共查询到20条相似文献,搜索用时 46 毫秒
1.
Jixin Liu Ling Zhao Guoying Li Shiwei Xiong Jiaofen Nan Jing Li Kai Yuan Karen M. von Deneen Fanrong Liang Wei Qin Jie Tian 《PloS one》2012,7(12)
Background
Little is known about the changes of brain structural and functional connectivity networks underlying the pathophysiology in migraine. We aimed to investigate how the cortical network reorganization is altered by frequent cortical overstimulation associated with migraine.Methodology/Principal Findings
Gray matter volumes and resting-state functional magnetic resonance imaging signal correlations were employed to construct structural and functional networks between brain regions in 43 female patients with migraine (PM) and 43 gender-matched healthy controls (HC) by using graph theory-based approaches. Compared with the HC group, the patients showed abnormal global topology in both structural and functional networks, characterized by higher mean clustering coefficients without significant change in the shortest absolute path length, which indicated that the PM lost optimal topological organization in their cortical networks. Brain hubs related to pain-processing revealed abnormal nodal centrality in both structural and functional networks, including the precentral gyrus, orbital part of the inferior frontal gyrus, parahippocampal gyrus, anterior cingulate gyrus, thalamus, temporal pole of the middle temporal gyrus and the inferior parietal gyrus. Negative correlations were found between migraine duration and regions with abnormal centrality. Furthermore, the dysfunctional connections in patients'' cortical networks formed into a connected component and three dysregulated modules were identified involving pain-related information processing and motion-processing visual networks.Conclusions
Our results may reflect brain alteration dynamics resulting from migraine and suggest that long-term and high-frequency headache attacks may cause both structural and functional connectivity network reorganization. The disrupted information exchange between brain areas in migraine may be reshaped into a hierarchical modular structure progressively. 相似文献2.
Background
Evolutionary rates of proteins in a protein-protein interaction network are primarily governed by the protein connectivity and/or expression level. A recent study revealed the importance of the features of the interacting protein partners, viz., the coefficient of functionality and clustering coefficient in controlling the protein evolutionary rates in a protein-protein interaction (PPI) network. 相似文献3.
The tracts between cortical areas are conceived as playing a central role in cortical information processing, but their actual numbers have never been determined in humans. Here, we estimate the absolute number of axons linking cortical areas from a whole-cortex diffusion MRI (dMRI) connectome, calibrated using the histologically measured callosal fiber density. Median connectivity is estimated as approximately 6,200 axons between cortical areas within hemisphere and approximately 1,300 axons interhemispherically, with axons connecting functionally related areas surprisingly sparse. For example, we estimate that <5% of the axons in the trunk of the arcuate and superior longitudinal fasciculi connect Wernicke’s and Broca’s areas. These results suggest that detailed information is transmitted between cortical areas either via linkage of the dense local connections or via rare, extraordinarily privileged long-range connections.Using data from Human Connectome Project to estimate the absolute number of axons linking cortical areas yields surprisingly sparse connectivity; reconciling large-scale functional synchronization with sparse anatomical connectivity presents a challenge for our present understanding of human brain organization. 相似文献
4.
Wei Liao Zhiqiang Zhang Zhengyong Pan Dante Mantini Jurong Ding Xujun Duan Cheng Luo Guangming Lu Huafu Chen 《PloS one》2010,5(1)
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. 相似文献5.
Semantic integration to identify overlapping functional modules in protein interaction networks 总被引:4,自引:0,他引:4
Background
The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. 相似文献6.
Nicola Trotta Serge Goldman Benjamin Legros Kristof Baete Koen Van Laere Patrick Van Bogaert Xavier De Tiège 《PloS one》2013,8(6)
Purpose
To investigate epilepsy-induced changes in effective connectivity between the non-epileptic amygdalo-hippocampal complex (AHC) and the rest of the brain in patients with unilateral mesiotemporal lobe epilepsy (MTLE) associated with hippocampal sclerosis (HS).Methods
Thirty-three patients with unilateral MTLE associated with HS (20 females, mean age: 36 years, 19 left HS) and 33 adult controls matched for age and gender underwent 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET). Right-HS patients'' FDG-PET data were flipped to obtain a left–epileptic–focus–lateralized group of patients. Voxels of interest (VOI) were selected within the cytoarchitectonic probabilistic maps of the non-epileptic AHC (probability level = 100%, SPM8 Anatomy toolbox v1.7). Patients and controls were compared using VOI metabolic activity as covariate of interest to search for epilepsy-induced changes in the contribution of the non-epileptic AHC to the level of metabolic activity in other brain areas. Age, gender, duration of epilepsy, seizure type and frequency were used as covariates of no-interest for connectivity analyses.Key findings
Significant decrease in effective connectivity was found between the non-epileptic AHC and ventral prefrontal cortical areas bilaterally, as well as with the temporal pole and the posterior cingulate cortex contralateral to HS. Significant increase in connectivity was found between the non-epileptic AHC and midline structures, such as the anterior cingulate and dorsal medial prefrontal cortices, as well as the temporo-parietal junction bilaterally. Connectivity analyses also revealed a preserved positive connectivity between the non-epileptic and the epileptic AHC in the patients'' group.Significance
This study evidences epilepsy-induced changes in connectivity between the non-epileptic AHC and some limbic and default mode network areas. These changes in connectivity probably account for emotional, cognitive and decision-making impairments frequently observed in MTLE patients. The preserved neurometabolic connectivity between the non-epileptic and the epileptic AHC in MTLE patients is pivotal to explain the epilepsy-induced changes found in this study. 相似文献7.
