@Article{BorgesBLPICVMBGB:2017:SyPlSp,
author = "Borges, Rafael R. and Borges, Fernando da Silva and Lameu,
Ewandson I. and Protachevicz, Paulo R. and Iarosz, Kelly C. and
Caldas, Ibere L. and Viana, Ricardo L. and Macau, Elbert Einstein
Nehrer and Baptista, Murilo S. and Grebogi, Celso and Batista,
Antonio M.",
affiliation = "{Universidade Tecnol{\'o}gica Federal do Paran{\'a} (UTFPR)} and
{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Universidade Federal de Ponta
Grossa} and {Universidade de S{\~a}o Paulo (USP)} and
{Universidade de S{\~a}o Paulo (USP)} and {Universidade Federal
do Paran{\'a} (UFPR)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {University of Aberdeen} and {University of
Aberdeen} and {Universidade de S{\~a}o Paulo (USP)}",
title = "Synaptic plasticity and spike synchronisation in neuronal
networks",
journal = "Brazilian Journal of Physics",
year = "2017",
volume = "47",
pages = "678--688",
keywords = "Neuronal network, Plasticity, Synchronisation.",
abstract = "Brain plasticity, also known as neuroplasticity, is a fundamental
mechanism of neuronal adaptation in response to changes in the
environment or due to brain injury. In this review, we show our
results about the effects of synaptic plasticity on neuronal
networks composed by Hodgkin-Huxley neurons. We show that the
final topology of the evolved network depends crucially on the
ratio between the strengths of the inhibitory and excitatory
synapses. Excitation of the same order of inhibition revels an
evolved network that presents the rich-club phenomenon, well known
to exist in the brain. For initial networks with considerably
larger inhibitory strengths, we observe the emergence of a complex
evolved topology, where neurons sparsely connected to other
neurons, also a typical topology of the brain. The presence of
noise enhances the strength of both types of synapses, but if the
initial network has synapses of both natures with similar
strengths. Finally, we show how the synchronous behaviour of the
evolved network will reflect its evolved topology.",
doi = "10.1007/s13538-017-0529-5",
url = "http://dx.doi.org/10.1007/s13538-017-0529-5",
issn = "0103-9733",
language = "en",
targetfile = "borges_synaptic.pdf",
urlaccessdate = "27 abr. 2024"
}