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Sepsis is a global health care issue that affects millions of people. DNA methyltransferase I (DNMT1)-mediated DNA methylation is involved in a number of human diseases by affecting many types of cellular progression events. However, the role and underlying molecular mechanism of DNMT1 in development of sepsis remain largely unknown. Lipopolysaccharide (LPS) induced lung fibrosis in the sepsis mouse model, and

Growth hormone deficiency (GHD) is a common developmental disorder in children characterized by low levels of growth hormone secretion, short stature, and multiple cognitive and behavioral problems, including hyperactivity, anxiety, and depression. However, the pathophysiology of this disorder remains unclear. In order to investigate abnormalities of brain functioning in children with GHD, we preformed functional magnetic resonance imaging and regional homogeneity (ReHo) analysis in 26 children with GHD and 15 age- and sex-matched healthy controls (HCs) in a resting state. Compared with HCs, children with GHD exhibited increased ReHo in the left putamen and decreased ReHo in the right precentral gyrus, reflecting a dysfunction of inhibitory control. Decreased ReHo was also identified in the orbital parts of the bilateral superior frontal gyrus and the medial part of the left superior frontal gyrus, a finding that correlated with the inappropriate anxiety and depression that are observed in this patient population. Our results provide imaging evidence of potential pathophysiologic mechanisms for the cognitive and behavioral abnormalities of children with GHD.

Asprosin, a recently discovered adipokine, stimulates the release of hepatic glucose. The purpose of the current research was to determine the relation between serum asprosin and obstructive sleep apnea syndrome (OSAS). The current investigation enrolled 152 patients with OSAS and 97 control subjects. Serum asprosin concentrations were measured and analyzed. Higher serum asprosin concentrations were found in patients with OSAS than in the controls. Logistic regression analysis demonstrated that serum asprosin concentrations were associated with an increased risk of OSAS. Patients with severe OSAS had significantly increased asprosin compared to mild and moderate groups. The group with moderate OSAS showed higher serum asprosin levels than the group with mild OSAS. Pearson correlation analysis demonstrated a positive relation between serum asprosin and disease severity. Simple linear regression analyses showed a significant correlation between serum asprosin with body mass index (BMI), fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides (TG), and apnea-hypopnea index (AHI), and negatively correlated with high-density lipoprotein cholesterol (HDL-C). Multiple linear regression analysis revealed a significant correlation between serum asprosin with BMI, FPG, HOMA-IR, TG, AHI, and HDL-C. There is a significant correlation between serum asprosin with the presence and severity of OSAS.

White matter lesions (WMLs) have been associated with cognitive and motor decline. Resting state networks (RSNs) are spatially coherent patterns in the human brain and their interactions sustain our daily function. Therefore, investigating the altered intra- and inter-network connectivity among the RSNs may help to understand the association of WMLs with impaired cognitive and motor function. Here, we assessed alterations in functional connectivity patterns based on six well-defined RSNs—the default mode network (DMN), dorsal attention network (DAN), frontal-parietal control network (FPCN), auditory network (AN), sensory motor network (SMN) and visual network (VN)—in 15 patients with ischemic WMLs and 15 controls. In the patients, Spearman’s correlation analysis was further performed between these alterations and cognitive test scores, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Our results showed wide alterations of inter-network connectivity mainly involving the SMN, DMN, FPCN and DAN, and some alterations correlated with cognitive test scores in the patients. The reduced functional connectivities in the SMN-AN, SMN-VN, FPCN-AN, DAN-VN pairs may account for the cognitive and motor decline in patients with ischemic WMLs, while the increased functional connectivities in the DMN-AN, DMN-FPCN and DAN-FPCN pairs may reflect a functional network reorganization after damage to white matter. It is unexpected that altered intra-network connectivities were found within the AN and VN, which may explain the impairments in verbal fluency and information retrieval associated with WMLs. This study highlights the importance of functional connectivity in understanding how WMLs influence cognitive and behavior dysfunction.

