Hirofumi Nagashino - Profile on Academia.edu (original) (raw)
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Papers by Hirofumi Nagashino
System Identification of the Brain Dynamics by EEG Analysis Using Neural Networks
Lecture Notes in Computer Science, 2003
ABSTRACT
Periodic activities in a reciprocal inhibition network consisting of a large number of neurons
Neuroscience Letters
Identification of biological signal sources for circadian and cardiac cycle rhythms using BP neural networks
Kybernetes
ABSTRACT
Synchronization with a periodic pulse train in an asymmetrically coupled neuronal network model
Neurocomputing
ABSTRACT
Oscillatory modes in a neuronal network model with transmission latency
Neurocomputing
ABSTRACT
We analyzed the characteristics of periodic solutions in a theoretical model of two symmetrically... more We analyzed the characteristics of periodic solutions in a theoretical model of two symmetrically coupled neural oscillators which are nonidentical in that a coupling coefficient between the units inside an oscillaor is different from the corresponding one in the other oscillator. The present paper shows this model has different qualitative oscillatory properties from the case where two identical oscillators are coupled with different coupling coefficients to each other.
Phase transitions in oscillatory neural networks
Proceedings of SPIE - The International Society for Optical Engineering
ABSTRACT
Magnetic motion measurement using BPNN
IFMBE Proceedings, 2007
ABSTRACT
Extracting characteristic feature of a inert region from EEG
ABSTRACT
A computational framework with simplified tonotopicity and homeostatic plasticity for tinnitus generation and its management by sound therapy
WSEAS Transactions on Biology and Biomedicine
ABSTRACT
Magnetic motion measurement using BPNN
IFMBE proceedings
ABSTRACT
Detection of biological system deviation by BPNN
ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004., 2004
ABSTRACT
A neuronal network model with homeostatic plasticity for tinnitus generation and its management by sound therapy
2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 2012
ABSTRACT Tinnitus is the perception that one hears phantom sound(s) in the ears or in the head wi... more ABSTRACT Tinnitus is the perception that one hears phantom sound(s) in the ears or in the head without any external source. Sound therapy is one of the most effective techniques for tinnitus treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy, we previously proposed computational and dynamical models with Hebbian or spike-time-dependent plasticity using a neural oscillator or a neuronal network. In the present paper, we propose a neuronal network model with homeostatic plasticity and demonstrate the simulation results of the model. The model is able to replicate the process of tinnitus generation and inhibition of perception of tinnitus by sound therapy.
Analysis of Multi-Layer Neural Network’s Recognition Mechanism Using Alopex Algorithm
IFMBE Proceedings, 2007
ABSTRACT
Extracting characteristic feature of a inert region from EEG
IFMBE Proceedings, 2007
ABSTRACT
Tinnitus is the perception of phantom sounds in the ears or in the head. Accordingly sound therap... more Tinnitus is the perception of phantom sounds in the ears or in the head. Accordingly sound therapy for tinnitus has been used. To account for mechanisms of tinnitus generation and the clinical effects of sound therapies from the viewpoint of neural engineering, we have proposed a plastic neural network model for the human auditory system. We found that this model has a bistable state, i.e., a stable oscillatory state and a stable equilibrium (non-oscillatory) state coexist at a certain parameter region. This paper describes inhibition of the oscillation for various kinds of noise stimuli, because noise stimuli are presented to tinnitus sufferers for therapeutic purposes. Through several numerical simulations it was shown that noise stimulus can inhibit the oscillation (similar to residual inhibition as seen in clinical studies), however, the oscillation is not inhibited in all cases, i.e., the effect of inhibition is not pervasive as in the case of inhibition in clinical cases.
Inhibition of oscillation in a neuronal network model for tinnitus management by sound therapy
ABSTRACT An abstract is not available.
International Journal of Mathematical Models and Methods in Applied Sciences
Tinnitus is a perception of sound in the ears or in the head without external source. There are m... more Tinnitus is a perception of sound in the ears or in the head without external source. There are many therapeutic approaches for tinnitus. Sound therapy is one of the effective techniques for its treatment. We have proposed computational models with plasticity by Hebbian hypothesis using a neural oscillator or coupled model neurons described by simplified Hodgkin-Huxley equations in order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy from the neural engineering point of view. In the present paper, a neuronal network model with synaptic plasticity by STDP (spike-timing-dependent plasticity) hypothesis is proposed for replication of the clinical results that human auditory system temporarily halts perception of tinnitus following sound therapy.
