论文标题
使用三方突触的生物计算模型可提供可靠的神经元逻辑门，具有峰值模式多样性
Biocomputing Model Using Tripartite Synapses Provides Reliable Neuronal Logic Gating with Spike Pattern Diversity
论文作者
论文摘要
生物计算技术利用涉及细胞 - 细胞信号传播的生物通信机制来执行计算。最近，研究人员致力于实现神经元制造的逻辑门，以开发新的设备，例如有机神经植物或细胞制造的脑植入物，在此称为生物植入物。这种方法引起了一些挑战，主要与神经元交流的随机性质和噪音有关。由于星形胶质细胞在神经元活动的调节中起着至关重要的作用，因此可以设计出星形胶质细胞来控制有利于可靠生物计算的突触。这项工作提出了一个涉及神经元和星形胶质细胞的神经元逻辑门的数学模型，即实现或和门控。我们使用Izhikevich和Postnov模型的浅耦合来表征具有尖峰模式变异性和星形胶质细胞突触调节的门控响应。逻辑操作误差率和准确性评估不同突触高斯噪声水平的门和 /或门的性能。我们的结果表明，星形胶质细胞调节活性可以有效地用作一种剥夺机制，为高度可靠的生物计算实施铺平了道路。
Biocomputing technologies exploit biological communication mechanisms involving cell-cell signal propagation to perform computations. Researchers recently worked toward realising logic gates made by neurons to develop novel devices such as organic neuroprostheses or brain implants made by cells, herein termed living implants. Several challenges arise from this approach, mainly associated with the stochastic nature and noise of neuronal communication. Since astrocytes play a crucial role in the regulation of neurons activity, there is a possibility whereby astrocytes can be engineered to control synapses favouring reliable biocomputing. This work proposes a mathematical model of neuronal logic gates involving neurons and astrocytes, realising OR and AND gating. We use a shallow coupling of both the Izhikevich and Postnov models to characterise gating responses with spike pattern variability and astrocyte synaptic regulation. Logic operation error ratio and accuracy assess the AND and OR gates' performances at different synaptic Gaussian noise levels. Our results demonstrate that the astrocyte regulating activity can effectively be used as a denoising mechanism, paving the way for highly reliable biocomputing implementations.