Growth hormone deficiency (GHD) is a developmental disorder caused by the partial or complete deficiency of growth hormone secreted by the pituitary gland, or its receptor. Patients with GHD are characterized by short stature, slow growth, and certain cognitive and behavioral abnormalities. Previous behavioral and neuroimaging studies indicate that GHD might affect the brain functional activity associated with cognitive and behavioral abilities. We thus investigated the spontaneous neural activity in children with GHD using amplitude of low-frequency fluctuation (ALFF) analysis. ALFF was calculated based on resting-state functional magnetic resonance imaging (rs-fMRI) data in 26 children with GHD and 15 age- and sex-matched healthy controls (HCs). Comparative analysis revealed that the ALFF of the right lingual gyrus and angular gyrus were significantly increased, while the ALFF of the right dorsolateral superior frontal gyrus, the left postcentral gyrus, superior parietal gyrus and middle temporal gyrus were significantly decreased in children with GHD relative to HCs. These findings support the presence of abnormal brain functional activity in children with GHD, which may account for the abnormal cognition and behavior, such as aggression, somatic complaints, attention deficits, and language withdrawal. This study provides imaging evidence for future studies on the pathophysiological mechanisms of abnormal behavior and cognition in children with GHD.

Brain metastases are the most prevalent cerebral tumors. Resting state networks (RSNs) are involved in multiple perceptual and cognitive functions. Therefore, precisely localizing multiple RSNs may be extremely valuable before surgical resection of metastases, to minimize neurocognitive impairments. Here we aimed to investigate the reliability of independent component analysis (ICA) for localizing multiple RSNs from resting-state functional MRI (rs-fMRI) data in individual patients, and further evaluate lesion-related spatial shifts of the RSNs. Twelve patients with brain metastases and 14 healthy controls were recruited. Using an improved automatic component identification method, we successfully identified seven common RSNs, including: the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), language network (LN), sensorimotor network (SMN), auditory network (AN) and visual network (VN), in both individual patients and controls. Moreover, the RSNs in the patients showed a visible spatial shift compared to those in the controls, and the spatial shift of some regions was related to the tumor location, which may reflect a complicated functional mechanism - functional disruptions and reorganizations - caused by metastases. Besides, higher cognitive networks (DMN, ECN, DAN and LN) showed significantly larger spatial shifts than perceptual networks (SMN, AN and VN), supporting a functional dichotomy between the two network groups even in pathologic alterations associated with metastases. Overall, our findings provide evidence that ICA is a promising approach for presurgical localization of multiple RSNs from rs-fMRI data in individual patients. More attention should be paid to the spatial shifts of the RSNs before surgical resection.

Myxopapillary ependymoma (MPE) is a rare variant of ependymoma that is most commonly located in the cauda equina and filum terminale. We present a case of 23-year-old man diagnosed with MPE in the fourth ventricle and sacral canal area with extensive disseminated lesions along the cerebrospinal ventricular system. Additionally, a molecular pathological diagnosis was performed. The patient underwent a craniotomy and a lumbar laminectomy. In the course of 18 months of follow-up, the patient have recovered very well.

In this study, small-world network analysis was performed to identify the similarities and differences between functional brain networks for right- and left-hand motor imageries (MIs). First, Pearson correlation coefficients among the nodes within the functional brain networks from healthy subjects were calculated. Then, small-world network indicators, including the clustering coefficient, the average path length, the global efficiency, the local efficiency, the average node degree, and the small-world index, were generated for the functional brain networks during both right- and left-hand MIs. We identified large differences in the small-world network indicators between the functional networks during MI and in the random networks. More importantly, the functional brain networks underlying the right- and left-hand MIs exhibited similar small-world properties in terms of the clustering coefficient, the average path length, the global efficiency, and the local efficiency. By contrast, the right- and left-hand MI brain networks showed differences in small-world characteristics, including indicators such as the average node degree and the small-world index. Interestingly, our findings also suggested that the differences in the activity intensity and range, the average node degree, and the small-world index of brain networks between the right- and left-hand MIs were associated with the asymmetry of brain functions.

