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振荡现象以动态形式普遍存在于神经系统中,并且与大脑的信息处理、传递和整合、巩固记忆等高级认知活动密切相关。神经振荡的特定活动模式往往关联认知功能及其变化,因此如何量化分析神经振荡活动模式成为了计算神经生物学的研究热点之一。结合作者实验室近年来的研究工作,本文对在神经生物学和认知科学研究中常用的多种分析算法进行了详细而全面的综述,并试图按照度量指标及耦合或同步方式的差异进行归类。通过算法比较,给出计算特点及算法适用情形。最后对将来有潜在应用价值的几种多维算法进行了深入的探讨。
Oscillatory phenomena are ubiquitous in the nervous system in dynamic form and are closely related to advanced cognitive processes such as brain information processing, transmission and integration, and memory consolidation. Therefore, how to quantitatively analyze the mode of neuron oscillation has become one of the hot topics in neurobiology research. In combination with recent research work by author labs, this article provides a detailed and comprehensive review of various analytical algorithms commonly used in neurobiology and cognitive science research, and tries to assess the differences between metrological indexes and coupling or synchronization methods class. Through the comparison of algorithms, the calculation characteristics and the application of the algorithm are given. Finally, several multidimensional algorithms with potential applications in the future are discussed in depth.