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Graph Theory

Thomas Barthel, Caterina De Bacco, Silvio Franz
We introduce and apply an efficient method for the precise simulation of stochastic dynamical processes on locally treelike graphs. Networks with cycles are treated in the framework of the cavity method. Such models correspond, for example, to spin-glass systems, Boolean networks, neural networks, or other technological, biological, and social networks. Building upon ideas from quantum many-body theory, our approach is based on a matrix product approximation of the so-called edge messages-conditional probabilities of vertex variable trajectories...
January 2018: Physical Review. E
Fabrizio Vecchio, Riccardo Di Iorio, Francesca Miraglia, Giuseppe Granata, Roberto Romanello, Placido Bramanti, Paolo Maria Rossini
Transcranial direct current stimulation (tDCS) is a non-invasive technique able to modulate cortical excitability in a polarity-dependent way. At present, only few studies investigated the effects of tDCS on the modulation of functional connectivity between remote cortical areas. The aim of this study was to investigate-through graph theory analysis-how bipolar tDCS modulate cortical networks high-density EEG recordings were acquired before and after bipolar cathodal, anodal and sham tDCS involving the primary motor and pre-motor cortices of the dominant hemispherein 14 healthy subjects...
February 13, 2018: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
D M Mateos, R Guevara Erra, R Wennberg, J L Perez Velazquez
Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied sensorimotor information. Thus, these frameworks are very useful in attempts to quantify cognitive states. We set out to analyze different types of signals obtained from scalp electroencephalography (EEG), intracranial EEG and magnetoencephalography recording in subjects during different states of consciousness: resting wakefulness, different sleep stages and epileptic seizures...
February 2018: Cognitive Neurodynamics
Yan Zhu, Dongqing Wang, Zhe Liu, Yuefeng Li
BACKGROUND: Neuroimaging studies have shown that major depressive disorder is associated with altered activity patterns of the default-mode network (DMN). In this study, we sought to investigate the topological organization of the DMN in patients with remitted geriatric depression (RGD) and whether RGD patients would be more likely to show disrupted topological configuration of the DMN during the resting-state. METHODS: Thirty-three RGD patients and thirty-one healthy control participants underwent clinical and cognitive evaluations as well as resting-state functional magnetic resonance imaging scans...
February 12, 2018: International Psychogeriatrics
Jason Z Kim, Jonathan M Soffer, Ari E Kahn, Jean M Vettel, Fabio Pasqualetti, Danielle S Bassett
Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems...
2018: Nature Physics
Guillaume Bastille-Rousseau, Iain Douglas-Hamilton, Stephen Blake, Joseph M Northrup, George Wittemyer
Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects, particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges...
February 8, 2018: Ecological Applications: a Publication of the Ecological Society of America
Federico Chiariotti, Chiara Pielli, Andrea Zanella, Michele Zorzi
Bike-sharing services are flourishing in Smart Cities worldwide. They provide a low-cost and environment-friendly transportation alternative and help reduce traffic congestion. However, these new services are still under development, and several challenges need to be solved. A major problem is the management of rebalancing trucks in order to ensure that bikes and stalls in the docking stations are always available when needed, despite the fluctuations in the service demand. In this work, we propose a dynamic rebalancing strategy that exploits historical data to predict the network conditions and promptly act in case of necessity...
February 8, 2018: Sensors
Pencho Yordanov, Jörg Stelling
In pharmacology and systems biology, it is a fundamental problem to determine how biological systems change their dose-response behavior upon perturbations. In particular, it is unclear how topologies, reactions, and parameters (differentially) affect the dose response. Because parameters are often unknown, systematic approaches should directly relate network structure and function. Here, we outline a procedure to compare general non-monotone dose-response curves and subsequently develop a comprehensive theory for differential dose responses of biochemical networks captured by non-equilibrium steady-state linear framework models...
February 6, 2018: Biophysical Journal
María Ramos Vázquez, Vibhav Bharadwaj, Belén Sotillo, Shu-Zee A Lo, Roberta Ramponi, Nikolay I Zheludev, Guglielmo Lanzani, Shane M Eaton, Cesare Soci
Cognitive photonic networks are researched to efficiently solve computationally hard problems. Flexible fabrication techniques for the implementation of such networks into compact and scalable chips are desirable for the study of new optical computing schemes and algorithm optimization. Here we demonstrate a femtosecond laser-written optical oracle based on cascaded directional couplers in glass, for the solution of the Hamiltonian path problem. By interrogating the integrated photonic chip with ultrashort laser pulses, we were able to distinguish the different paths traveled by light pulses, and thus infer the existence or the absence of the Hamiltonian path in the network by using an optical correlator...
January 22, 2018: Optics Express
Jun-Ho Choi, Hochan Lee, Hyung Ran Choi, Minhaeng Cho
In molecular and cellular biology, dissolved ions and molecules have decisive effects on chemical and biological reactions, conformational stabilities, and functions of small to large biomolecules. Despite major efforts, the current state of understanding of the effects of specific ions, osmolytes, and bioprotecting sugars on the structure and dynamics of water H-bonding networks and proteins is not yet satisfactory. Recently, to gain deeper insight into this subject, we studied various aggregation processes of ions and molecules in high-concentration salt, osmolyte, and sugar solutions with time-resolved vibrational spectroscopy and molecular dynamics simulation methods...
