Search Results - "Nobukawa, Sou"

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  1. 1

    Changes in functional connectivity dynamics with aging: A dynamical phase synchronization approach by Nobukawa, Sou, Kikuchi, Mitsuru, Takahashi, Tetsuya

    Published in NeuroImage (Orlando, Fla.) (01-03-2019)
    “…The dynamics of the human brain network has attracted broad attention, in recognition of the concept that functional connectivity is not static, but changes…”
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  2. 2

    Long-Tailed Characteristics of Neural Activity Induced by Structural Network Properties by Nobukawa, Sou

    “…Over the past few decades, neuroscience studies have elucidated the structural/anatomical network characteristics in the brain and their associations with…”
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  3. 3

    A microcircuit model involving parvalbumin, somatostatin, and vasoactive intestinal polypeptide inhibitory interneurons for the modulation of neuronal oscillation during visual processing by Wagatsuma, Nobuhiko, Nobukawa, Sou, Fukai, Tomoki

    Published in Cerebral cortex (New York, N.Y. 1991) (04-04-2023)
    “…Abstract Various subtypes of inhibitory interneurons contact one another to organize cortical networks. Most cortical inhibitory interneurons express 1 of 3…”
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  4. 4

    Controlling Chaotic Resonance using External Feedback Signals in Neural Systems by Nobukawa, Sou, Shibata, Natsusaku

    Published in Scientific reports (21-03-2019)
    “…Stochastic resonance is a phenomenon in which the signal response of a non-linear system is enhanced by appropriate external noise. Likewise, a similar…”
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  5. 5

    Atypical instantaneous spatio-temporal patterns of neural dynamics in Alzheimer’s disease by Nobukawa, Sou, Ikeda, Takashi, Kikuchi, Mitsuru, Takahashi, Tetsuya

    Published in Scientific reports (02-01-2024)
    “…Cognitive functions produced by large-scale neural integrations are the most representative ‘emergence phenomena’ in complex systems. A novel approach focusing…”
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  6. 6

    Identification of Electroencephalogram Signals in Alzheimer's Disease by Multifractal and Multiscale Entropy Analysis by Ando, Momo, Nobukawa, Sou, Kikuchi, Mitsuru, Takahashi, Tetsuya

    Published in Frontiers in neuroscience (28-06-2021)
    “…Alzheimer's disease (AD) is the most common form of dementia and is a progressive neurodegenerative disease that primarily develops in old age. In recent…”
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  7. 7

    Dynamic Pattern Recognition Model Based on Neural Network Response to Signal Fluctuation by Doho, Hirotaka, Nishimura, Haruhiko, Nobukawa, Sou

    “…We have proposed a model of dynamic retrieval in associative memory based on temporal input/output correlations under a stimulus-response open scheme of neural…”
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  8. 8

    Editorial: Perspectives in brain-network dynamics in computational psychiatry by Nobukawa, Sou, Takahashi, Tetsuya

    Published in Frontiers in computational neuroscience (22-09-2023)
    “…In these multiscale neural activities, the network dynamics, which is captured by the degree of synchronization and information flow between pair-wise brain…”
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  9. 9

    Resonance phenomena controlled by external feedback signals and additive noise in neural systems by Nobukawa, Sou, Shibata, Natsusaku, Nishimura, Haruhiko, Doho, Hirotaka, Wagatsuma, Nobuhiko, Yamanishi, Teruya

    Published in Scientific reports (02-09-2019)
    “…Chaotic resonance is a phenomenon that can replace the fluctuation source in stochastic resonance from additive noise to chaos. We previously developed a…”
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  10. 10

    Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise by Nobukawa, Sou, Nishimura, Haruhiko

    Published in International journal of neural systems (01-08-2016)
    “…Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of…”
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  11. 11

    Chaotic Resonance in Typical Routes to Chaos in the Izhikevich Neuron Model by Nobukawa, Sou, Nishimura, Haruhiko, Yamanishi, Teruya