There is increasing evidence that white matter lesions (WMLs) are associated with cognitive impairments. The purpose of this study was to explore the relationship of WMLs with cognitive impairments from the aspect of cortical functional activity. Briefly, Sixteen patients with ischemic WMLs and 13 controls participated in this study. A regional homogeneity (ReHo) approach was used to investigate altered neural coherence in patients with ischemic WMLs during the resting state. A correlation analysis was further performed between regions with altered ReHo and cognitive test scores, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), in the patient group. Finally, we found regions with altered ReHo values in patients with ischemic WMLs to be involved in default mode network (DMN), frontal-parietal control network (FPCN), dorsal attention network (DAN), motor network and right temporal cortex. Moreover, some altered regions belonging to DMN, FPCN and motor network were significantly correlated with cognitive test scores. Our results provide neuroimaging evidence for the impairments of memory, attention, executive and motor function in patients with ischemic WMLs. It is interesting to note that the decreased ReHo was mainly in the anterior brain regions, while increased ReHo in the posterior brain regions, which may indicate a failure down regulation of spontaneous activity in posterior regions. In summary, this study indicates an important role of specific cortical dysfunction in cognitive associated with WMLs.

Studies of in mesial temporal lobe epilepsy (mTLE) patients with hippocampal sclerosis (HS) have reported reductions in both functional and structural connectivity between hippocampal structures and adjacent brain regions. However, little is known about the connectivity among the default mode network (DMN) in mTLE. Here, we hypothesized that both functional and structural connectivity within the DMN were disturbed in mTLE. To test this hypothesis, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were applied to examine the DMN connectivity of 20 mTLE patients, and 20 gender‐ and age‐matched healthy controls. Combining these two techniques, we explored the changes in functional (temporal correlation coefficient derived from fMRI) and structural (path length and connection density derived from DTI tractography) connectivity of the DMN. Compared to the controls, we found that both functional and structural connectivity were significantly decreased between the posterior cingulate cortex (PCC)/precuneus (PCUN) and bilateral mesial temporal lobes (mTLs) in patients. No significant between‐group difference was found between the PCC/PCUN and medial prefrontal cortex (mPFC). In addition, functional connectivity was found to be correlated with structural connectivity in two pairwise regions, namely between the PCC/PCUN and bilateral mTLs, respectively. Our results suggest that the decreased functional connectivity within the DMN in mTLE may be a consequence of the decreased connection density underpinning the degeneration of structural connectivity. Hum Brain Mapp, 2011. © 2010 Wiley‐Liss, Inc.

The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings suggest that the decoupling of functional and structural connectivity may reflect the progress of long-term impairment in idiopathic generalized epilepsy, and may be used as a potential biomarker to detect subtle brain abnormalities in epilepsy. Overall, our results demonstrate for the first time that idiopathic generalized epilepsy is reflected in a disrupted topological organization in large-scale brain functional and structural networks, thus providing valuable information for better understanding the pathophysiological mechanisms of generalized tonic–clonic seizures. * Abbreviations : AAL : automated anatomical labelling GTCS : generalized tonic–clonic seizures IGE : idiopathic generalized epilepsy

In social anxiety disorder (SAD), impairments in limbic/paralimbic structures are associated with emotional dysregulation and inhibition of the medial prefrontal cortex (MPFC). Little is known, however, about alterations in limbic and frontal regions associated with the integrated morphometric, functional, and structural architecture of SAD. Whether altered gray matter volume is associated with altered functional and structural connectivity in SAD. Three techniques were used with 18 SAD patients and 18 healthy controls: voxel-based morphometry; resting-state functional connectivity analysis; and diffusion tensor imaging tractography. SAD patients exhibited significantly decreased gray matter volumes in the right posterior inferior temporal gyrus (ITG) and right parahippocampal/hippocampal gyrus (PHG/HIP). Gray matter volumes in these two regions negatively correlated with the fear factor of the Liebowitz Social Anxiety Scale. In addition, we found increased functional connectivity in SAD patients between the right posterior ITG and the left inferior occipital gyrus, and between the right PHF/HIP and left middle temporal gyrus. SAD patients had increased right MPFC volume, along with enhanced structural connectivity in the genu of the corpus callosum. Reduced limbic/paralimbic volume, together with increased resting-state functional connectivity, suggests the existence of a compensatory mechanism in SAD. Increased MPFC volume, consonant with enhanced structural connectivity, suggests a long-time overgeneralization of structural connectivity and a role of this area in the mediation of clinical severity. Overall, our results may provide a valuable basis for future studies combining morphometric, functional and anatomical data in the search for a comprehensive understanding of the neural circuitry underlying SAD.