January 31, 2018: Annual Review of Physical Chemistry
Xiaomei Zou, Jing Yang, Jianpei Zhang
Analyzing massive user-generated microblogs is very crucial in many fields, attracting many researchers to study. However, it is very challenging to process such noisy and short microblogs. Most prior works only use texts to identify sentiment polarity and assume that microblogs are independent and identically distributed, which ignore microblogs are networked data. Therefore, their performance is not usually satisfactory. Inspired by two sociological theories (sentimental consistency and emotional contagion), in this paper, we propose a new method combining social context and topic context to analyze microblog sentiment...
2018: PloS One
Olaf F A Larsen, Eric Claassen
Although numerous reports link a decreased diversity of the gut microbiota to a declined health status, to date no mechanistic motivation for this exists. Here, we show by applying first principles basic graph theory on small networks that higher diversity within such a network indeed leads to more efficient systems and redundancy. Our results quantitatively support earlier hypothetical considerations on gut microbiota richness with respect to these parameters. Our simulations show that higher species diversity leads to higher resilience within small microbiological ecosystems, like being present in the gut microbiota...
February 1, 2018: Scientific Reports
Zhonglin Li, Rui Chen, Min Guan, Enfeng Wang, Tianyi Qian, Cuihua Zhao, Zhi Zou, Thomas Beck, Dapeng Shi, Meiyun Wang, Hongju Zhang, Yongli Li
This study investigated the topological characteristics of brain functional networks in chronic insomnia disorder (CID) patients. The resting-state functional magnetic resonance imaging and graph theory analysis method were applied to investigate the brain functional connectome patterns among 45 CID patients and 32 healthy controls. The brain functional connectome was constructed by thresholding partial correlation matrices of 90 brain regions from an automated anatomical labeling atlas. The topologic properties of brain functional connectomes at both global and nodal levels were tested...
2018: NeuroImage: Clinical
Milovan Šuvakov, Miroslav Andjelković, Bosiljka Tadić
Multilevel self-assembly involving small structured groups of nano-particles provides new routes to development of functional materials with a sophisticated architecture. Apart from the inter-particle forces, the geometrical shapes and compatibility of the building blocks are decisive factors. Therefore, a comprehensive understanding of these processes is essential for the design of assemblies of desired properties. Here, we introduce a computational model for cooperative self-assembly with the simultaneous attachment of structured groups of particles, which can be described by simplexes (connected pairs, triangles, tetrahedrons and higher order cliques) to a growing network...
January 31, 2018: Scientific Reports
Dimitrios A Adamos, Nikolaos Laskaris, Sifis Micheloyannis
<i>Objective</i>. Music, being a multifaceted stimulus evolving at multiple timescales, modulates brain function in a manifold way that encompasses not only the distinct stages of auditory perception, but also higher cognitive processes like memory and appraisal. Network theory is apparently a promising approach to describe the functional reorganization of brain oscillatory dynamics during music listening. However, the music induced changes have so far been examined within the functional boundaries of isolated brain rhythms...
February 1, 2018: Journal of Neural Engineering
A Sreeja, U Krishnakumar, K P Vinayan
Interaction of multiple genetic variants is a major challenge in the development of effective treatment strategies for complex disorders. Identifying the most promising genes enhances the understanding of the underlying mechanisms of the disease, which, in turn leads to better diagnostic and therapeutic predictions. Categorizing the disease genes into meaningful groups even helps in analyzing the correlated phenotypes which will further improve the power of detecting disease-associated variants. Since experimental approaches are time consuming and expensive, computational methods offer an accurate and efficient alternative for analyzing gene-disease associations from vast amount of publicly available genomic information...
January 30, 2018: Interdisciplinary Sciences, Computational Life Sciences
Thomas Forkmann, Tobias Teismann, Jana-Sophie Stenzel, Heide Glaesmer, Derek de Beurs
BACKGROUND: Defeat and entrapment have been shown to be of central relevance to the development of different disorders. However, it remains unclear whether they represent two distinct constructs or one overall latent variable. One reason for the unclarity is that traditional factor analytic techniques have trouble estimating the right number of clusters in highly correlated data. In this study, we applied a novel approach based on network analysis that can deal with correlated data to establish whether defeat and entrapment are best thought of as one or multiple constructs...
January 25, 2018: BMC Medical Research Methodology
Angela M Muller, Naznin Virji-Babul
Sports-related concussion in youth is a major public health issue. Evaluating the diffuse and often subtle changes in structure and function that occur in the brain, particularly in this population, remains a significant challenge. The goal of this pilot study was to evaluate the relationship between the intrinsic dynamics of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) and relate these findings to structural brain correlates from diffusion tensor imaging in a group of adolescents with sports-related concussions ( n = 6) and a group of healthy adolescent athletes ( n = 6)...
January 2018: ASN Neuro
Jeong-Hyeon Shin, Yu Hyun Um, Chang Uk Lee, Hyun Kook Lim, Joon-Kyung Seong
BACKGROUND: Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. METHODS: In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients...
January 5, 2018: Journal of Affective Disorders
Frigyes Samuel Racz, Peter Mukli, Zoltan Nagy, Andras Eke
Brain function is organized as a network of functional connections between different neuronal populations with connection strengths dynamically changing in time and space. Studies investigating functional connectivity (FC) usually follow a static approach when describing FC by considering the connectivity strengths constant, however a dynamic approach seems more reasonable, as this way the spatio-temporal dynamics of the underlying system can also be captured. Objective: The scale-free, i.e. fractal nature of neural dynamics is an inherent property of the nervous system...
January 19, 2018: Physiological Measurement
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