Yaou Liu Yunyun Duan Yong He Jun Wang Mingrui Xia Chunshui Yu Huiqing Dong Jing Ye Helmut Butzkueven Kuncheng Li Ni Shu 《PloS one》2012,7(11)
Objective
To investigate the topological alterations of the whole-brain white-matter (WM) structural networks in patients with neuromyelitis optica (NMO).Methods
The present study involved 26 NMO patients and 26 age- and sex-matched healthy controls. WM structural connectivity in each participant was imaged with diffusion-weighted MRI and represented in terms of a connectivity matrix using deterministic tractography method. Graph theory-based analyses were then performed for the characterization of brain network properties. A multiple linear regression analysis was performed on each network metric between the NMO and control groups.Results
The NMO patients exhibited abnormal small-world network properties, as indicated by increased normalized characteristic path length, increased normalized clustering and increased small-worldness. Furthermore, largely similar hub distributions of the WM structural networks were observed between NMO patients and healthy controls. However, regional efficiency in several brain areas of NMO patients was significantly reduced, which were mainly distributed in the default-mode, sensorimotor and visual systems. Furthermore, we have observed increased regional efficiency in a few brain regions such as the orbital parts of the superior and middle frontal and fusiform gyri.Conclusion
Although the NMO patients in this study had no discernible white matter T2 lesions in the brain, we hypothesize that the disrupted topological organization of WM networks provides additional evidence for subtle, widespread cerebral WM pathology in NMO. 相似文献8.
Background
Tinnitus is an auditory phantom perception that is most likely generated in the central nervous system. Most of the tinnitus research has concentrated on the auditory system. However, it was suggested recently that also non-auditory structures are involved in a global network that encodes subjective tinnitus. We tested this assumption using auditory steady state responses to entrain the tinnitus network and investigated long-range functional connectivity across various non-auditory brain regions.Methods and Findings
Using whole-head magnetoencephalography we investigated cortical connectivity by means of phase synchronization in tinnitus subjects and healthy controls. We found evidence for a deviating pattern of long-range functional connectivity in tinnitus that was strongly correlated with individual ratings of the tinnitus percept. Phase couplings between the anterior cingulum and the right frontal lobe and phase couplings between the anterior cingulum and the right parietal lobe showed significant condition x group interactions and were correlated with the individual tinnitus distress ratings only in the tinnitus condition and not in the control conditions.Conclusions
To the best of our knowledge this is the first study that demonstrates existence of a global tinnitus network of long-range cortical connections outside the central auditory system. This result extends the current knowledge of how tinnitus is generated in the brain. We propose that this global extend of the tinnitus network is crucial for the continuos perception of the tinnitus tone and a therapeutical intervention that is able to change this network should result in relief of tinnitus. 相似文献9.