Entrainment of a Reciprocal Inhibition Neural Network Model to a Periodic Pulse Train
Computational Neuroscience, 1998
System Identification of the Brain Dynamics by EEG Analysis Using Neural Networks
Lecture Notes in Computer Science, 2003
ABSTRACT
Periodic activities in a reciprocal inhibition network consisting of a large number of neurons
Neuroscience Letters
Identification of biological signal sources for circadian and cardiac cycle rhythms using BP neural networks
Kybernetes
ABSTRACT
Synchronization with a periodic pulse train in an asymmetrically coupled neuronal network model
Neurocomputing
ABSTRACT
Oscillatory modes in a neuronal network model with transmission latency
Neurocomputing
ABSTRACT
We analyzed the characteristics of periodic solutions in a theoretical model of two symmetrically... more We analyzed the characteristics of periodic solutions in a theoretical model of two symmetrically coupled neural oscillators which are nonidentical in that a coupling coefficient between the units inside an oscillaor is different from the corresponding one in the other oscillator. The present paper shows this model has different qualitative oscillatory properties from the case where two identical oscillators are coupled with different coupling coefficients to each other.
Phase transitions in oscillatory neural networks
Proceedings of SPIE - The International Society for Optical Engineering
ABSTRACT
Magnetic motion measurement using BPNN
IFMBE Proceedings, 2007
ABSTRACT
Extracting characteristic feature of a inert region from EEG
ABSTRACT
A computational framework with simplified tonotopicity and homeostatic plasticity for tinnitus generation and its management by sound therapy
WSEAS Transactions on Biology and Biomedicine
ABSTRACT
Magnetic motion measurement using BPNN
IFMBE proceedings
ABSTRACT
Detection of biological system deviation by BPNN
ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004., 2004
ABSTRACT
A neuronal network model with homeostatic plasticity for tinnitus generation and its management by sound therapy
2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 2012
ABSTRACT Tinnitus is the perception that one hears phantom sound(s) in the ears or in the head wi... more ABSTRACT Tinnitus is the perception that one hears phantom sound(s) in the ears or in the head without any external source. Sound therapy is one of the most effective techniques for tinnitus treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy, we previously proposed computational and dynamical models with Hebbian or spike-time-dependent plasticity using a neural oscillator or a neuronal network. In the present paper, we propose a neuronal network model with homeostatic plasticity and demonstrate the simulation results of the model. The model is able to replicate the process of tinnitus generation and inhibition of perception of tinnitus by sound therapy.
Analysis of Multi-Layer Neural Network’s Recognition Mechanism Using Alopex Algorithm
IFMBE Proceedings, 2007
ABSTRACT
Extracting characteristic feature of a inert region from EEG
IFMBE Proceedings, 2007
ABSTRACT
Tinnitus is the perception of phantom sounds in the ears or in the head. Accordingly sound therap... more Tinnitus is the perception of phantom sounds in the ears or in the head. Accordingly sound therapy for tinnitus has been used. To account for mechanisms of tinnitus generation and the clinical effects of sound therapies from the viewpoint of neural engineering, we have proposed a plastic neural network model for the human auditory system. We found that this model has a bistable state, i.e., a stable oscillatory state and a stable equilibrium (non-oscillatory) state coexist at a certain parameter region. This paper describes inhibition of the oscillation for various kinds of noise stimuli, because noise stimuli are presented to tinnitus sufferers for therapeutic purposes. Through several numerical simulations it was shown that noise stimulus can inhibit the oscillation (similar to residual inhibition as seen in clinical studies), however, the oscillation is not inhibited in all cases, i.e., the effect of inhibition is not pervasive as in the case of inhibition in clinical cases.
Inhibition of oscillation in a neuronal network model for tinnitus management by sound therapy
ABSTRACT An abstract is not available.
International Journal of Mathematical Models and Methods in Applied Sciences
Tinnitus is a perception of sound in the ears or in the head without external source. There are m... more Tinnitus is a perception of sound in the ears or in the head without external source. There are many therapeutic approaches for tinnitus. Sound therapy is one of the effective techniques for its treatment. We have proposed computational models with plasticity by Hebbian hypothesis using a neural oscillator or coupled model neurons described by simplified Hodgkin-Huxley equations in order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy from the neural engineering point of view. In the present paper, a neuronal network model with synaptic plasticity by STDP (spike-timing-dependent plasticity) hypothesis is proposed for replication of the clinical results that human auditory system temporarily halts perception of tinnitus following sound therapy.
Entrainment of a Reciprocal Inhibition Neural Network Model to a Periodic Pulse Train
Computational Neuroscience, 1998