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用于体内亚毫秒级相互作用的多神经元活动的实时自动分类

Real-time and automatic sorting of multi-neuronal activity for sub-millisecond interactions in vivo.

作者信息

Takahashi S, Sakurai Y

机构信息

Department of Psychology, Graduate School of Letters, Kyoto University, Kyoto 606-8501, Japan.

出版信息

Neuroscience. 2005;134(1):301-15. doi: 10.1016/j.neuroscience.2005.03.031.

Abstract

Recent in vitro electrophysiological studies have revealed that neighboring interneurons interact with each other in a sub-millisecond time range via gap junctions and that individual dendritic compartments generate local excitation spikes and back-propagated spikes within a single-neuron. However, most in vivo electrophysiological studies using behaving animals only focus on activity rates of single-neurons and/or large neuronal populations without considering the potential role of such sub-millisecond interactions among neurons. This neglect is due to the limitation of ordinary in vivo multi-neuronal recording and spike sorting techniques applied to behaving animals. Though independent component analysis (ICA) is a powerful method to overcome certain limitations, ICA has a serious problem in that the number of single-electrodes (microwires) must be more than the number of single-neurons to be recorded. Our recently-developed method has solved this limitation of ICA, but a few problems have remained: the computational load is heavy, the method can be used only for off-line, not real-time, processing, and the electrode-neuron drift problem remains unsolved. In this paper, solving all these problems, we introduce a novel system consisting of automatic and real-time spike sorting with ICA in combination with a newly developed multi-electrode, dodecatrode. The system has the potential to answer some important neurobiological questions that have not been explored in in vivo electrophysiological experiments: how sub-millisecond interactions between closely neighboring single-neurons act in freely behaving animals. The system promises to be a bridge connecting electrophysiological studies in vitro and in vivo.

摘要

最近的体外电生理研究表明,相邻的中间神经元通过缝隙连接在亚毫秒时间范围内相互作用,并且单个树突区室在单个神经元内产生局部兴奋尖峰和反向传播尖峰。然而,大多数使用行为动物的体内电生理研究仅关注单个神经元和/或大型神经元群体的活动率,而没有考虑神经元之间这种亚毫秒相互作用的潜在作用。这种忽视是由于应用于行为动物的普通体内多神经元记录和尖峰分类技术的局限性。尽管独立成分分析(ICA)是一种克服某些局限性的强大方法,但ICA存在一个严重问题,即单电极(微丝)的数量必须多于要记录的单个神经元的数量。我们最近开发的方法解决了ICA的这一局限性,但仍存在一些问题:计算量很大,该方法只能用于离线处理,而不能用于实时处理,并且电极-神经元漂移问题仍然没有解决。在本文中,我们解决了所有这些问题,介绍了一种新颖的系统,该系统由结合ICA的自动实时尖峰分类与新开发的多电极十二电极组成。该系统有潜力回答一些在体内电生理实验中尚未探索的重要神经生物学问题:紧密相邻的单个神经元之间的亚毫秒相互作用在自由行为动物中是如何起作用的。该系统有望成为连接体外和体内电生理研究的桥梁。

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