Small-world organization is known to be a robust and consistent network architecture, and is a hallmark of the structurally and functionally connected human brain. However, it remains unknown if the same organization is present in directed influence brain networks whose connectivity is inferred by the transfer of information from one node to another. Here, we aimed to reveal the network architecture of the directed influence brain network using multivariate Granger causality analysis and graph theory on resting-state fMRI recordings. We found that some regions acted as pivotal hubs, either being influenced by or influencing other regions, and thus could be considered as information convergence regions. In addition, we observed that an exponentially truncated power law fits the topological distribution for the degree of total incoming and outgoing connectivity. Furthermore, we also found that this directed network has a modular structure. More importantly, according to our data, we suggest that the human brain directed influence network could have a prominent small-world topological property.

Summary Purpose Psychogenic non-epileptic seizures (PNES) are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Some neuroimaging studies have reported that PNES exhibits aberrant functional connectivity in specific brain networks. Thus, advanced neuroimaging technologies may aid clinical diagnosis and treatment of PNES. Methods We investigated changes in brain functional connectivity in 18 patients with PNES and 20 healthy controls. Functional connectivity density mapping (FCDM), a voxelwise data-driven technique, was employed to compute local and global FCD maps. Then, short-range and long-range FCD values were calculated and group analyses performed between patents with PNES and healthy controls. A correlation analysis with clinical variables was also performed. Results We found that patients with PNES showed abnormal FCD regions mainly in the frontal cortex, sensorimotor cortex, cingulate gyrus, insula and occipital cortex. Seed-voxel correlation analyses also showed disrupted functional connectivity between these regions. In addition, the occipital cortex FCD correlated with duration of disease. Conclusion The present results support the hypothesis that patients with PNES are associated with altered attention, sensorimotor and emotion systems. Furthermore, correlations between altered regions in the occipital cortex and duration of disease may reflect an adaptation in these patients for long-term hypervigilance and increased response to external stimuli. This study adds new knowledge to our understanding of the pathophysiological mechanisms underlying PNES.

Recent research has shown that social anxiety disorder (SAD) is accompanied by abnormalities in brain functional connections. However, these findings are based on group comparisons, and, therefore, little is known about whether functional connections could be used in the diagnosis of an individual patient with SAD. Here, we explored the potential of the functional connectivity to be used for SAD diagnosis. Twenty patients with SAD and 20 healthy controls were scanned using resting-state functional magnetic resonance imaging. The whole brain was divided into 116 regions based on automated anatomical labeling atlas. The functional connectivity between each pair of regions was computed using Pearson’s correlation coefficient and used as classification feature. Multivariate pattern analysis was then used to classify patients from healthy controls. The pattern classifier was designed using linear support vector machine. Experimental results showed a correct classification rate of 82.5 % (p

Psychogenic non-epileptic seizures (PNES) are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Recent studies suggest aberrant functional connectivity involving specific brain regions in PNES. Little is known, however, about alterations of topological organization of whole-brain functional and structural connectivity networks in PNES. We constructed functional connectivity networks from resting-state functional MRI signal correlations and structural connectivity networks from diffusion tensor imaging tractography in 17 PNES patients and 20 healthy controls. Graph theoretical analysis was employed to compute network properties. Moreover, we investigated the relationship between functional and structural connectivity networks. We found that PNES patients exhibited altered small-worldness in both functional and structural networks and shifted towards a more regular (lattice-like) organization, which could serve as a potential imaging biomarker for PNES. In addition, many regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect disease-specific pathophysiology in PNES. Importantly, the coupling strength of functional-structural connectivity was decreased and exhibited high sensitivity and specificity to differentiate PNES patients from healthy controls, suggesting that the decoupling strength of functional-structural connectivity might be an important characteristic reflecting the mechanisms of PNES. This is the first study to explore the altered topological organization in PNES combining functional and structural connectivity networks, providing a new way to understand the pathophysiological mechanisms of PNES.

