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用于生物传感器应用的神经元网络同步测量

Measuring synchronization in neuronal networks for biosensor applications.

作者信息

Selinger Jonathan V, Pancrazio Joseph J, Gross Guenter W

机构信息

Center for Bio/Molecular Science and Engineering, Naval Research Laboratory, Code 6900, 4555 Overlook Avenue, SW, Washington, DC 20375, USA.

出版信息

Biosens Bioelectron. 2004 Feb 15;19(7):675-83. doi: 10.1016/s0956-5663(03)00267-7.

Abstract

Cultures of neurons can be grown on microelectrode arrays (MEAs), so that their spike and burst activity can be monitored. These activity patterns are quite sensitive to changes in the environment, such as chemical exposure, and hence the cultures can be used as biosensors. One key issue in analyzing the data from neuronal networks is how to quantify the level of synchronization among different units, which represent different neurons in the network. In this paper, we propose a synchronization metric, based on the statistical distribution of unit-to-unit correlation coefficients. We show that this synchronization metric changes significantly when the networks are exposed to bicuculline, strychnine, or 2,3-dioxo-6-nitro-l,2,3,4-tetrahydrobenzoquinoxaline-7-sulphonamide (NBQX). For that reason, this metric can be used to characterize pharmacologically induced changes in a network, either for research or for biosensor applications.

摘要

神经元培养物可以生长在微电极阵列(MEA)上,以便监测其尖峰和爆发活动。这些活动模式对环境变化(如化学物质暴露)非常敏感,因此培养物可用作生物传感器。分析神经网络数据的一个关键问题是如何量化不同单元之间的同步水平,这些单元代表网络中的不同神经元。在本文中,我们基于单元间相关系数的统计分布提出了一种同步度量。我们表明,当网络暴露于荷包牡丹碱、士的宁或2,3-二氧代-6-硝基-1,2,3,4-四氢苯并喹喔啉-7-磺酰胺(NBQX)时,这种同步度量会发生显著变化。因此,该度量可用于表征网络中药物诱导的变化,无论是用于研究还是生物传感器应用。

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