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利用独立成分分析从豚鼠体内光学记录中分离信号与噪声。

Separation of signal and noise from in vivo optical recording in Guinea pigs using independent component analysis.

作者信息

Maeda S, Inagaki S, Kawaguchi H, Song W J

机构信息

Department of Electronic Engineering, Graduate School of Engineering, Osaka University, 565-0821, Suita, Japan.

出版信息

Neurosci Lett. 2001 Apr 20;302(2-3):137-40. doi: 10.1016/s0304-3940(01)01678-0.

Abstract

Optical recording in vivo severely suffers from the interference of heartbeat noise. So far, heartbeat noise has been minimized by subtracting from each experimental trial an average of interlaced control recordings. This method, however, is time-consuming and increases tissue damage due to phototoxicity. Here we applied independent component analysis (ICA) to in vivo optical recordings, for separation of auditory signals and noises. Our results show that ICA can be successfully used to separate sound-evoked signals and heartbeat noises. Compared with the previous method, ICA has a comparable power of separation and does not require background recordings.

摘要

体内光学记录严重受到心跳噪声的干扰。到目前为止,通过从每个实验试验中减去交错控制记录的平均值,心跳噪声已被最小化。然而,这种方法既耗时又会因光毒性增加组织损伤。在这里,我们将独立成分分析(ICA)应用于体内光学记录,以分离听觉信号和噪声。我们的结果表明,ICA可以成功地用于分离声音诱发信号和心跳噪声。与以前的方法相比,ICA具有相当的分离能力,并且不需要背景记录。

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