White matter lesions (WMLs) are frequently detected in elderly people. Previous structural and functional studies have demonstrated that WMLs are associated with cognitive and motor decline. However, the underlying mechanism of how WMLs lead to cognitive decline and motor disturbance remains unclear. We used functional connectivity density mapping (FCDM) to investigate changes in brain functional connectivity in 16 patients with ischemic WMLs and 13 controls. Both short- and long-range FCD maps were computed, and group comparisons were performed between the 2 groups. A correlation analysis was further performed between regions with altered FCD and cognitive test scores (Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]) in the patient group. We found that patients with ischemic WMLs showed reduced short-range FCD in the temporal cortex, primary motor cortex, and subcortical region, which may account for inadequate top-down attention, impaired motor, memory, and executive function associated with WMLs. The positive correlation between primary motor cortex and MoCA scores may provide evidence for the influences of cognitive function on behavioral performance. The inferior parietal cortex exhibited increased short-range FCD, reflecting a hyper bottom-up attention to compensate for the inadequate top-down attention for language comprehension and information retrieval in patients with WMLs. Moreover, the prefrontal and primary motor cortex showed increased long-range FCD and the former positively correlated with MoCA scores, which may suggest a strategy of cortical functional reorganization to compensate for motor and executive deficits. Our findings provide new insights into how WMLs cause cognitive and motor decline from cortical functional connectivity perspective.

Magnetic resonance imaging (MRI) studies have indicated that the structure deficits and resting-state functional connectivity (FC) imbalances in cortico-limbic circuitry might underline the pathophysiology of MDD. Using structure and functional MRI, our aim is to investigate gray matter abnormalities in patients with treatment-resistant depression (TRD) and treatment-responsive depression (TSD), and test whether the altered gray matter is associated with altered FC. Voxel-based morphometry was used to investigate the regions with gray matter abnormality and FC analysis was further conducted between each gray matter abnormal region and the remaining voxels in the brain. Using one-way analysis of variance, we found significant gray matter abnormalities in the right middle temporal cortex (MTG) and bilateral caudate among the TRD, TSD and healthy controls. For the FC of the right MTG, we found that both the patients with TRD and TSD showed altered connectivity mainly in the default-mode network (DMN). For the FC of the right caudate, both patient groups showed altered connectivity in the frontal regions. Our results revealed the gray matter reduction of right MTG and bilateral caudate, and disrupted functional connection to widely distributed circuitry in DMN and frontal regions, respectively. These results suggest that the abnormal DMN and reward circuit activity might be biomarkers of depression trait.

A great improvement to the insight on brain function that we can get from fMRI data can come from effective connectivity analysis, in which the flow of information between even remote brain regions is inferred by the parameters of a predictive dynamical model. As opposed to biologically inspired models, some techniques as Granger causality (GC) are purely data-driven and rely on statistical prediction and temporal precedence. While powerful and widely applicable, this approach could suffer from two main limitations when applied to BOLD fMRI data: confounding effect of hemodynamic response function (HRF) and conditioning to a large number of variables in presence of short time series. For task-related fMRI, neural population dynamics can be captured by modeling signal dynamics with explicit exogenous inputs; for resting-state fMRI on the other hand, the absence of explicit inputs makes this task more difficult, unless relying on some specific prior physiological hypothesis. In order to overcome these issues and to allow a more general approach, here we present a simple and novel blind-deconvolution technique for BOLD-fMRI signal. In a recent study it has been proposed that relevant information in resting-state fMRI can be obtained by inspecting the discrete events resulting in relatively large amplitude BOLD signal peaks. Following this idea, we consider resting fMRI as ‘spontaneous event-related’, we individuate point processes corresponding to signal fluctuations with a given signature, extract a region-specific HRF and use it in deconvolution, after following an alignment procedure. Coming to the second limitation, a fully multivariate conditioning with short and noisy data leads to computational problems due to overfitting. Furthermore, conceptual issues arise in presence of redundancy. We thus apply partial conditioning to a limited subset of variables in the framework of information theory, as recently proposed. Mixing these two improvements we compare the differences between BOLD and deconvolved BOLD level effective networks and draw some conclusions.

