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Graph Theory

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https://www.readbyqxmd.com/read/27922640/brain-network-reorganization-differs-in-response-to-stress-in-rats-genetically-predisposed-to-depression-and-stress-resilient-rats
#1
N Gass, R Becker, A J Schwarz, W Weber-Fahr, C Clemm von Hohenberg, B Vollmayr, A Sartorius
Treatment-resistant depression (TRD) remains a pressing clinical problem. Optimizing treatment requires better definition of the specificity of the involved brain circuits. The rat strain bred for negative cognitive state (NC) represents a genetic animal model of TRD with high face, construct and predictive validity. Vice versa, the positive cognitive state (PC) strain represents a stress-resilient phenotype. Although NC rats show depressive-like behavior, some symptoms such as anhedonia require an external trigger, i...
December 6, 2016: Translational Psychiatry
https://www.readbyqxmd.com/read/27920976/resting-state-theta-band-connectivity-and-graph-analysis-in-generalized-social-anxiety-disorder
#2
Mengqi Xing, Reza Tadayonnejad, Annmarie MacNamara, Olusola Ajilore, Julia DiGangi, K Luan Phan, Alex Leow, Heide Klumpp
BACKGROUND: Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/27919750/mapping-the-functional-connectome-in-traumatic-brain-injury-what-can-graph-metrics-tell-us
#3
Karen Caeyenberghs, Helena Verhelst, Adam Clemente, Peter H Wilson
OBJECTIVE: Traumatic brain injury (TBI) is associated with cognitive and motor deficits, and poses a significant personal, societal, and economic burden. One mechanism by which TBI is thought to affect cognition and behaviour is through changes in functional connectivity. Graph theory is a powerful framework for quantifying topological features of neuroimaging-derived functional networks. The objective of this paper is to review studies examining functional connectivity in TBI with an emphasis on graph theoretical analysis that is proving to be valuable in uncovering network abnormalities in this condition...
December 2, 2016: NeuroImage
https://www.readbyqxmd.com/read/27917350/completeness-and-regularity-of-generalized-fuzzy-graphs
#4
Sovan Samanta, Biswajit Sarkar, Dongmin Shin, Madhumangal Pal
Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems. Generalized fuzzy graphs are appropriate to avoid such restrictions. In this study generalized fuzzy graphs are introduced. In this study, matrix representation of generalized fuzzy graphs is described. Completeness and regularity are two important parameters of graph theory. Here, regular and complete generalized fuzzy graphs are introduced...
2016: SpringerPlus
https://www.readbyqxmd.com/read/27916383/disentangling-interactions-in-the-microbiome-a-network-perspective
#5
REVIEW
Mehdi Layeghifard, David M Hwang, David S Guttman
Microbiota are now widely recognized as being central players in the health of all organisms and ecosystems, and subsequently have been the subject of intense study. However, analyzing and converting microbiome data into meaningful biological insights remain very challenging. In this review, we highlight recent advances in network theory and their applicability to microbiome research. We discuss emerging graph theoretical concepts and approaches used in other research disciplines and demonstrate how they are well suited for enhancing our understanding of the higher-order interactions that occur within microbiomes...
December 1, 2016: Trends in Microbiology
https://www.readbyqxmd.com/read/27908125/a-h%C3%A3-ckel-source-sink-potential-theory-of-pauli-spin-blockade-in-molecular-electronic-devices
#6
Barry T Pickup, Patrick W Fowler, Irene Sciriha
This paper shows how to include Pauli (exclusion principle) effects within a treatment of ballistic molecular conduction that uses the tight-binding Hückel Hamiltonian and the source-sink-potential (SSP) method. We take into account the many-electron ground-state of the molecule and show that we can discuss ballistic conduction for a specific molecular device in terms of four structural polynomials. In the standard one-electron picture, these are characteristic polynomials of vertex-deleted graphs, with spectral representations in terms of molecular-orbital eigenvectors and eigenvalues...
November 28, 2016: Journal of Chemical Physics
https://www.readbyqxmd.com/read/27896314/graph-theoretic-and-motif-analyses-of-the-hippocampal-neuron-type-potential-connectome
#7
Christopher L Rees, Diek W Wheeler, David J Hamilton, Charise M White, Alexander O Komendantov, Giorgio A Ascoli
We computed the potential connectivity map of all known neuron types in the rodent hippocampal formation by supplementing scantly available synaptic data with spatial distributions of axons and dendrites from the open-access knowledge base Hippocampome.org. The network that results from this endeavor, the broadest and most complete for a mammalian cortical region at the neuron-type level to date, contains more than 3200 connections among 122 neuron types across six subregions. Analyses of these data using graph theory metrics unveil the fundamental architectural principles of the hippocampal circuit...
