Artículo
A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks
Fecha de publicación:
02/2012
Editorial:
National Academy of Sciences
Revista:
Proceedings of the National Academy of Sciences of The United States of America
ISSN:
0027-8424
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.
Palabras clave:
No
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Articulos(IFIBA)
Articulos de INST.DE FISICA DE BUENOS AIRES
Articulos de INST.DE FISICA DE BUENOS AIRES
Citación
Gallos, Lazaros K.; Makse, Hernán Alejandro; Sigman, Mariano; A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks; National Academy of Sciences; Proceedings of the National Academy of Sciences of The United States of America; 109; 8; 2-2012; 2825-2830
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