A Study of Nonlinear Characteristics in a Hardware Active Dendrite Model

Zongyang XUE; Haruki NAGAMI; Kazutaka SOMEYA; Katsutoshi SAEKI; Yoshifumi SEKINE

A Study of Nonlinear Characteristics in a Hardware Active Dendrite Model

Zongyang XUE, Haruki NAGAMI, Kazutaka SOMEYA, Katsutoshi SAEKI, Yoshifumi SEKINE

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Brain subsystems have a high degree of information processing ability using nonlinear dynamics and although various neuron models and artificial neural networks have been investigated, the information processing functions of biological neural networks have not yet been clarified. Recently, various research efforts have confirmed that dendrites perform an important role in brain information processing. In this paper, we discuss the nonlinear characteristics of a hardware active dendrite model, in order to clarify information encoding and transmission via action potentials. That is to say, we show that our proposed model can reproduce the nonlinear characteristics of a biologically active dendrite. First, the hardware active dendrite model we propose is described. We next discuss the response characteristics for pulse stimuli using the model. As a result, when input pulses are applied to an active line, which is the basic structure of the dendrite model, it is shown clearly that backpropagation characteristics are acquired and that the characteristics are qualitatively in agreement with the characteristics of biological dendrites. Furthermore, we verify that the ratio of input to output frequency at the cell body is influenced by the backpropagation characteristics with two branches, which is the simplest structure in the active dendrite model. Thus, with backpropagation characteristics, the possibility that the model can carry out clearly the information processing of biological neural networks, is suggested.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.9 pp.2287-2293

Publication Date: 2003/09/01

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Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)

Category: Neuro, Fuzzy, GA

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Zongyang XUE, Haruki NAGAMI, Kazutaka SOMEYA, Katsutoshi SAEKI, Yoshifumi SEKINE, "A Study of Nonlinear Characteristics in a Hardware Active Dendrite Model" in IEICE TRANSACTIONS on Fundamentals, vol. E86-A, no. 9, pp. 2287-2293, September 2003, doi: .
Abstract: Brain subsystems have a high degree of information processing ability using nonlinear dynamics and although various neuron models and artificial neural networks have been investigated, the information processing functions of biological neural networks have not yet been clarified. Recently, various research efforts have confirmed that dendrites perform an important role in brain information processing. In this paper, we discuss the nonlinear characteristics of a hardware active dendrite model, in order to clarify information encoding and transmission via action potentials. That is to say, we show that our proposed model can reproduce the nonlinear characteristics of a biologically active dendrite. First, the hardware active dendrite model we propose is described. We next discuss the response characteristics for pulse stimuli using the model. As a result, when input pulses are applied to an active line, which is the basic structure of the dendrite model, it is shown clearly that backpropagation characteristics are acquired and that the characteristics are qualitatively in agreement with the characteristics of biological dendrites. Furthermore, we verify that the ratio of input to output frequency at the cell body is influenced by the backpropagation characteristics with two branches, which is the simplest structure in the active dendrite model. Thus, with backpropagation characteristics, the possibility that the model can carry out clearly the information processing of biological neural networks, is suggested.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e86-a_9_2287/_p

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@ARTICLE{e86-a_9_2287,
author={Zongyang XUE, Haruki NAGAMI, Kazutaka SOMEYA, Katsutoshi SAEKI, Yoshifumi SEKINE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Study of Nonlinear Characteristics in a Hardware Active Dendrite Model},
year={2003},
volume={E86-A},
number={9},
pages={2287-2293},
abstract={Brain subsystems have a high degree of information processing ability using nonlinear dynamics and although various neuron models and artificial neural networks have been investigated, the information processing functions of biological neural networks have not yet been clarified. Recently, various research efforts have confirmed that dendrites perform an important role in brain information processing. In this paper, we discuss the nonlinear characteristics of a hardware active dendrite model, in order to clarify information encoding and transmission via action potentials. That is to say, we show that our proposed model can reproduce the nonlinear characteristics of a biologically active dendrite. First, the hardware active dendrite model we propose is described. We next discuss the response characteristics for pulse stimuli using the model. As a result, when input pulses are applied to an active line, which is the basic structure of the dendrite model, it is shown clearly that backpropagation characteristics are acquired and that the characteristics are qualitatively in agreement with the characteristics of biological dendrites. Furthermore, we verify that the ratio of input to output frequency at the cell body is influenced by the backpropagation characteristics with two branches, which is the simplest structure in the active dendrite model. Thus, with backpropagation characteristics, the possibility that the model can carry out clearly the information processing of biological neural networks, is suggested.},
keywords={},
doi={},
ISSN={},
month={September},}

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TY - JOUR
TI - A Study of Nonlinear Characteristics in a Hardware Active Dendrite Model
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2287
EP - 2293
AU - Zongyang XUE
AU - Haruki NAGAMI
AU - Kazutaka SOMEYA
AU - Katsutoshi SAEKI
AU - Yoshifumi SEKINE
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2003
AB - Brain subsystems have a high degree of information processing ability using nonlinear dynamics and although various neuron models and artificial neural networks have been investigated, the information processing functions of biological neural networks have not yet been clarified. Recently, various research efforts have confirmed that dendrites perform an important role in brain information processing. In this paper, we discuss the nonlinear characteristics of a hardware active dendrite model, in order to clarify information encoding and transmission via action potentials. That is to say, we show that our proposed model can reproduce the nonlinear characteristics of a biologically active dendrite. First, the hardware active dendrite model we propose is described. We next discuss the response characteristics for pulse stimuli using the model. As a result, when input pulses are applied to an active line, which is the basic structure of the dendrite model, it is shown clearly that backpropagation characteristics are acquired and that the characteristics are qualitatively in agreement with the characteristics of biological dendrites. Furthermore, we verify that the ratio of input to output frequency at the cell body is influenced by the backpropagation characteristics with two branches, which is the simplest structure in the active dendrite model. Thus, with backpropagation characteristics, the possibility that the model can carry out clearly the information processing of biological neural networks, is suggested.
ER -