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How synapses can enhance sensibility of a neural network

Protachevicz, P.R. ; Borges, F.S. ; Iarosz, K.C. ; Caldas, I.L. ; Baptista, M.S. ; Viana, R.L. ; Lameu, E.L. ; Macau, E.E.N. ; Batista, A.M.

Physica A, 2018-02, Vol.492, p.1045-1052 [Periódico revisado por pares]

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Título:
How synapses can enhance sensibility of a neural network
Autor: Protachevicz, P.R. ; Borges, F.S. ; Iarosz, K.C. ; Caldas, I.L. ; Baptista, M.S. ; Viana, R.L. ; Lameu, E.L. ; Macau, E.E.N. ; Batista, A.M.
Assuntos: Cellular automaton ; Dynamic range ; Plasticity
É parte de: Physica A, 2018-02, Vol.492, p.1045-1052
Descrição: In this work, we study the dynamic range in a neural network modelled by cellular automaton. We consider deterministic and non-deterministic rules to simulate electrical and chemical synapses. Chemical synapses have an intrinsic time-delay and are susceptible to parameter variations guided by learning Hebbian rules of behaviour. The learning rules are related to neuroplasticity that describes change to the neural connections in the brain. Our results show that chemical synapses can abruptly enhance sensibility of the neural network, a manifestation that can become even more predominant if learning rules of evolution are applied to the chemical synapses. •We have been studying the dynamic range in a neuronal network modelled by cellular automaton.•An enhancement of the dynamic range happens mediated by a phase transition in its value due to a hysteretic behaviour.•We observe that chemical synapses can abruptly enhance sensibility of the neural network.
Editor: Elsevier B.V
Idioma: Inglês

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