Full text
| |
| Author(s): |
César Henrique Comin
Total Authors: 1
|
| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Física de São Carlos (IFSC/BT) |
| Defense date: | 2016-04-26 |
| Examining board members: |
Luciano da Fontoura Costa;
Roberto de Alencar Lotufo;
David Corrêa Martins Junior;
Orides Morandin Junior;
Carlos Antonio Ruggiero
|
| Advisor: | Luciano da Fontoura Costa |
| Abstract | |
There has been a growing interest in modeling diverse types of real-world systems through the tools provided by complex network theory. One of the main topics of research in this area is related to the identification and characterization of groups, or communities, of nodes more densely connected between themselves than with the rest of the network. We show that communities can be characterized by four general classes of features, associated with the internal topology, internal dynamics, topological border, and dynamical border of the communities. We verify that these characteristics have direct influence on the dynamics taking place over the network. Particularly, for each considered class we study the interdependence between the topology and the dynamics associated with each network community. We show that some of the studied properties can influence the topology-dynamics interdependence, inducing what we call the communities specific behavior. In order to present and characterize this concept on the four considered classes, we study the following combinations of network topology and dynamics. We first investigate traditional random walks taking place on a directed network. We demonstrate that, for this dynamics, the direction of the edges between communities represents the main method for the modification of the topology-dynamics relationship. We apply the developed approach on a real-world network, defined by the connectivity between cortical regions in primates of the Macaca genus. The second studied case considers the biased random walk on undirected networks. We demonstrate that the transition bias of this dynamics becomes more relevant for higher network modularity. In addition, we show that the biased random walk can be used to model with good accuracy the passenger flow inside the communities of two airport networks. The third analysis is done on a neuronal dynamics, called integrate-and-fire, applied to networks composed of communities generated by the Watts-Strogatz model. We show that the considered communities can not only posses distinct dynamical activation levels, but also yield different signal regularity. Lastly, we study the influence of the positions of inhibitory connections on the integrate-and-fire dynamics. We show that inhibitory connections placed between communities can have a non-trivial influence on the global behavior of the dynamics. The current study reveals the importance of considering parameter variations of network models at the scale of communities. (AU) | |
| FAPESP's process: | 11/22639-8 - Unveiling the relationship between structure and dynamics on modular networks |
| Grantee: | Cesar Henrique Comin |
| Support Opportunities: | Scholarships in Brazil - Doctorate |