Fabrizio De Vico Fallani Luciano da Fontoura Costa Francisco Aparecido Rodriguez Laura Astolfi Giovanni Vecchiato Jlenia Toppi Gianluca Borghini Febo Cincotti Donatella Mattia Serenella Salinari Roberto Isabella Fabio Babiloni 《Nonlinear biomedical physics》2010,4(Z1):S8
Background
Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory, that is a mathematical representation of a network, which is essentially reduced to nodes and connections between them.Methods
We used high-resolution EEG technology to enhance the poor spatial information of the EEG activity on the scalp and it gives a measure of the electrical activity on the cortical surface. Afterwards, we used the Directed Transfer Function (DTF) that is a multivariate spectral measure for the estimation of the directional influences between any given pair of channels in a multivariate dataset. Finally, a graph theoretical approach was used to model the brain networks as graphs. These methods were used to analyze the structure of cortical connectivity during the attempt to move a paralyzed limb in a group (N=5) of spinal cord injured patients and during the movement execution in a group (N=5) of healthy subjects.Results
Analysis performed on the cortical networks estimated from the group of normal and SCI patients revealed that both groups present few nodes with a high out-degree value (i.e. outgoing links). This property is valid in the networks estimated for all the frequency bands investigated. In particular, cingulate motor areas (CMAs) ROIs act as “hubs” for the outflow of information in both groups, SCI and healthy. Results also suggest that spinal cord injuries affect the functional architecture of the cortical network sub-serving the volition of motor acts mainly in its local feature property.In particular, a higher local efficiency E l can be observed in the SCI patients for three frequency bands, theta (3-6 Hz), alpha (7-12 Hz) and beta (13-29 Hz).By taking into account all the possible pathways between different ROI couples, we were able to separate clearly the network properties of the SCI group from the CTRL group. In particular, we report a sort of compensatory mechanism in the SCI patients for the Theta (3-6 Hz) frequency band, indicating a higher level of “activation” Ω within the cortical network during the motor task. The activation index is directly related to diffusion, a type of dynamics that underlies several biological systems including possible spreading of neuronal activation across several cortical regions.Conclusions
The present study aims at demonstrating the possible applications of graph theoretical approaches in the analyses of brain functional connectivity from EEG signals. In particular, the methodological aspects of the i) cortical activity from scalp EEG signals, ii) functional connectivity estimations iii) graph theoretical indexes are emphasized in the present paper to show their impact in a real application.10.
Background
The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. 相似文献11.
Xiao-Fei Lv Kai Liu Ying-Wei Qiu Pei-Qiang Cai Jing Li Gui-Hua Jiang Yan-Jia Deng Xue-Lin Zhang Pei-Hong Wu Chuan-Miao Xie Ge Wen 《PloS one》2015,10(3)
Background and Purpose
Increasing evidence suggests that cirrhosis may affect the connectivity among different brain regions in patients before overt hepatic encephalopathy (OHE) occurs. However, there has been no study investigating the structural reorganization of these altered connections at the network level. The primary focus of this study was to investigate the abnormal topological organization of the structural network in patients with hepatitis B virus-related cirrhosis (HBV-RC) without OHE using structural MRI.Methods
Using graph theoretical analysis, we compared the global and regional topological properties of gray matter structural networks between 28 patients with HBV-RC without OHE and 30 age-, sex- and education-matched healthy controls. The structural correlation networks were constructed for the two groups based on measures of gray matter volume.Results
The brain network of the HBV-RC group exhibited a significant decrease in the clustering coefficient and reduced small-worldness at the global level across a range of network densities. Regionally, brain areas with altered nodal degree/betweenness centrality were observed predominantly in association cortices (frontal and temporal regions) (p < 0.05, uncorrected), including a significantly decreased nodal degree in the inferior temporal gyrus (p < 0.001, uncorrected). Furthermore, the HBV-RC group exhibited a loss of association hubs and the emergence of an increased number of non-association hubs compared with the healthy controls.Conclusion
The results of this large-scale gray matter structural network study suggest reduced topological organization efficiency in patients with HBV-RC without OHE. Our findings provide new insight concerning the mechanisms of neurobiological reorganization in the HBV-RC brain from a network perspective. 相似文献12.
Franco Cauda Katiuscia Sacco Sergio Duca Dario Cocito Federico D'Agata Giuliano C. Geminiani Sergio Canavero 《PloS one》2009,4(2)
Background
The spontaneous component of neuropathic pain (NP) has not been explored sufficiently with neuroimaging techniques, given the difficulty to coax out the brain components that sustain background ongoing pain. Here, we address for the first time the correlates of this component in an fMRI study of a group of eight patients suffering from diabetic neuropathic pain and eight healthy control subjects. Specifically, we studied the functional connectivity that is associated with spontaneous neuropathic pain with spatial independent component analysis (sICA).Principal Findings
Functional connectivity analyses revealed a cortical network consisting of two anti-correlated patterns: one includes the left fusiform gyrus, the left lingual gyrus, the left inferior temporal gyrus, the right inferior occipital gyrus, the dorsal anterior cingulate cortex bilaterally, the pre and postcentral gyrus bilaterally, in which its activity is correlated negatively with pain and positively with the controls; the other includes the left precuneus, dorsolateral prefrontal, frontopolar cortex (both bilaterally), right superior frontal gyrus, left inferior frontal gyrus, thalami, both insulae, inferior parietal lobuli, right mammillary body, and a small area in the left brainstem, in which its activity is correlated positively with pain and negatively with the controls. Furthermore, a power spectra analyses revealed group differences in the frequency bands wherein the sICA signal was decomposed: patients'' spectra are shifted towards higher frequencies.Conclusion
In conclusion, we have characterized here for the first time a functional network of brain areas that mark the spontaneous component of NP. Pain is the result of aberrant default mode functional connectivity. 相似文献13.