November 2016: ENeuro
https://www.readbyqxmd.com/read/27893780/identifying-key-drivers-of-return-reversal-with-dynamical-bayesian-factor-graph
#8
Shuai Zhao, Yunhai Tong, Zitian Wang, Shaohua Tan
In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals...
2016: PloS One
https://www.readbyqxmd.com/read/27893770/network-analysis-shows-asymmetrical-flows-within-a-bird-metapopulation
#9
Emilio R Rojas, Cédric Sueur, Pierre-Yves Henry, Blandine Doligez, Gérard Wey, Olivier Dehorter, Sylvie Massemin
How the spatial expansion of a species changes at a human time scale is a process difficult to determine. We studied the dispersal pattern of the French white stork population, using a 21-year ringing/resighting dataset. We used the graph-theory to investigate the strength of links between 5 populations (North-East, North-West, Centre, West, and South) and to determine factors important for the birds' movements. Two clusters of populations were identified within the metapopulation, with most frequent movements of individuals between North-Eastern and Centre populations, and between North-Western and Western populations...
2016: PloS One
https://www.readbyqxmd.com/read/27892508/l%C3%A3-vy-random-walks-on-multiplex-networks
#10
Quantong Guo, Emanuele Cozzo, Zhiming Zheng, Yamir Moreno
Random walks constitute a fundamental mechanism for many dynamics taking place on complex networks. Besides, as a more realistic description of our society, multiplex networks have been receiving a growing interest, as well as the dynamical processes that occur on top of them. Here, inspired by one specific model of random walks that seems to be ubiquitous across many scientific fields, the Lévy flight, we study a new navigation strategy on top of multiplex networks. Capitalizing on spectral graph and stochastic matrix theories, we derive analytical expressions for the mean first passage time and the average time to reach a node on these networks...
November 28, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27891516/functional-region-annotation-of-liver-ct-image-based-on-vascular-tree
#11
Yufei Chen, Xiaodong Yue, Caiming Zhong, Gang Wang
Anatomical analysis of liver region is critical in diagnosis and treatment of liver diseases. The reports of liver region annotation are helpful for doctors to precisely evaluate liver system. One of the challenging issues is to annotate the functional regions of liver through analyzing Computed Tomography (CT) images. In this paper, we propose a vessel-tree-based liver annotation method for CT images. The first step of the proposed annotation method is to extract the liver region including vessels and tumors from the CT scans...
2016: BioMed Research International
https://www.readbyqxmd.com/read/27891195/reflections-on-a-giant-of-brain-science-how-lucky-we-are-having-walter-j-freeman-as-our-beacon-in-cognitive-neurodynamics-research
#12
REVIEW
Robert Kozma
Walter J. Freeman was a giant of the field of neuroscience whose visionary work contributed various experimental and theoretical breakthroughs to brain research in the past 60 years. He has pioneered a number of Electroencephalogram and Electrocorticogram tools and approaches that shaped the field, while "Freeman Neurodynamics" is a theoretical concept that is widely known, used, and respected among neuroscientists all over the world. His recent death is a profound loss to neuroscience and biomedical engineering...
December 2016: Cognitive Neurodynamics
https://www.readbyqxmd.com/read/27891090/disrupted-nodal-and-hub-organization-account-for-brain-network-abnormalities-in-parkinson-s-disease
#13
Yuko Koshimori, Sang-Soo Cho, Marion Criaud, Leigh Christopher, Mark Jacobs, Christine Ghadery, Sarah Coakeley, Madeleine Harris, Romina Mizrahi, Clement Hamani, Anthony E Lang, Sylvain Houle, Antonio P Strafella
The recent application of graph theory to brain networks promises to shed light on complex diseases such as Parkinson's disease (PD). This study aimed to investigate functional changes in sensorimotor and cognitive networks in Parkinsonian patients, with a focus on inter- and intra-connectivity organization in the disease-associated nodal and hub regions using the graph theoretical analyses. Resting-state functional MRI data of a total of 65 participants, including 23 healthy controls (HCs) and 42 patients, were investigated in 120 nodes for local efficiency, betweenness centrality, and degree...
