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Reliability of Static and Dynamic Network Metrics in the Resting-State: A MEG-beamformed Connectivity Analysis [article]

Stavros I Dimitriadis, Bethany Routley, David E Linden, Krish D Singh
2018 biorxiv/medrxiv   pre-print
This analysis encourages the analysis of MEG resting-state via DFC.  ...  The coordinated activity of the resting state can be explored via magnetoencephalography (MEG) by studying frequency-dependent functional brain networks at the source level.  ...  This criterion can be applied for each MEG source pair by setting L to their shortest-path-length.  ... 
doi:10.1101/358192 fatcat:xcvdd5kmkbcajptxxtnaylsnpe

Reliability of Static and Dynamic Network Metrics in the Resting-State: A MEG-Beamformed Connectivity Analysis

Stavros I. Dimitriadis, Bethany Routley, David E. Linden, Krish D. Singh
2018 Frontiers in Neuroscience  
This study encourages the analysis of MEG resting-state via DFC.  ...  The coordinated activity of the resting state can be explored via magnetoencephalography (MEG) by studying frequency-dependent functional brain networks at the source level.  ...  This criterion can be applied for each MEG source pair by setting L to their shortest-path-length.  ... 
doi:10.3389/fnins.2018.00506 pmid:30127710 pmcid:PMC6088195 fatcat:mpxnhkrhnfe75h3bd67zfukec4

Review on Graph Clustering and Subgraph Similarity Based Analysis of Neurological Disorders

Jaya Thomas, Dongmin Seo, Lee Sael
2016 International Journal of Molecular Sciences  
The HCS algorithm recursively finds the minimum graph cut that leads to a graph partition that outputs highly connected components or subgraphs.  ...  The characteristic path length quantifies the average minimum number of connections that link any two nodes.  ... 
doi:10.3390/ijms17060862 pmid:27258269 pmcid:PMC4926396 fatcat:42vgbgz6erg2jaquohdirhw4ge

A hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration

J Olamaei, A Arefi, A H Mazinan, T Niknam
2010 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)  
It discovers the set of functional communities using only the structural connection between users and without using any content information.  ...  Graph mining techniques are commonly used for knowledge discovery in social networks to unveil intricate structural patterns among users.  ...  The map equation-based methods are proposed based on minimizing the descriptive length of the code-words given to the vertexes along the random walk.  ... 
doi:10.1109/iccae.2010.5451699 fatcat:xtkq7vrlzvd33ft2wysg7q2jny

Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

Mahdi Jalili
2016 Scientific Reports  
In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and densitypreserving methods.  ...  ), Magnetocephalography (MEG) or functional Magnetic Resonance Imaging (fMIR) modalities 3-5 .  ...  These studies used various neuroimaging modalities including fMRI, PET, EEG and MEG.  ... 
doi:10.1038/srep29780 pmid:27417262 pmcid:PMC4945914 fatcat:xx5kpm3b2fccviifona72imdym

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations

Kanad Mandke, Jil Meier, Matthew J. Brookes, Reuben D. O'Dea, Piet Van Mieghem, Cornelis J. Stam, Arjan Hillebrand, Prejaas Tewarie
2018 NeuroImage  
In such a description, nodes in the network correspond to anatomical regions and links typically refer to either structural or functional connections between those regions.  ...  Various metrics, describing both nodal and global topological network characteristics, have been shown to provide useful quantitative descriptions of networks in order to reveal common pathways across  ...  Data used were collected as part of the University of Nottingham Multimodal Imaging Study in Psychosis, funded by the Medical Research Council (MR/J01186X/1).  ... 
doi:10.1016/j.neuroimage.2017.11.016 pmid:29138088 fatcat:tykal74btrbsvkxxsgp3d5bqly

Intra- and Inter-Frequency Brain Network Structure in Health and Schizophrenia [article]

Felix Siebenhuhner, Shennan A. Weiss, Richard Coppola, Daniel R. Weinberger, Danielle S. Bassett
2012 arXiv   pre-print
In this study, we perform an extensive analysis of functional connectivity patterns extracted from MEG data in 14 subjects with schizophrenia and 14 healthy controls during a 2-back working memory task  ...  of nodes and edges connected to node i and L j,k is the minimum path length between nodes j and k in the subgraph [53] .  ...  Regional efficiency is therefore inversely related to minimum path length and a region with high efficiency will have short minimum path length to all other regions in the graph.  ... 
arXiv:1209.0729v1 fatcat:3lj3yvs3vjewda46lcazx5egyq

Clustering and community detection in directed networks: A survey

Fragkiskos D. Malliaros, Michalis Vazirgiannis
2013 Physics reports  
Networks (or graphs) appear as dominant structures in diverse domains, including sociology, biology, neuroscience and computer science.  ...  Revealing the underlying community structure of directed complex networks has become a crucial and interdisciplinary topic with a plethora of applications.  ...  Then, the clustering problem can be expressed as finding the partition that yields the minimum description code length.  ... 
doi:10.1016/j.physrep.2013.08.002 fatcat:qyj2bq6j5vbhhlcoyqnjgrmgwu

