Literature DB >> 15903508

Efficiency of informational transfer in regular and complex networks.

I Vragović1, E Louis, A Díaz-Guilera.   

Abstract

We analyze the process of informational exchange through complex networks by measuring network efficiencies. Aiming to study nonclustered systems, we propose a modification of this measure on the local level. We apply this method to an extension of the class of small worlds that includes declustered networks and show that they are locally quite efficient, although their clustering coefficient is practically zero. Unweighted systems with small-world and scale-free topologies are shown to be both globally and locally efficient. Our method is also applied to characterize weighted networks. In particular we examine the properties of underground transportation systems of Madrid and Barcelona and reinterpret the results obtained for the Boston subway network.

Year:  2005        PMID: 15903508     DOI: 10.1103/PhysRevE.71.036122

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  14 in total

Review 1.  Cortical high-density counterstream architectures.

Authors:  Kenneth Knoblauch; Zoltán Toroczkai; Henry Kennedy; Nikola T Markov; Mária Ercsey-Ravasz; David C Van Essen
Journal:  Science       Date:  2013-11-01       Impact factor: 47.728

2.  The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles.

Authors:  Răzvan Gămănuţ; Henry Kennedy; Zoltán Toroczkai; Mária Ercsey-Ravasz; David C Van Essen; Kenneth Knoblauch; Andreas Burkhalter
Journal:  Neuron       Date:  2018-02-07       Impact factor: 17.173

3.  EEG-Based Brain Network Analysis of Chronic Stroke Patients After BCI Rehabilitation Training.

Authors:  Gege Zhan; Shugeng Chen; Yanyun Ji; Ying Xu; Zuoting Song; Junkongshuai Wang; Lan Niu; Jianxiong Bin; Xiaoyang Kang; Jie Jia
Journal:  Front Hum Neurosci       Date:  2022-06-27       Impact factor: 3.473

4.  Reorganization of the Brain Structural Covariance Network in Ischemic Moyamoya Disease Revealed by Graph Theoretical Analysis.

Authors:  Peijing Wang; Wenjie Li; Huan Zhu; Xingju Liu; Tao Yu; Dong Zhang; Yan Zhang
Journal:  Front Aging Neurosci       Date:  2022-06-02       Impact factor: 5.702

5.  A predictive network model of cerebral cortical connectivity based on a distance rule.

Authors:  Mária Ercsey-Ravasz; Nikola T Markov; Camille Lamy; David C Van Essen; Kenneth Knoblauch; Zoltán Toroczkai; Henry Kennedy
Journal:  Neuron       Date:  2013-10-02       Impact factor: 17.173

6.  Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

Authors:  István A Kovács; Robin Palotai; Máté S Szalay; Peter Csermely
Journal:  PLoS One       Date:  2010-09-02       Impact factor: 3.240

7.  Evolutionary Analysis of DELLA-Associated Transcriptional Networks.

Authors:  Asier Briones-Moreno; Jorge Hernández-García; Carlos Vargas-Chávez; Francisco J Romero-Campero; José M Romero; Federico Valverde; Miguel A Blázquez
Journal:  Front Plant Sci       Date:  2017-04-25       Impact factor: 5.753

8.  Metabolic and amyloid PET network reorganization in Alzheimer's disease: differential patterns and partial volume effects.

Authors:  Gabriel Gonzalez-Escamilla; Isabelle Miederer; Michel J Grothe; Mathias Schreckenberger; Muthuraman Muthuraman; Sergiu Groppa
Journal:  Brain Imaging Behav       Date:  2021-02       Impact factor: 3.978

9.  Exploring the morphospace of communication efficiency in complex networks.

Authors:  Joaquín Goñi; Andrea Avena-Koenigsberger; Nieves Velez de Mendizabal; Martijn P van den Heuvel; Richard F Betzel; Olaf Sporns
Journal:  PLoS One       Date:  2013-03-07       Impact factor: 3.240

10.  Graph theoretical analysis of complex networks in the brain.

Authors:  Cornelis J Stam; Jaap C Reijneveld
Journal:  Nonlinear Biomed Phys       Date:  2007-07-05
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