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使用混合交流/直流分频滤波器的全频段脑电图记录

Full-Band EEG Recordings Using Hybrid AC/DC-Divider Filters.

作者信息

Nasretdinov Azat, Evstifeev Alexander, Vinokurova Daria, Burkhanova-Zakirova Gulshat, Chernova Kseniya, Churina Zoya, Khazipov Roustem

机构信息

Laboratory of Neurobiology, Kazan Federal University, Kazan 420008, Russia

Laboratory of Neurobiology, Kazan Federal University, Kazan 420008, Russia.

出版信息

eNeuro. 2021 Aug 25;8(4). doi: 10.1523/ENEURO.0246-21.2021. Print 2021 Jul-Aug.

Abstract

Full-band DC recordings enable recording of slow electrical brain signals that are severely compromised during conventional AC recordings. However, full-band DC recordings may be limited by the amplifier's dynamic input range and the loss of small amplitude high-frequency signals. Recently, Neuralynx has proposed full-band recordings with inverse filtering for signal reconstruction based on hybrid AC/DC-divider RRC filters that enable only partial suppression of DC signals. However, the quality of signal reconstruction for biological signals has not yet been assessed. Here, we propose a novel digital inverse filter based on a mathematical model describing RRC filter properties, which provides high computational accuracy and versatility. Second, we propose procedures for the evaluation of the inverse filter coefficients, adapted for each recording channel to minimize the error caused by the deviation of the real values of the RRC filter elements from their nominal values. We demonstrate that this approach enables near 99% reconstruction quality of high-potassium-induced cortical spreading depolarizations (SDs), endothelin-induced ischemic negative ultraslow potentials (NUPs), and whole-cell recordings of membrane potential using RRC filters. The quality of the reconstruction was significantly higher than with the existing inverse filtering procedures. Thus, RRC filters with inverse filtering are optimal for full-band EEG recordings in various applications.

摘要

全频段直流记录能够记录在传统交流记录过程中严重受损的缓慢脑电信号。然而,全频段直流记录可能会受到放大器动态输入范围以及小幅度高频信号损失的限制。最近,Neuralynx提出了基于混合交流/直流分频器RRC滤波器进行信号重建的全频段记录方法,该滤波器仅能部分抑制直流信号。然而,生物信号的信号重建质量尚未得到评估。在此,我们基于描述RRC滤波器特性的数学模型提出了一种新型数字逆滤波器,它具有高计算精度和通用性。其次,我们提出了评估逆滤波器系数的程序,该程序适用于每个记录通道,以最小化由RRC滤波器元件实际值与其标称值偏差所导致的误差。我们证明,这种方法能够使用RRC滤波器实现高钾诱导的皮层扩散性去极化(SDs)、内皮素诱导的缺血性负超慢电位(NUPs)以及膜电位全细胞记录近99%的重建质量。重建质量显著高于现有的逆滤波程序。因此,具有逆滤波功能的RRC滤波器在各种应用中对于全频段脑电图记录是最优的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/361b/8387152/a7f6005393f2/ENEURO.0246-21.2021_f006.jpg

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