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Adaptive virtual referencing for the extraction of extracellularly recorded action potentials in noisy environments
Journal of Neural Engineering ( IF 4 ) Pub Date : 2020-10-09 , DOI: 10.1088/1741-2552/abb73c
Corey E Cruttenden 1, 2 , Wei Zhu 2 , Yi Zhang 2 , Soo Han Soon 2 , Xiao-Hong Zhu 2 , Wei Chen 2 , Rajesh Rajamani 1
Affiliation  

Objective. Removal of common mode noise and artifacts from extracellularly measured action potentials, herein referred to as spikes, recorded with multi-electrode arrays (MEAs) which included severe noise and artifacts generated by an ultrahigh field (UHF) 16.4 Tesla magnetic resonance imaging (MRI) scanner. Approach. An adaptive virtual referencing (AVR) algorithm is used to remove artifacts and thus enable extraction of neural spike signals from extracellular recordings in anesthetized rat brains. A 16-channel MEA with 150-micron inter-site spacing is used, and a virtual reference is created by spatially averaging the 16 signal channels which results in a reference signal without extracellular spiking activity while preserving common mode noise and artifacts. This virtual reference signal is then used as the input to an adaptive FIR filter which optimally scales and time-shifts the reference to each specific electrode site to remove the artifacts and noise. M...

中文翻译:

用于在嘈杂环境中提取细胞外记录的动作电位的自适应虚拟参考

客观的。从细胞外测量的动作电位中去除共模噪声和伪影,本文称为尖峰,用多电极阵列 (MEA) 记录,其中包括由超高场 (UHF) 16.4 特斯拉磁共振成像 (MRI) 产生的严重噪声和伪影扫描器。方法。自适应虚拟参考 (AVR) 算法用于去除伪影,从而能够从麻醉大鼠大脑的细胞外记录中提取神经尖峰信号。使用具有 150 微米站点间距的 16 通道 MEA,并通过对 16 个信号通道进行空间平均来创建虚拟参考,从而产生没有细胞外尖峰活动的参考信号,同时保留共模噪声和伪影。然后将该虚拟参考信号用作自适应 FIR 滤波器的输入,该滤波器以最佳方式缩放和时移参考到每个特定电极位点,以消除伪影和噪声。米...
更新日期:2020-10-12
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