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An automated method to remove artifacts induced by microstimulation in local field potentials recorded from rat somatosensory cortex

机译:一种自动化方法,用于去除从大鼠躯体卷曲皮层记录的局部场电位中微刺激诱导的伪影

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Stimulus evoked field potentials are commonly used in studying sensory systems. But, the stimulus induced signals are often contaminated by stimulus artifacts. Especially, microstimulation greatly affects the recorded field potentials. In this paper, we present a novel technique capable of removing the microstimulation induced stimulus artifacts from the recorded sensory signals (local field potentials, LFPs). The algorithm detects the start and the end of the artifact based on signal derivative and removes the artifacts from the recordings. This algorithm overcomes the barrier of artifact shape, duration, and frequency imposed by many existing techniques and provides the flexibility of automatic batch processing of multiple neuronal signals. This technique provides the advantages of being simple, straightforward, and computationally efficient, demonstrating to be an efficient and accurate artifact removal method, as validated by analyzing recordings from the rat somatosensory cortex (S1) using standard borosilicate micropipettes (1 MΩ).
机译:刺激诱发的现场电位通常用于研究感官系统。但是,刺激诱导的信号通常被刺激伪影污染。特别是,微刺激极大地影响了记录的现场电位。在本文中,我们提出了一种能够从记录的感觉信号(本地场电位,LFP)中去除微刺激诱导刺激伪影的新技术。该算法基于信号导数检测伪像的开始和末尾,并从录像中删除伪像。该算法克服了许多现有技术所施加的伪影形,持续时间和频率的屏障,并提供多个神经元信号的自动批量处理的灵活性。该技术提供了简单,简单,简单,计算的优点,表明是一种有效且准确的伪像去除方法,通过使用标准硼硅酸盐微量化合物(1M&#x03a9)分析来自大鼠体敏感皮层(S1)的录音来验证。

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