神经分子计算逻辑门的星形胶质细胞钙信号工程
Engineering Calcium Signaling of Astrocytes for Neural-Molecular Computing Logic Gates
摘要：
本文提出了使用真核细胞，即星形胶质细胞，开发逻辑门。通过基于输入信号操纵单元之间的Ca $^{2+}$离子流的阈值来实现逻辑门。通过用pcDNA3.1-hGPR 17基因工程化星形胶质细胞的湿实验室实验，我们表明AND和OR门都可以通过控制流经群体的Ca $^{2+}$信号来实现。本文还提出了一个强化学习平台，以优化两个主要参数，即Ca $^{2+}$激活阈值和输入信号$T_b$进入门的时隙。该设计平台通过考虑由小区之间的信令产生的延迟和噪声，以微调激活阈值和输入信号时隙参数，来满足小区群的任何大小和连接性。为了验证强化学习平台的有效性，使用基于Ca $^{2+}$信号传导的分子通信模拟器来模拟星形胶质细胞之间的信号传导。仿真结果表明，Ca $^{2+}$激活阈值和输入信号$T_b$的时隙都需要一个最佳值，以实现最佳的计算精度，其中，对于AND和OR门，利用正确的值组合可以实现高达90%的精度。工程星形胶质细胞创建数字逻辑门的强化学习平台可用于未来的神经分子计算芯片，这可以彻底改变由工程生物细胞构建的大脑植入物。
英文摘要：
This paper proposes the use of Eukaryotic cells, namely astrocytes, to develop logic gates. The logic gates are achieved by manipulating the threshold of 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, we show that both AND and OR gates can be implemented by controlling Ca$^{2+}$ signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize two main parameters, which are the Ca$^{2+}$ activation threshold and time slot of input signals $T_b$ 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, in order to fine-tune the activation threshold and input signal time slot parameters. To validate the effectiveness of the reinforced learning platform, a Ca$^{2+}$ Signalling-based Molecular Communications Simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation showed that an optimum value for both the Ca$^{2+}$ activation threshold and time slot of input signals $T_b$ is required to achieve optimal computation accuracy, where up to 90\% accuracy for both the AND and OR gates can be achieved with the right combination of values. The reinforced learning platform for the engineered astrocytes to create digital logic gates can be used for future Neural-Molecular Computing chip, which can revolutionize brain implants that are constructed from engineered biological cells.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
