, 95% CI [-0.42, -0.137]), and the total number of submovements (SMD -0.804, 95% CI [-1.069, -0.538]) decreased. CONCLUSIONS: The submovements appeared to become longer, fewer, and more overlapped with motor recovery. Based on the results, the ability of the neural system to blend submovements increased in both acute/subacute and chronic patients during recovery. Therefore, assessing the submovements during recovery can be a new quantitative measure of motor improvement, providing another means of comparing rehabilitation interventions and individualizing therapy for stroke patients.

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.

Early Posterior Negativity as Facial Emotion Recognition Index in Children With Attention Deficit Hyperactivity Disorder.

INTRODUCTION: Studies indicate that children with Attention Deficit Hyperactivity Disorder (ADHD) have deficits in social and emotional functions. It can be hypothesized that these children have some deficits in early stages of facial emotion discrimination. Based on this hypothesis, the present study investigated neural correlates of early visual processing during emotional face recognition in this group compared with typically developing children using the Event-Related Potentials (ERPs). METHODS: Nineteen boys between the ages of 7 and 11 years diagnosed with ADHD (Combined type) based on DSM-IV-TR classification were compared with 19 typically developing children matched on age and gender. The participants performed an emotional face recognition task while their brain activities were recorded using the event-related potentials procedure. RESULTS: A significant reduction in the Early Posterior Negativity (EPN) for happy and angry faces has been revealed in ADHD children compared to normal ones (P<0.05). CONCLUSION: The present study supports the notion that individuals with ADHD have some impairments in early stage of emotion processing which can leading to their misinterpretation of emotion in faces.

Emotional Face Recognition in Children With Attention Deficit/Hyperactivity Disorder: Evidence From Event Related Gamma Oscillation.

INTRODUCTION: Children with attention-deficit/hyperactivity disorder (ADHD) have some impairment in emotional relationship which can be due to problems in emotional processing. The present study investigated neural correlates of early stages of emotional face processing in this group compared with typically developing children using the Gamma Band Activity (GBA). METHODS: A total of 19 children diagnosed with ADHD (Combined type) based on DSM-IV classification were compared with 19 typically developing children matched on age, gender, and IQ. The participants performed an emotional face recognition while their brain activities were recorded using an event-related oscillation procedure. RESULTS: The results indicated that ADHD children compared to normal group showed a significant reduction in the gamma band activity, which is thought to reflect early perceptual emotion discrimination for happy and angry emotions (P<0.05). CONCLUSION: The present study supports the notion that individuals with ADHD have some impairments in early stage of emotion processing which can cause their misinterpretation of emotional faces.

Evaluation of estimating missed answers in conners adult ADHD rating scale (screening version).

OBJECTIVE: Conners Adult ADHD Rating Scale (CAARS) is among the valid questionnaires for evaluating Attention-Deficit/Hyperactivity Disorder in adults. The aim of this paper is to evaluate the validity of the estimation of missed answers in scoring the screening version of the Conners questionnaire, and to extract its principal components. METHOD: This study was performed on 400 participants. Answer estimation was calculated for each question (assuming the answer was missed), and then a Kruskal-Wallis test was performed to evaluate the difference between the original answer and its estimation. In the next step, principal components of the questionnaire were extracted by means of Principal Component Analysis (PCA). Finally the evaluation of differences in the whole groups was provided using the Multiple Comparison Procedure (MCP). RESULTS: Findings indicated that a significant difference existed between the original and estimated answers for some particular questions. However, the results of MCP showed that this estimation, when evaluated in the whole group, did not show a significant difference with the original value in neither of the questionnaire subscales. The results of PCA revealed that there are eight principal components in the CAARS questionnaire. CONCLUSION: The obtained results can emphasize the fact that this questionnaire is mainly designed for screening purposes, and this estimation does not change the results of groups when a question is missed randomly. Notwithstanding this finding, more considerations should be paid when the missed question is a critical one.