Abnormal brain activity dynamics, in the sense of a thalamocortical dysrhythmia (TCD), has been proposed as the underlying mechanism for a subset of disorders that bridge the traditional delineations of neurology and neuropsychiatry. In order to test this proposal from a psychiatric perspective, a study using magnetoencephalography (MEG) was implemented in subjects with schizophrenic spectrum disorder (n = 14), obsessive–compulsive disorder (n = 10), or depressive disorder (n = 5) and in control individuals (n = 18). Detailed CNS electrophysiological analysis of these patients, using MEG, revealed the presence of abnormal theta range spectral power with typical TCD characteristics, in all cases. The use of independent component analysis and minimum-norm-based methods localized such TCD to ventromedial prefrontal and temporal cortices. The observed mode of oscillation was spectrally equivalent but spatially distinct from that of TCD observed in other related disorders, including Parkinson's disease, central tinnitus, neuropathic pain, and autism. The present results indicate that the functional basis for much of these pathologies may relate most fundamentally to the category of calcium channelopathies and serve as a model for the cellular substrate for low-frequency oscillations present in these psychiatric disorders, providing a basis for therapeutic strategies.

Insomnia is one of the most common health complaints, with a high prevalence of 30~50% in the general population. In particular, neuroimaging research has revealed that widespread dysfunctions in brain regions involved in hyperarousal are strongly correlated with insomnia. However, whether the topology of the intrinsic connectivity is aberrant in insomnia remains largely unknown. In this study, resting-state functional magnetic resonance imaging (rsfMRI) in conjunction with graph theoretical analysis, was used to construct functional connectivity matrices and to extract the attribute features of the small-world networks in insomnia. We examined the alterations in global and local small-world network properties of the distributed brain regions that are predominantly implicated in the frontostriatal network between 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without insomnia symptoms (NIS). Correlations between the small-world properties and clinical measurements were also generated to identify the differences between the two groups. Both the IS group and the NIS group exhibited a small-worldness topology. Meanwhile, the global topological properties didn't show significant difference between the two groups. By contrast, participants in the IS group showed decreased regional degree and efficiency in the left inferior frontal gyrus (IFG) compared with subjects in the NIS group. More specifically, significantly decreased nodal efficiency in the IFG was found to be negatively associated with insomnia scores, whereas the abnormal changes in nodal betweenness centrality of the right putamen were positively correlated with insomnia scores. Our findings suggested that the aberrant topology of the salience network and frontostriatal connectivity is linked to insomnia, which can serve as an important biomarker for insomnia.

ObjectivesConduct disorder (CD) is characterized by the violation of the rights of others or basic social rules and a repetitive, persistent pattern of antisocial and aggressive behaviors. A large number of functional and structural neuroimaging studies have identified widely abnormalities in specific brain regions in CD, but the alterations in the topological organization of functional networks among them remain largely unknown.MethodsResting-state functional magnetic resonance imaging was applied to investigate the intrinsic functional connectivity in 18 pure CD patients and eighteen typically developing healthy controls. We first constructed the functional networks and then examined the CD-related alteration in topology properties using graph theoretical analysis.ResultsBoth the CD group and healthy controls exhibited small-world topology. However, the CD group showed decreased global and local efficiency. Changes in the nodal characteristics in CD group were found predominantly in the default-mode network, visual, and striatum regions. In addition, altered fronto-limbic-striatum network topology was found to have a relationship with clinical scores.ConclusionsOur findings indicate the altered nodal topology of brain functional connectivity networks in CD.SignificanceThe results provide unequivocal evidence of a topological disruption in the brain networks that suggest some possible pathophysiological mechanisms underlying CD.

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Abstract-Implementing convenient traveling information service is a crucial task for deploying intelligent transportation system applications and location-based services. Traditional traveling information service systems, such as car navigation systems or web maps, only provide relatively static information which doesn't truly reflect the dynamic changes of traffic situation, and result in very limited practical use. Although there have emerged some car navigation products and other applications involving dynamic traffic information, considering the rapid change of city traffic situation, these applications still face practical difficulties for all the information received real-timely will get outdated within a few minutes, which makes the so called dynamic applications basically time-slice limited static ones. Aiming at such a problem, a short-term traffic prediction approach and a consequent real-time route guidance process are presented in this paper which integrates historical traffic based statistical reasoning, real-time traffic and events processing, with a BP neural network based analytical model, to forecast the situation and evaluate the influence of traffic during the traveling process. Then a collaboration working framework is set forward to implement dynamic route guidance, with the combination of a GIS server, a traffic forecasting server and a database management system. The traffic forecasting server, integrating with historical statistics reckoning continuously receives real-time traffic information obtained from floating vehicles, traffic events described in natural language, and achieves short-term forecasting results for the whole road networks, then fed the results back into the database management system and GIS server, so that a time-dependant optimal routing can be conducted through a dynamic least traveling time algorithm developed in this study. A prototype navigation system fulfilling the above aspects has been developed and the dynamic route choice approach demonstrated on road networks in the downtown area of Beijing city. The approach presented in this paper is argued to provide a practical solution for real-time public traveling information service and dynamic web maps.Keywords-traffic forecasting; traffic simulatio; BP neural networ;, natural language processing; dynamic route guidance I. BACKGROUND City traffic is an urgent problem nowadays, but no better solution is found so far. To mitigate the city traffic problems, it has got commonly understood that not only transportation infrastructure construction, but also traffic management and controlling must achieve great progress with modern information and communication technologies (ICT) and GIS technologies [Goodchild 2000].Over the past decades, GIS has found many successful applications in different fields, including intelligent transportation system (ITS) and location-based services (LBS). It can be used to manage road network concerned data efficiently and to assist with transportation planning and controlling [Miller and Sha...