生産研究
Online ISSN : 1881-2058
Print ISSN : 0037-105X
ISSN-L : 0037-105X
研究速報
ニューロハイブリッドシステム:生物医学的応用の未来
西川 ステファニー舞コイラティ ファラドアイレア アンクレア金 秀炫井樋田 悟史年吉 洋ティクシェ三田 アニエス池内 与志穂河野 崇合原 一幸藤井 輝夫レヴィ ティモテ
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ジャーナル フリー

2019 年 71 巻 4 号 p. 787-790

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Nowadays, neurological disorders that disrupt the connections between the brain and the body causing paralysis affect millions of people around the world. The development of neuroprostheses has and will have a serious impact on the quality of life. These neuroprostheses are designed from knowledge of neural networks and their interaction, taking into account the spontaneous activity of neural networks but also the activity of these networks following various stimuli. These systems must integrate the behavior of the neural network to be replaced but also generate the appropriate stimuli to restore the desired neural function. The hardware system that interfaces with the biological component is a network of biomimetic Spiking Neural Network (SNN). A neural activity recording and stimulation platform is also mandatory for testing the different approach and hypothesis. The aim of this work is to enable bio-hybrid experiments which means bi-directional communications between artificial neurons and biological neurons, allowing tools to be developed for further biomedical understanding of the nervous system. Here, we propose some set up experiments using biomimetic artificial neural network connected in a bi-directional communication with ‘in vitro’ cells. Nowadays, neurological disorders that disrupt the connections between the brain and the body causing paralysis affect millions of people around the world. The development of neuroprostheses has and will have a serious impact on the quality of life. These neuroprostheses are designed from knowledge of neural networks and their interaction, taking into account the spontaneous activity of neural networks but also the activity of these networks following various stimuli. These systems must integrate the behavior of the neural network to be replaced but also generate the appropriate stimuli to restore the desired neural function. The hardware system that interfaces with the biological component is a network of biomimetic Spiking Neural Network

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© 2019 東京大学生産技術研究所
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