There is an increasing body of evidence pointing to a relationship between personality and brain markers. The purpose of this study was to identify the associations between personality dimensions of extraversion and neuroticism and the local synchronization of spontaneous blood oxygen level-dependent (BOLD) activity assessed by regional homogeneity (ReHo) approach. Our results revealed the significant negative correlation between neuroticism and ReHo in the left middle frontal gyrus, providing evidence for the left frontal activation involved in pleasant emotion. ReHo was correlated negatively with extraversion in the medial prefrontal cortex (MPFC), an important portion of the default mode network (DMN), thus further indicating the relationship between DMN and personality. In addition, ReHo in the insula, cerebellum and cingulate gyrus was correlated positively with extraversion, suggesting the associations between individual difference in extraversion and specific brain regions involved in affective processing. These findings shed light on the important relationship between the synchronization of spontaneous fluctuations and personality dimensions of extraversion and neuroticism, which provide further evidence for the neural underpinning of individual difference in personality traits.

Brain functional activation of decision-making on fMRI experiment is seldom analyzed by data driven method to reveal the distinct brain functional network of decision-making. In this paper, a spatial independent component analysis (sICA) is presented to detect the functional network underlying decision-making by analyzing the unmixing matrices temporal components corresponding to spatial separated pattern. Our results show that ICA could separate various sub-functional activation networks to understand the neural mechanisms underlying decision-making, which mainly include functional network of conflict detection, cognitive and emotion.

Several functional MRI (fMRI) activation studies have highlighted specific differences in brain response in social anxiety disorder (SAD) patients. Little is known, so far, about the changes in the functional architecture of resting state networks (RSNs) in SAD during resting state. We investigated statistical differences in RSNs on 20 SAD and 20 controls using independent component analysis. A diffuse impact on widely distributed RSNs and selective changes of RSN intrinsic functional connectivity were observed in SAD. Functional connectivity was decreased in the somato-motor (primary and motor cortices) and visual (primary visual cortex) networks, increased in a network including medial prefrontal cortex which is thought to be involved in self-referential processes, and increased or decreased in the default mode network (posterior cingulate cortex/precuneus, bilateral inferior parietal gyrus, angular gyrus, middle temporal gyrus, and superior and medial frontal gyrus) which has been suggested to be involved in episodic memory, and self-projection, the dorsal attention network (middle and superior occipital gyrus, inferior and superior parietal gyrus, and middle and superior frontal gyrus) which is thought to mediate goal-directed top-down processing, the core network (insula-cingulate cortices) which is associated with task control function, and the central-executive network (fronto-parietal cortices). A relationship between functional connectivity and disease severity was found in specific regions of RSNs, including medial and lateral prefrontal cortex, as well as parietal and occipital regions. Our results might supply a novel way to look into neuro-pathophysiological mechanisms in SAD patients.

Dysfunction of the corticolimbic circuitry has been highlighted in social anxiety disorder (SAD) during social stimuli. However, few studies have investigated functional connectivity in SAD during the resting state, which may improve our understanding of SAD pathophysiology. The aim of this study was to investigate whether whole-brain functional connectivity might be aberrant in SAD patients, and if so, whether these changes are related to the measured clinical severity. Seventeen SAD patients and 19 healthy controls participated in resting-state functional magnetic resonance imaging. The brain was first divided into 90 paired brain regions and functional connectivity was then estimated by temporal correlation between each of these regions. Furthermore, connections that were significantly disrupted in SAD patients were correlated with clinical severity measured using the Liebowitz Social Anxiety Scale. Compared with healthy controls, SAD patients showed decreased positive connections within the frontal lobe and decreased negative connections between the frontal and occipital lobes. In particular, the weaker negative connections between the frontal lobe, which mainly involved the right median prefrontal cortex, and the occipital lobe had a significant positive correlation with the severity of SAD symptoms. The results support the hypothesis that some abnormalities of functional connectivity exist in SAD patients, which relate to the frontal cortex and occipital cortex. In addition, decreased functional connectivity between the frontal and occipital lobes and within the frontal lobe might be related to abnormal information processing and reflect disturbed neural organization resulting in defective social cognition, which could represent an early imaging biomarker for SAD.

