Development of the deterministic and stochastic Markovian model of a dendritic neuron

• Autorzy: Świetlicka A. , Gugała K. , Pedrycz W. , Rybarczyk A.

Identyfikatory

DOI

10.1016/j.bbe.2016.10.002

• Języki publikacji: EN

Abstrakty

EN

In this study, we propose a model of the dendritic structure of the neuron (referred to as a neural network – NN), which can be viewed as an extension of the models that are currently used in the description of the potential on the neuron's membrane. The proposed extensions augment the generic model and offer a fuller description of the neuron's nature. The common assumption being used in most of the previous models stating a single channel (forming component of the neuron's membrane) can be positioned in only one of the two states (permissive – open and non-permissive – closed), is now relaxed by allowing the channel to be positioned in more states (five or eight states). The relationship between these states is expressed in terms of Markov kinetic schemes. In the paper, we demonstrate that the new approach is more suitable for a larger number of applications than the conventional Hodgkin–Huxley model. The study, by providing the mathematical background of the new extended model, forms a significant step towards a hardware implementation of the biologically realistic neural network (NN) of this type. To reduce the number of components required in such implementation, we propose a new optimization technique that significantly reduces the computational complexity of a single neuron.

Słowa kluczowe

EN

model of dendritic neuron; Hodgkin–Huxley model; Markov kinetic scheme; hardware simplification

PL

neuron dendrytyczny; model Hodgkina-Huxleya; schemat kinetyczny Markova

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2017
• Tom: Vol. 37, no. 1
• Strony: 201--216
• Opis fizyczny: Bibliogr. 36 poz., tab., wykr.

Twórcy

autor

Świetlicka A.

• Poznan University of Technology, Department of Computer Science, ul. Piotrowo 3A, 60-965 Poznań, Poland

autor

Gugała K.

• Poznan University of Technology, Department of Computer Science, ul. Piotrowo 3A, 60-965 Poznań, Poland

autor

Pedrycz W.

• University of Alberta, Department of Electrical and Computer Engineering, Edmonton, Alberta, Canada; Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

autor

Rybarczyk A.

• Poznan University of Technology, Department of Computer Science, ul. Piotrowo 3A, 60-965 Poznań, Poland

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).