    Published in Scientific reports (02-05-2017)
    “…Chaotic resonance (CR), in which a system responds to a weak signal through the effects of chaotic activities, is a known function of chaos in neural systems…”
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  12. 12

    Long-Tailed Characteristic of Spiking Pattern Alternation Induced by Log-Normal Excitatory Synaptic Distribution by Nobukawa, Sou, Nishimura, Haruhiko, Wagatsuma, Nobuhiko, Ando, Satoshi, Yamanishi, Teruya

    “…Studies of structural connectivity at the synaptic level show that in synaptic connections of the cerebral cortex, the excitatory postsynaptic potential (EPSP)…”
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  13. 13

    Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer's Disease by Nobukawa, Sou, Yamanishi, Teruya, Kasakawa, Shinya, Nishimura, Haruhiko, Kikuchi, Mitsuru, Takahashi, Tetsuya

    Published in Frontiers in psychiatry (07-04-2020)
    “…Electroencephalography (EEG) has long been studied as a potential diagnostic method for Alzheimer's disease (AD). The pathological progression of AD leads to…”
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  14. 14

    Temporal-specific complexity of spiking patterns in spontaneous activity induced by a dual complex network structure by Nobukawa, Sou, Nishimura, Haruhiko, Yamanishi, Teruya

    Published in Scientific reports (04-09-2019)
    “…Temporal fluctuation of neural activity in the brain has an important function in optimal information processing. Spontaneous activity is a source of such…”
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  15. 15

    Analysis of Chaotic Resonance in Izhikevich Neuron Model by Nobukawa, Sou, Nishimura, Haruhiko, Yamanishi, Teruya, Liu, Jian-Qin

    Published in PloS one (30-09-2015)
    “…In stochastic resonance (SR), the presence of noise helps a nonlinear system amplify a weak (sub-threshold) signal. Chaotic resonance (CR) is a phenomenon…”
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  16. 16

    Impact of time-history terms on reservoir dynamics and prediction accuracy in echo state networks by Ebato, Yudai, Nobukawa, Sou, Sakemi, Yusuke, Nishimura, Haruhiko, Kanamaru, Takashi, Sviridova, Nina, Aihara, Kazuyuki

    Published in Scientific reports (15-04-2024)
    “…The echo state network (ESN) is an excellent machine learning model for processing time-series data. This model, utilising the response of a recurrent neural…”
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  17. 17

    Identification of attention-deficit hyperactivity disorder based on the complexity and symmetricity of pupil diameter by Nobukawa, Sou, Shirama, Aya, Takahashi, Tetsuya, Takeda, Toshinobu, Ohta, Haruhisa, Kikuchi, Mitsuru, Iwanami, Akira, Kato, Nobumasa, Toda, Shigenobu

    Published in Scientific reports (19-04-2021)
    “…Adult attention-deficit/hyperactivity disorder (ADHD) frequently leads to psychological/social dysfunction if unaddressed. Identifying a reliable biomarker…”
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  18. 18

    Routes to Chaos Induced by a Discontinuous Resetting Process in a Hybrid Spiking Neuron Model by Nobukawa, Sou, Nishimura, Haruhiko, Yamanishi, Teruya

    Published in Scientific reports (10-01-2018)
    “…Several hybrid spiking neuron models combining continuous spike generation mechanisms and discontinuous resetting processes following spiking have been…”
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  19. 19

    Synchronization of Chaos in Neural Systems by Nobukawa, Sou, Nishimura, Haruhiko

    “…Multiple non-linear systems demonstrate the phenomenon where fluctuations enhance the synchronization and periodic behaviors of the system. In the phenomenon…”
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  20. 20

    Alteration of Neural Network Activity With Aging Focusing on Temporal Complexity and Functional Connectivity Within Electroencephalography by Ando, Momo, Nobukawa, Sou, Kikuchi, Mitsuru, Takahashi, Tetsuya

    Published in Frontiers in aging neuroscience (04-02-2022)
    “…With the aging process, brain functions, such as attention, memory, and cognitive functions, degrade over time. In a super-aging society, the alteration of…”
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