The previous task-based or resting perfusion studies in social anxiety disorder (SAD) patients have highlighted specific differences in brain response. Little is known about the changes in the local synchronization of spontaneous functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) signals that occur in SAD during the resting state. We investigated altered neural activity in the resting state using a regional homogeneity (ReHo) analysis on 20 SAD and 20 healthy controls (HC). Compared with HC, SAD patients exhibited decreased coherence (ReHo) in the bilateral angular gyrus and the left medial prefrontal cortex within the default mode network (DMN), suggesting functional impairment of the perception of socially relevant emotional state and self-related mental representations; and also in the right dorsolateral prefrontal cortex and right inferior parietal gyrus within the central-executive network (CEN), reflecting the deficit of cognitive control of social anxiety. Significantly increased coherence (ReHo) was found in the left middle occipital gyrus, which would be consistent with their hypervigilance and hyperprosexia to the social communication even in the resting state. Our results might supply a novel way to look into neuro-pathophysiological mechanisms in SAD patients.

Background The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low–frequency coherent neuronal fluctuations that can be observed in a resting state condition. Little is known, so far, about the changes in functional connectivity and in the topological properties of functional networks, associated with different brain diseases. Methodology/Principal Findings In this study, we investigated alterations related to mesial temporal lobe epilepsy (mTLE), using resting state functional magnetic resonance imaging on 18 mTLE patients and 27 healthy controls. Functional connectivity among 90 cortical and subcortical regions was measured by temporal correlation. The related values were analyzed to construct a set of undirected graphs. Compared to controls, mTLE patients showed significantly increased connectivity within the medial temporal lobes, but also significantly decreased connectivity within the frontal and parietal lobes, and between frontal and parietal lobes. Our findings demonstrated that a large number of areas in the default-mode network of mTLE patients showed a significantly decreased number of connections to other regions. Furthermore, we observed altered small-world properties in patients, along with smaller degree of connectivity, increased n-to-1 connectivity, smaller absolute clustering coefficients and shorter absolute path length. Conclusions/Significance We suggest that the mTLE alterations observed in functional connectivity and topological properties may be used to define tentative disease markers.

The human brain has been documented to be spatially organized in a finite set of specific coherent patterns, namely resting state networks (RSNs). The interactions among RSNs, being potentially dynamic and directional, may not be adequately captured by simple correlation or anticorrelation. In order to evaluate the possible effective connectivity within those RSNs, we applied a conditional Granger causality analysis (CGCA) to the RSNs retrieved by independent component analysis (ICA) from resting state functional magnetic resonance imaging (fMRI) data. Our analysis provided evidence for specific causal influences among the detected RSNs: default-mode, dorsal attention, core, central-executive, self-referential, somatosensory, visual, and auditory networks. In particular, we identified that self-referential and default-mode networks (DMNs) play distinct and crucial roles in the human brain functional architecture. Specifically, the former RSN exerted the strongest causal influence over the other RSNs, revealing a top-down modulation of self-referential mental activity (SRN) over sensory and cognitive processing. In quite contrast, the latter RSN was profoundly affected by the other RSNs, which may underlie an integration of information from primary function and higher level cognition networks, consistent with previous task-related studies. Overall, our results revealed the causal influences among these RSNs at different processing levels, and supplied information for a deeper understanding of the brain network dynamics.

e18506 Background: Clinical trials have demonstrated that adjuvant chemotherapy (ACT) can improve survival in selected patients with completely resected NSCLC. Even though, those patients are still...

Exploring topological properties of human brain network has become an exciting topic in neuroscience research. Large-scale structural and functional brain networks both exhibit a small-world topology, which is evidence for global and local parallel information processing. Meanwhile, resting state networks (RSNs) underlying specific biological functions have provided insights into how intrinsic functional architecture influences cognitive and perceptual information processing. However, topological properties of single RSNs remain poorly understood. Here, we have two hypotheses: i) each RSN also has optimized small-world architecture; ii) topological properties of RSNs related to perceptual and higher cognitive processes are different. To test these hypotheses, we investigated the topological properties of the default-mode, dorsal attention, central-executive, somato-motor, visual and auditory networks derived from resting-state functional magnetic resonance imaging (fMRI). We found small-world topology in each RSN. Furthermore, small-world properties of cognitive networks were higher than those of perceptual networks. Our findings are the first to demonstrate a topological fractionation between perceptual and higher cognitive networks. Our approach may be useful for clinical research, especially for diseases that show selective abnormal connectivity in specific brain networks. ispartof: PLoS One vol:6 issue:10 ispartof: location:United States status: published