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A functional assembly framework based on implementable neurobionic material
Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805406/ https://www.ncbi.nlm.nih.gov/pubmed/33463062 http://dx.doi.org/10.1002/ctm2.277 |
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author | Zou, Xiang Jiang, Conglin Sun, Yirui Zhao, Donghua Tong, Yusheng Mao, Ying Chen, Liang |
author_facet | Zou, Xiang Jiang, Conglin Sun, Yirui Zhao, Donghua Tong, Yusheng Mao, Ying Chen, Liang |
author_sort | Zou, Xiang |
collection | PubMed |
description | Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary to develop a feasible neurobionics framework to realize advanced brain function. In this study, we proposed a mathematical neurobionic material model, and attempted to explore advanced function only by simple and feasible structures. Here an equivalent simplified framework was used to describe the dynamics expressed in an equation set, while in vivo study was performed to verify simulation results. In neural tissue, the output of neurobionic material was characterized by spike frequency, and the stability is based on the excitatory/inhibitory proportion. Spike frequency in mathematical neurobionic material model can spontaneously meet the solution of a nonlinear equation set. Assembly can also evolve into a certain distribution under different stimulations, closely related to decision making. Short‐term memory can be formed by coupling neurobionic material assemblies. In vivo experiments further confirmed predictions in our mathematical neurobionic material model. The property of this neural biomimetic material model demonstrates its intrinsic neuromorphic computational ability, which should offer promises for implementable neurobionic device design. |
format | Online Article Text |
id | pubmed-7805406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78054062021-01-22 A functional assembly framework based on implementable neurobionic material Zou, Xiang Jiang, Conglin Sun, Yirui Zhao, Donghua Tong, Yusheng Mao, Ying Chen, Liang Clin Transl Med Research Articles Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary to develop a feasible neurobionics framework to realize advanced brain function. In this study, we proposed a mathematical neurobionic material model, and attempted to explore advanced function only by simple and feasible structures. Here an equivalent simplified framework was used to describe the dynamics expressed in an equation set, while in vivo study was performed to verify simulation results. In neural tissue, the output of neurobionic material was characterized by spike frequency, and the stability is based on the excitatory/inhibitory proportion. Spike frequency in mathematical neurobionic material model can spontaneously meet the solution of a nonlinear equation set. Assembly can also evolve into a certain distribution under different stimulations, closely related to decision making. Short‐term memory can be formed by coupling neurobionic material assemblies. In vivo experiments further confirmed predictions in our mathematical neurobionic material model. The property of this neural biomimetic material model demonstrates its intrinsic neuromorphic computational ability, which should offer promises for implementable neurobionic device design. John Wiley and Sons Inc. 2021-01-13 /pmc/articles/PMC7805406/ /pubmed/33463062 http://dx.doi.org/10.1002/ctm2.277 Text en © 2021 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Zou, Xiang Jiang, Conglin Sun, Yirui Zhao, Donghua Tong, Yusheng Mao, Ying Chen, Liang A functional assembly framework based on implementable neurobionic material |
title | A functional assembly framework based on implementable neurobionic material |
title_full | A functional assembly framework based on implementable neurobionic material |
title_fullStr | A functional assembly framework based on implementable neurobionic material |
title_full_unstemmed | A functional assembly framework based on implementable neurobionic material |
title_short | A functional assembly framework based on implementable neurobionic material |
title_sort | functional assembly framework based on implementable neurobionic material |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805406/ https://www.ncbi.nlm.nih.gov/pubmed/33463062 http://dx.doi.org/10.1002/ctm2.277 |
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