Automated Distributed Element Model Generation for Neural Interface Co-Design
Automated Distributed Element Model Generation for Neural Interface Co-Design
复制标题
用于神经接口协同设计的自动分布式元素模型生成
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Benjamin C. Johnson
中科院分区：
文献类型：
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作者：
Fnu Tala;M. Bandali;Benjamin C. Johnson
我们提出了一个脚本化的分布式元件建模框架，使过程便携式协同设计的神经记录和刺激电路和其他应用程序，需要协同设计与电极电解质接口。使用分布式元件使设计人员能够模拟组织中的空间电压和电流分布，以确定关键参数，例如刺激器电压裕量、刺激伪影和电荷平衡。设计人员在MATLAB中指定电极配置的2D或3D物理参数，然后在Cadence Virtuoso中生成网表，用于电路仿真。使用这个框架，我们表明，时域伪影消除技术优于频域技术的并发神经记录和刺激。
We present a scripted distributed element modeling framework to enable process-portable co-design of neural recording and stimulation circuits and other applications that require co-design with an electrode-electrolyte interface. Using distributed elements enables designers to simulate the spatial voltage and current profiles in tissue to determine key parameters such as stimulator voltage headroom, stimulation artifact, and charge-balance. Designers specify 2D or 3D physical parameters of the electrode configuration in MATLAB, which in turn generates a netlist in Cadence Virtuoso for simulation with circuitry. Using this framework, we show that time-domain artifact cancellation techniques outperform frequency-domain techniques for concurrent neural recording and stimulation.