Integrative Models of Brain Structure and Dynamics: Concepts, Challenges, and Methods

Siva Venkadesh, John Darrell Van Horn
2021 Frontiers in Neuroscience  
as Diffusion-weighted Magnetic Resonance Imaging (dMRI), Electroencephalography (EEG), Magnetoencephalography (MEG), and functional Magnetic Resonance Imaging (fMRI). dMRI measures the anisotropy of water  ...  EEG and MEG signals measure electrical activity and magnetic fields induced by the electrical activity, respectively, from various brain regions with a high temporal resolution (but limited spatial coverage  ...  Frameworks to Characterize Network Dynamics Description of functional connectivity that emphasizes temporal evolution and collective dynamics maybe more meaningful than the spatialized descriptions based  ... 
doi:10.3389/fnins.2021.752332 pmid:34776853 pmcid:PMC8585845 fatcat:rgcwmry7tjfa3ciqo6fggnnaea

Brain Graphs: Graphical Models of the Human Brain Connectome

Edward T. Bullmore, Danielle S. Bassett
2011 Annual Review of Clinical Psychology  
regions or recording electrodes) and interconnecting edges (denoting structural or functional connections).  ...  Brain graphs provide a relatively simple and increasingly popular way of modeling the human brain connectome, using graph theory to abstractly define a nervous system as a set of nodes (denoting anatomical  ...  MEG).  ... 
doi:10.1146/annurev-clinpsy-040510-143934 pmid:21128784 fatcat:ggvwjpajkrhmtcutrhwbkvcluy

Combining complex networks and data mining: Why and how

M. Zanin, D. Papo, P.A. Sousa, E. Menasalvas, A. Nicchi, E. Kubik, S. Boccaletti
2016 Physics reports  
The increasing power of computer technology does not dispense with the need to extract meaningful in- formation out of data sets of ever growing size, and indeed typically exacerbates the complexity of  ...  A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented.  ...  A classical concept of graph theory, a MST is the shortest-length tree subgraph that contains all the nodes of the original network.  ... 
doi:10.1016/j.physrep.2016.04.005 fatcat:dp33n23k7vhdfg7nm6lfo57adu

A Graphlet-Based Topological Characterization of the Resting-State Network in Healthy People

Paolo Finotelli, Carlo Piccardi, Edie Miglio, Paolo Dulio
2021 Frontiers in Neuroscience  
Then, we select a number of working graphlets, namely, connected and non-isomorphic induced subgraphs.  ...  We compute, for each labeled node, its Graphlet Degree Vector (GDV), which allows us to associate a GDV matrix to each one of the 133 subjects of the considered sample, reporting how many times each node  ...  Typically, a large average silhouette value over a cluster reveals its significance, and a large average value over all objects i denotes a meaningful partition.  ... 
doi:10.3389/fnins.2021.665544 pmid:33994939 pmcid:PMC8113409 fatcat:nzulzc2jbngejgr3jovjne6u6y

The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition

J. R. Cohen, M. D'Esposito
2016 Journal of Neuroscience  
the performance of a variety of cognitive tasks, there are meaningful differences as well.  ...  Existing research probing task-related reconfiguration of brain network structure has concluded that, although there are many similarities in network structure during an intrinsic, resting state and during  ...  Both are calculated using the metric of minimum path length (L), which counts the smallest number of edges that must be crossed to get from node i to node j.  ... 
doi:10.1523/jneurosci.2965-15.2016 pmid:27903719 pmcid:PMC5148214 fatcat:shki62k57bf6vezl6g7gtqbmmi

Constraint-based Ontology Induction from Online Customer Reviews

Thomas Lee
2006 Group Decision and Negotiation  
Using shallow natural language processing techniques, reviews are parsed into phrase sequences where each phrase refers to a single concept.  ...  Using shallow natural language processing techniques, reviews are parsed into phrase sequences where each phrase refers to a single concept.  ...  Our objective is to automatically learn a structured vocabulary to support the use and integration of online product information.  ... 
doi:10.1007/s10726-006-9065-3 fatcat:kmj7iop2endcxh653wsvumsci4

Combining complex networks and data mining: why and how [article]

Massimiliano Zanin, David Papo, Pedro A. Sousa, Ernestina Menasalvas, Andrea Nicchi, Elaine Kubik, Stefano Boccaletti
2016 bioRxiv   pre-print
The increasing power of computer technology does not dispense with the need to extract meaningful in- formation out of data sets of ever growing size, and indeed typically exacerbates the complexity of  ...  A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented.  ...  A classical concept of graph theory, a MST is the shortest-length tree subgraph that contains all the nodes of the original network.  ... 
doi:10.1101/054064 fatcat:ncnw5vdvnfawxiq52vyzqtziuu
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