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使用基于熵的方法量化时变多单元神经活动。

Quantifying time-varying multiunit neural activity using entropy based measures.

作者信息

Choi Young-Seok, Koenig Matthew A, Jia Xiaofeng, Thakor Nitish V

出版信息

IEEE Trans Biomed Eng. 2010 Nov;57(11). doi: 10.1109/TBME.2010.2049266. Epub 2010 May 10.

DOI:10.1109/TBME.2010.2049266
PMID:20460201
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3111013/
Abstract

Modern micro-electrode arrays make it possible to simultaneously record population neural activity. However, methods to analyze multiunit activity (MUA), which reflects the aggregate spiking activity of a population of neurons, have remained underdeveloped in comparison to those used for studying single unit activity (SUA). In scenarios where SUA is hard to record and maintain or is not representative of brains response, MUA is informative in deciphering the brains complex time-varying response to stimuli or to clinical insults. Here, we present two quantitative methods of analysis of the time-varying dynamics of MUA without spike detection. These methods are based on the multiresolution discrete wavelet transform (DWT) of an envelope of MUA followed by information theoretic measures: multiresolution entropy (MRE) and the multiresolution Kullback-Leibler distance (MRKLD). We test the proposed quantifiers on both simulated and experimental MUA recorded from rodent cortex in an experimental model of global hypoxic-ischemic brain injury. First, our results validate the use of the envelope of MUA as an alternative to detecting and analyzing transient and complex spike activity. Second, the MRE and MRKLD are shown to respond to dynamic changes due to the brains response to global injury and to identify the transient changes in the MUA.

摘要

现代微电极阵列使同时记录群体神经活动成为可能。然而,与用于研究单神经元活动(SUA)的方法相比,用于分析多单位活动(MUA,反映一群神经元的总体放电活动)的方法仍未得到充分发展。在SUA难以记录和维持或不能代表大脑反应的情况下,MUA对于解读大脑对刺激或临床损伤的复杂时变反应具有参考价值。在此,我们提出两种无需检测尖峰信号即可分析MUA时变动力学的定量方法。这些方法基于MUA包络的多分辨率离散小波变换(DWT),随后采用信息论度量:多分辨率熵(MRE)和多分辨率库尔贝克-莱布勒距离(MRKLD)。我们在全球缺氧缺血性脑损伤实验模型中,对从啮齿动物皮层记录的模拟和实验MUA测试了所提出的量化指标。首先,我们的结果验证了使用MUA包络作为检测和分析瞬态及复杂尖峰活动的替代方法的有效性。其次,MRE和MRKLD显示出对大脑对整体损伤反应引起的动态变化有响应,并能识别MUA中的瞬态变化。

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