Engineering calcium signaling of astrocytes for neural–molecular computing logic gates
Abstract This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of $$\hbox {Ca}^{2+}$$ Ca 2 + 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...
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doaj-b9fda029ec8a48e28722c146761894942021-01-17T12:40:44ZengNature Publishing GroupScientific Reports2045-23222021-01-0111111010.1038/s41598-020-79891-xEngineering calcium signaling of astrocytes for neural–molecular computing logic gatesMichael Taynnan Barros0Phuong Doan1Meenakshisundaram Kandhavelu2Brendan Jennings3Sasitharan Balasubramaniam4School of Computer Science and Electronic Engineering, University of EssexBioMediTech, Faculty of Medicine and Health Technology, Tampere UniversityBioMediTech, Faculty of Medicine and Health Technology, Tampere UniversityTelecommunication Software and Systems Group (TSSG), Waterford Institute of Technology (WIT)Telecommunication Software and Systems Group (TSSG), Waterford Institute of Technology (WIT)Abstract This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of $$\hbox {Ca}^{2+}$$ Ca 2 + 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 $$\hbox {Ca}^{2+}$$ Ca 2 + signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the $$\hbox {Ca}^{2+}$$ Ca 2 + activated level and time slot of input signals $$T_b$$ T b 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 $$\hbox {Ca}^{2+}$$ Ca 2 + 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 $$\hbox {Ca}^{2+}$$ Ca 2 + activated level and time slot of input signals $$T_b$$ T b 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.https://doi.org/10.1038/s41598-020-79891-x |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Michael Taynnan Barros Phuong Doan Meenakshisundaram Kandhavelu Brendan Jennings Sasitharan Balasubramaniam |
spellingShingle |
Michael Taynnan Barros Phuong Doan Meenakshisundaram Kandhavelu Brendan Jennings Sasitharan Balasubramaniam Engineering calcium signaling of astrocytes for neural–molecular computing logic gates Scientific Reports |
author_facet |
Michael Taynnan Barros Phuong Doan Meenakshisundaram Kandhavelu Brendan Jennings Sasitharan Balasubramaniam |
author_sort |
Michael Taynnan Barros |
title |
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_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_sort |
engineering calcium signaling of astrocytes for neural–molecular computing logic gates |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-01-01 |
description |
Abstract This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of $$\hbox {Ca}^{2+}$$ Ca 2 + 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 $$\hbox {Ca}^{2+}$$ Ca 2 + signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the $$\hbox {Ca}^{2+}$$ Ca 2 + activated level and time slot of input signals $$T_b$$ T b 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 $$\hbox {Ca}^{2+}$$ Ca 2 + 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 $$\hbox {Ca}^{2+}$$ Ca 2 + activated level and time slot of input signals $$T_b$$ T b 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. |
url |
https://doi.org/10.1038/s41598-020-79891-x |
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