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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A decaying factor accounts for contained activity in neuronal networks with no need of hierarchical or modular organization

Texto completo
Amancio, Diego R. [1] ; Oliveira, Jr., Osvaldo N. [1] ; Costa, Luciano da F. [1]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Paulo - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Citações Web of Science: 1

The mechanisms responsible for containing activity in systems represented by networks are crucial in various phenomena, for example, in diseases such as epilepsy that affect the neuronal networks and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided into modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory, through which containment of activity is achieved by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, namely, random, Barabasi-Albert and geographical networks. The generality of this finding was confirmed by showing that modularity is no longer needed if the dynamics based on the integrate-and-fire dynamics incorporated the decay factor. Taken together, these results provide a proof of principle that persistent, restrained network activation might occur in the absence of any particular topological structure. This may be the reason why neuronal activity does not spread out to the entire neuronal network, even when no special topological organization exists. (AU)

Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
Beneficiário:Roberto Marcondes Cesar Junior
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 10/00927-9 - Classificação de textos com redes complexas
Beneficiário:Diego Raphael Amancio
Linha de fomento: Bolsas no Brasil - Doutorado Direto