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Engineering calcium signaling of astrocytes for neural–molecular computing logic gates
This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of [Formula: see text] ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803753/ https://www.ncbi.nlm.nih.gov/pubmed/33436729 http://dx.doi.org/10.1038/s41598-020-79891-x |
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author | Barros, Michael Taynnan Doan, Phuong Kandhavelu, Meenakshisundaram Jennings, Brendan Balasubramaniam, Sasitharan |
author_facet | Barros, Michael Taynnan Doan, Phuong Kandhavelu, Meenakshisundaram Jennings, Brendan Balasubramaniam, Sasitharan |
author_sort | Barros, Michael Taynnan |
collection | PubMed |
description | This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of [Formula: see text] ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling [Formula: see text] signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the [Formula: see text] activated level and time slot of input signals [Formula: see text] into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the effectiveness of the reinforced learning platform, a [Formula: see text] signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the [Formula: see text] activated level and time slot of input signals [Formula: see text] is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural–Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants. |
format | Online Article Text |
id | pubmed-7803753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78037532021-01-13 Engineering calcium signaling of astrocytes for neural–molecular computing logic gates Barros, Michael Taynnan Doan, Phuong Kandhavelu, Meenakshisundaram Jennings, Brendan Balasubramaniam, Sasitharan Sci Rep Article This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of [Formula: see text] ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling [Formula: see text] signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the [Formula: see text] activated level and time slot of input signals [Formula: see text] into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the effectiveness of the reinforced learning platform, a [Formula: see text] signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the [Formula: see text] activated level and time slot of input signals [Formula: see text] is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural–Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants. Nature Publishing Group UK 2021-01-12 /pmc/articles/PMC7803753/ /pubmed/33436729 http://dx.doi.org/10.1038/s41598-020-79891-x Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Barros, Michael Taynnan Doan, Phuong Kandhavelu, Meenakshisundaram Jennings, Brendan Balasubramaniam, Sasitharan Engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
title | Engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
title_full | Engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
title_fullStr | Engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
title_full_unstemmed | Engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
title_short | Engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
title_sort | engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803753/ https://www.ncbi.nlm.nih.gov/pubmed/33436729 http://dx.doi.org/10.1038/s41598-020-79891-x |
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