Dobrushin Mean-Field Approach for Queueing Large-Scale Networks with a Small Parameter

2017 ◽  
pp. 395-405
Author(s):  
Galina O. Tsareva ◽  
Sergey A. Vasilyev
Keyword(s):  
Small Parameter ◽  
Large Scale ◽  
Mean Field ◽  
Field Approach ◽  
Large Scale Networks

Optimal attack and defence of large scale networks using mean field theory

2016 ◽  
Author(s):  
Jorge del Val ◽  
Santiago Zazo ◽  
Sergio Valcarcel Macua ◽  
Javier Zazo ◽  
Juan Parras
Keyword(s):  
Field Theory ◽  
Large Scale ◽  
Mean Field Theory ◽  
Mean Field ◽  
Large Scale Networks

A Master Equation Formalism for Macroscopic Modeling of Asynchronous Irregular Activity States

2009 ◽  
Vol 21 (1) ◽  
pp. 46-100 ◽  
Author(s):  
Sami El Boustani ◽  
Alain Destexhe
Keyword(s):  
Master Equation ◽  
Large Scale ◽  
Mean Field ◽  
Finite Size ◽  
External Input ◽  
Complex Activity ◽  
Macroscopic Modeling ◽  
Large Scale Networks ◽  
Sparse Connectivity ◽  
Balanced Networks

Many efforts have been devoted to modeling asynchronous irregular (AI) activity states, which resemble the complex activity states seen in the cerebral cortex of awake animals. Most of models have considered balanced networks of excitatory and inhibitory spiking neurons in which AI states are sustained through recurrent sparse connectivity, with or without external input. In this letter we propose a mesoscopic description of such AI states. Using master equation formalism, we derive a second-order mean-field set of ordinary differential equations describing the temporal evolution of randomly connected balanced networks. This formalism takes into account finite size effects and is applicable to any neuron model as long as its transfer function can be characterized. We compare the predictions of this approach with numerical simulations for different network configurations and parameter spaces. Considering the randomly connected network as a unit, this approach could be used to build large-scale networks of such connected units, with an aim to model activity states constrained by macroscopic measurements, such as voltage-sensitive dye imaging.

scholarly journals Contribution of Ionotropic Glutamatergic Receptors to Excitability and Attentional Signals in Macaque Frontal Eye Field

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele
Keyword(s):  
Attentional Control ◽  
Large Scale ◽  
Neuronal Excitability ◽  
Cell Types ◽  
Receptor Activation ◽  
Frontal Eye Field ◽  
Control Signals ◽  
Cognitive Operations ◽  
Eye Field ◽  
Large Scale Networks

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.

scholarly journals Inhomogeneous mean-field approach to collective excitations near the superfluid-Mott glass transition

2021 ◽  
pp. 168526
Author(s):  
Martin Puschmann ◽  
João C. Getelina ◽  
José A. Hoyos ◽  
Thomas Vojta
Keyword(s):  
Glass Transition ◽  
Mean Field ◽  
Collective Excitations ◽  
Field Approach

scholarly journals Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling

2015 ◽  
Author(s):  
Michael Mitzenmacher ◽  
Jakub Pachocki ◽  
Richard Peng ◽  
Charalampos Tsourakakis ◽  
Shen Chen Xu
Keyword(s):  
Large Scale ◽  
Large Scale Networks

scholarly journals How does the position of firms in the supply chain affect their performance? An empirical study

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Individual Performance ◽  
Supply Network ◽  
Supply Chain Networks ◽  
Focal Firm ◽  
Cooperative Competition ◽  
Large Scale Networks ◽  
The Relationship

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.

A rigorous multiscale random field approach to generate large scale rough rock surfaces

2021 ◽  
Vol 142 ◽  
pp. 104716
Author(s):  
M. Jeffery ◽  
J. Huang ◽  
S. Fityus ◽  
A. Giacomini ◽  
O. Buzzi
Keyword(s):  
Random Field ◽  
Large Scale ◽  
Field Approach
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