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The brain may be considered as a synchronized dynamic network with several coherent dynamical units. However, concerns remain whether synchronizability is a stable state in the brain networks. If so, which index can best reveal the synchronizability in brain networks? To answer these questions, we tested the application of the spectral graph theory and the Shannon entropy as alternative approaches in neuroimaging. We specifically tested the alpha rhythm in the resting-state eye closed (rsEC) and the resting-state eye open (rsEO) conditions, a well-studied classical example of synchrony in neuroimaging EEG. Since the synchronizability of alpha rhythm is more stable during the rsEC than the rsEO, we hypothesized that our suggested spectral graph theory indices (as reliable measures to interpret the synchronizability of brain signals) should exhibit higher values in the rsEC than the rsEO condition. We performed two separate analyses of two different datasets (as elementary and confirmatory studies). Based on the results of both studies and in agreement with our hypothesis, the spectral graph indices revealed higher stability of synchronizability in the rsEC condition. The k-mean analysis indicated that the spectral graph indices can distinguish the rsEC and rsEO conditions by considering the synchronizability of brain networks. We also computed correlations among the spectral indices, the Shannon entropy, and the topological indices of brain networks, as well as random networks. Correlation analysis indicated that although the spectral and the topological properties of random networks are completely independent, these features are significantly correlated with each other in brain networks. Furthermore, we found that complexity in the investigated brain networks is inversely related to the stability of synchronizability. In conclusion, we revealed that the spectral graph theory approach can be reliably applied to study the stability of synchronizability of state-related brain networks. [ABSTRACT FROM AUTHOR]

Purpose:In this article, we propose current source density (CSD) as a marker for diagnosis of Attention Deficit and Hyperactivity Disorder (ADHD) children for the first time. Materials and methods: A source localization method (sLORETA) was used to find the source of abnormality in the CSD in electrical distribution of different frequency bands in resting state EEG for the ADHD children in comparison to the normal children using statistical nonparametric mapping (SnPM) test. Resting-state EEG in eye-open (EO) condition was recorded from 13 ADHD and 15 age-matched normal children (aged between 6 and 13). Results: Significant differences were found in the CSD of three frequency bands: delta, theta, and alpha in the parietal lobe, between ADHD and normal groups. Conclusions: Higher CSD in the parietal lobe for ADHD children was found which suggests that an abnormality exists in the parietal lobe of children with ADHD which can be related to the attention shifting problem in these children. [ABSTRACT FROM AUTHOR]

Aim of the study: The neural basis of demanding mathematical problem solving is currently indeterminate and unclear. Mathematical problem solving engages higher order cognition and a complex associative activity of functional neural networks occurs during demanding problem solving. Method: Twenty right handed subjects (mean age: 24.6 years; SD = 3.97 years; 50% female) participated in this study. An arithmetic logic puzzle was used as a demanding mathematical task. EEGs were recorded in the eye open rest and eye open task conditions. To clarify functional connectivity of brain networks, clustering coefficient, transitivity, global efficiency, degree and entropy were investigated in two conditions. Results: During problem solving, disrupted brain connectivity and decreased brain segregation were observed in the alpha band. However, in the beta band, increased connectivity, transitivity and clustering associated with higher modularity were observed. Theta exhibited unaltered brain network function. Conclusion: In the demanding problem solving task, decreased local alpha coupling may suggest that default mode network activity is interrupted. Since there is no significant difference within the theta network, the central executive network may not be as strongly involved. Increased segregation of functional brain network (without increasing of integration level) can be discussed in relation of demanding aspects of mathematical problem. We suggest a complex network may involve in the real situation of demanding problem solving. [ABSTRACT FROM AUTHOR]