Background
It has been previously shown that loss of consciousness is associated with a breakdown of dominating fronto-parietal feedback connectivity as assessed by electroencephalogram (EEG) recordings. Structure and strength of network connectivity may change over time. Aim of the current study is to investigate cortico-cortical connectivity at different time intervals during consciousness and unconsciousness. For this purpose, EEG symbolic transfer entropy (STEn) was calculated to indicate cortico-cortical information transfer at different transfer times.Methods
The study was performed in 15 male volunteers. 29-channel EEG was recorded during consciousness and propofol-induced unconsciousness. EEG data were analyzed by STEn, which quantifies intensity and directionality of the mutual information flow between two EEG channels. STEn was computed over fronto-parietal channel pair combinations (10 s length, 0.5–45 Hz total bandwidth) to analyze changes of intercortical directional connectivity. Feedback (fronto → parietal) and feedforward (parieto → frontal) connectivity was calculated for transfer times from 25 ms to 250 ms in 5 ms steps. Transfer times leading to maximum directed interaction were identified to detect changes of cortical information transfer (directional connectivity) induced by unconsciousness (p<0.05).Results
The current analyses show that fronto-parietal connectivity is a non-static phenomenon. Maximum detected interaction occurs at decreased transfer times during propofol-induced unconsciousness (feedback interaction: 60 ms to 40 ms, p = 0.002; feedforward interaction: 65 ms to 45 ms, p = 0.001). Strength of maximum feedback interaction decreases during unconsciousness (p = 0.026), while no effect of propofol was observed on feedforward interaction. During both consciousness and unconsciousness, intensity of fronto-parietal interaction fluctuates with increasing transfer times.Conclusion
Non-stationarity of directional connectivity may play a functional role for cortical network communication as it shows characteristic changes during propofol-induced unconsciousness. 相似文献14.
15.
Tommaso Piccoli Giancarlo Valente David E. J. Linden Marta Re Fabrizio Esposito Alexander T. Sack Francesco Di Salle 《PloS one》2015,10(4)
Introduction
The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time.Methods
To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks.Results
We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks.Conclusions
Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network. 相似文献16.
Verstraete E van den Heuvel MP Veldink JH Blanken N Mandl RC Hulshoff Pol HE van den Berg LH 《PloS one》2010,5(10):e13664
Background
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by motor neuron degeneration. How this disease affects the central motor network is largely unknown. Here, we combined for the first time structural and functional imaging measures on the motor network in patients with ALS and healthy controls.Methodology/Principal Findings
Structural measures included whole brain cortical thickness and diffusion tensor imaging (DTI) of crucial motor tracts. These structural measures were combined with functional connectivity analysis of the motor network based on resting state fMRI. Focal cortical thinning was observed in the primary motor area in patients with ALS compared to controls and was found to correlate with disease progression. DTI revealed reduced FA values in the corpus callosum and in the rostral part of the corticospinal tract. Overall functional organisation of the motor network was unchanged in patients with ALS compared to healthy controls, however the level of functional connectedness was significantly correlated with disease progression rate. Patients with increased connectedness appear to have a more progressive disease course.Conclusions/Significance
We demonstrate structural motor network deterioration in ALS with preserved functional connectivity measures. The positive correlation between functional connectedness of the motor network and disease progression rate could suggest spread of disease along functional connections of the motor network. 相似文献17.
Wynand S Verwoerd 《BMC systems biology》2011,5(1):25
Background
Compared to more general networks, biochemical networks have some special features: while generally sparse, there are a small number of highly connected metabolite nodes; and metabolite nodes can also be divided into two classes: internal nodes with associated mass balance constraints and external ones without. Based on these features, reclassifying selected internal nodes (separators) to external ones can be used to divide a large complex metabolic network into simpler subnetworks. Selection of separators based on node connectivity is commonly used but affords little detailed control and tends to produce excessive fragmentation. 相似文献18.
Background
Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization.Methodology and Principal Findings
We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network.Conclusion
The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale. 相似文献19.
20.