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稳健的神经元检测和自动解混分类算法

Method for Robust Spike Sorting with Automatic Overlap Decomposition

中文摘要英文摘要

在神经系统信息处理研究中,为分析多电极记录信号,神经元动作电位检测和分类是必不可少的第一步。细胞外记录经常包含由电极附近多个神经元动作电位叠加产生的信号和特性未知的背景噪声。在本文的研究中,提出了一种稳健的方法来处理这些问题,该方法使用了基于RELAX算法的自动解混叠技术,而RELAX算法可以通过快速傅立叶变换有效实施。通过把本文提出的方法的与已报道的一种算法应用于不同信噪比的基于实测数据合成的数据集,结果显示新方法有更优越的性能。

Spike sorting is the mandatory first step in analyzing multi-unit recording signals for studying information processing mechanisms within the nervous system. Extracellular recordings usually contain overlapped spikes produced by a number of neurons adjacent to the electrode, together with background noise having unknown properties. In the present study, a robust method to deal with these problems is proposed. The method employs an automatic overlap decomposition technique based on the relaxation (RELAX) algorithm that requires simple fast Fourier transforms (FFT’s). The performance of the presented system is better than that of a previously published method tested at various signal-to-noise ratio(SNR) levels based on synthetic data that were generated from real data.

王光力、梁培基

生物科学研究方法、生物科学研究技术计算技术、计算机技术

动作电位检测和分类 RELAX算法 多电极记录

Spike sorting RELAX algorithm Multi-unit recordings

王光力,梁培基.稳健的神经元检测和自动解混分类算法[EB/OL].(2005-12-19)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/200512-478.点此复制

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