2016: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/27886495/new-integrable-4d-quantum-field-theories-from-strongly-deformed-planar-n-4-supersymmetric-yang-mills-theory
#14
Ömer Gürdoğan, Vladimir Kazakov
We introduce a family of new integrable quantum field theories in four dimensions by considering the γ-deformed N=4 supersymmetric Yang-Mills (SYM) theory in the double scaling limit of large imaginary twists and small coupling. This limit discards the gauge fields and retains only certain Yukawa and scalar interactions with three arbitrary effective couplings. In the 't Hooft limit, these 4D theories are integrable, and contain a wealth of conformal correlators such that the whole arsenal of AdS/CFT integrability remains applicable...
November 11, 2016: Physical Review Letters
https://www.readbyqxmd.com/read/27880802/algebraic-topology-of-multi-brain-connectivity-networks-reveals-dissimilarity-in-functional-patterns-during-spoken-communications
#15
Bosiljka Tadić, Miroslav Andjelković, Biljana Mileva Boshkoska, Zoran Levnajić
Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers...
2016: PloS One
https://www.readbyqxmd.com/read/27876847/a-simplified-computational-memory-model-from-information-processing
#16
Lanhua Zhang, Dongsheng Zhang, Yuqin Deng, Xiaoqian Ding, Yan Wang, Yiyuan Tang, Baoliang Sun
This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular...
November 23, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27875170/towards-unambiguous-edge-bundling-investigating-confluent-drawings-for-network-visualization
#17
Benjamin Bach, Nathalie Henry Riche, Christophe Hurter, Kim Marriott, Tim Dwyer
In this paper, we investigate Confluent Drawings (CD), a technique for bundling edges in node-link diagrams based on network connectivity. Edge-bundling techniques are designed to reduce edge clutter in node-link diagrams by coalescing lines into common paths or bundles. Unfortunately, traditional bundling techniques introduce ambiguity since edges are only bundled by spatial proximity, rather than network connectivity; following an edge from its source to its target can lead to the perception of incorrect connectivity if edges are not clearly separated within the bundles...
January 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/27870559/combinatorial-methods-for-epistasis-and-dominance
#18
Serge Sverdlov, Elizabeth Thompson
We develop computational tools for the analysis of nonlinear genotype-phenotype relationships with epistasis among multiple loci or dominance interactions among multiple alleles within the same locus. Theory distinguishes between separable traits, with removable epistasis, and traits with essential epistasis. Separable traits can be transformed to a natural scale where additive methods apply. The methods we present solve for the natural scale, exactly when possible and approximately when not. Through graph methods, our methods allow for enumeration, counting, or sampling of distinct trait architectures satisfying constraints from the separability theory...
November 21, 2016: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/27870395/sex-differences-in-associations-of-arginine-vasopressin-and-oxytocin-with-resting-state-functional-brain-connectivity
#19
Leah H Rubin, Li Yao, Sarah K Keedy, James L Reilly, Jeffrey R Bishop, C Sue Carter, Hossein Pournajafi-Nazarloo, Lauren L Drogos, Carol A Tamminga, Godfrey D Pearlson, Matcheri S Keshavan, Brett A Clementz, Scot K Hill, Wei Liao, Gong-Jun Ji, Su Lui, John A Sweeney
Oxytocin (OT) and arginine vasopressin (AVP) exert robust and sexually dimorphic influences on cognition and emotion. How these hormones regulate relevant functional brain systems is not well understood. OT and AVP serum concentrations were assayed in 60 healthy individuals (36 women). Brain functional networks assessed with resting-state functional magnetic resonance imaging (rs-fMRI) were constructed with graph theory-based approaches that characterize brain networks as connected nodes. Sex differences were demonstrated in rs-fMRI...
January 2, 2017: Journal of Neuroscience Research
https://www.readbyqxmd.com/read/27865921/community-detection-in-weighted-brain-connectivity-networks-beyond-the-resolution-limit
#20
Carlo Nicolini, Cécile Bordier, Angelo Bifone
Graph theory provides a powerful framework to investigate brain functional connectivity networks and their modular organization. However, most graph-based methods suffer from a fundamental resolution limit that may have affected previous studies and prevented detection of modules, or "communities", that are smaller than a specific scale. Surprise, a resolution-limit-free function rooted in discrete probability theory, has been recently introduced and applied to brain networks, revealing a wide size-distribution of functional modules (Nicolini and Bifone, 2016), in contrast with many previous reports...
November 16, 2016: NeuroImage
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