Objectives: The aetiology and molecular mechanisms of schizophrenia (SCZ) and paranoid personality disorder (PPD) are not yet clarified. The present study aimed to assess the role of mitochondrial complex I and cell bioenergetic pathways in the aetiology and characteristics of SCZ and PPD. Methods: mRNA levels of all genomic and mitochondrial genes which encode mitochondrial complex I subunits (44 genes) were assessed in blood in 634 SCZ, 340 PPD patients and 528 non-psychiatric subjects using quantitative real-time PCR, and associated comprehensive psychiatric, neurological and biochemical assessments. Results: Significant expression changes of 18 genes in SCZ patients and 11 genes in PPD patients were detected in mitochondrial complex I. Most of these genes were novel candidate genes for SCZ and PPD. Several correlations between mRNA levels and severity of symptoms, drug response, deficits in attention, working memory, executive functions and brain activities were found. Conclusions: Deregulations of both core and supernumerary subunits of complex I are involved in the aetiology of SCZ and PPD. These deregulations have effects on brain activity as well as disorder characteristics. [ABSTRACT FROM AUTHOR]

Frontal cortex activity in the left hemisphere during depression is reduced. Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that can increase frontal cortex activity. Therapy based on tDCS and positive psychology (PP) therapy was applied improving patients’ quality of life. The present study compared three conditions participants with clinical depression; (a) tDCS therapy, (b) positive psychotherapy, and (c) combined treatment. Hamilton Depression Rating Scale (HDRS), Adult State Hope Scale and Optimism/Pessimism Scale (OPS) was used at baseline, 2 weeks, 4-weeks and 3-months follow-up. Combined condition participants showed greater reduction in depressed mood, improved hope and optimism after 4-weeks as well as during 3-months follow-up than the other conditions. The results are discussed in terms of additive or synergistic relation between tDCS and PP treatment. Future studies should (a) use larger sample-sizes, (b) include no-treatment control conditions, (c) include double-blind designs, (d) control for previous or on-going drug therapy, (d) control for previous or ongoing psychotherapy. Furthermore, future studies should aim to increase theoretical understanding by investigating whether the relation between tDCS and psychotherapy are additive or synergistic. [ABSTRACT FROM AUTHOR]

Elucidation of the neural correlates of time perception constitutes an important research topic in cognitive neuroscience. The focus to date has been on durations in the millisecond to seconds range, but here we used electroencephalography (EEG) to examine brain functional connectivity during much longer durations (i.e., 15 min). For this purpose, we conducted an initial exploratory experiment followed by a confirmatory experiment. Our results showed that those participants who overestimated time exhibited lower activity of beta (18–30 Hz) at several electrode sites. Furthermore, graph theoretical analysis indicated significant differences in the beta range (15–30 Hz) between those that overestimated and underestimated time. Participants who underestimated time showed higher clustering coefficient compared to those that overestimated time. We discuss our results in terms of two aspects. FFT results, as a linear approach, are discussed within localized/dedicated models (i.e., scalar timing model). Second, non-localized properties of psychological interval timing (as emphasized by intrinsic models) are addressed and discussed based on results derived from graph theory. Results suggested that although beta amplitude in central regions (related to activity of BG-thalamocortical pathway as a dedicated module) is important in relation to timing mechanisms, the properties of functional activity of brain networks; such as the segregation of beta network, are also crucial for time perception. These results may suggest subjective time may be created by vector units instead of scalar ticks. [ABSTRACT FROM AUTHOR]

Introduction: Contrary to Diagnostic and Statistical Manual of Mental Disorders (DSM-5), fifth edition, some studies indicate that ADHD-inattentive presentation (ADHD-I) is a distinct diagnostic disorder and not an ADHD presentation. Methods: In this study, 12 ADHD-combined presentation (ADHD-C), 10 ADHD-I, and 13 controls were enrolled and their resting state EEG recorded. Following this, a graph theoretical analysis was performed and functional integration and segregation of brain network was calculated. Results: The results show that clustering coefficient of theta band was significantly different among three groups and significant differences were observed in theta global efficiency between controls and ADHD-C. Regarding the alpha band, a lower clustering coefficient was observed in control subjects. In the beta band, clustering coefficient was significantly different between the control and children with ADHD-C and also between ADHD-I and ADHD-C. The clustering coefficient, in the subjects with ADHD-C, demonstrated a rapid decline and was significantly lower than the subjects with ADHD-I and control. Conclusion: Decreased clustering, in high thresholds, may be associated with hyperactivity while increased segregation in low thresholds with inattentiveness. A different functional network occurs in the ADHD-C brain that is consistent with several studies that have reported ADHD-I as a distinct disorder. [ABSTRACT FROM AUTHOR]