Neuroscience has shown great progress in recent years. Several of the theoretical bases have arisen from the examination of dynamic systems, using Neural Mass Models (NMMs). Due to the largescale brain dynamics of NMMs and the difficulty of studying nonlinear systems, the local linearization approach to discretize the state equation was used via an algebraic formulation, as it intervenes favorably in the speed and efficiency of numerical integration. To study the spacetime organization of the brain and generate more complex dynamics, three structural levels (cortical unit, population and system) were defined and assumed, in which the new assumed representation for conduction delays and new ways of connecting were defined. This is a new time-delay NMM, which can simulate several types of EEG activities since kinetics information was considered at three levels of complexity. Results obtained in this analysis provide additional theoretical foundations and indicate specific characteristics for understanding neurodynamic.

中文翻译：

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在 NMM 中研究高维动态的计算工具

近年来，神经科学取得了巨大的进步。一些理论基础来自使用神经质量模型 (NMM) 对动态系统的检查。由于 NMM 的大规模脑动力学和研究非线性系统的困难，通过代数公式使用局部线性化方法来离散化状态方程，因为它有利地干预了数值积分的速度和效率。为了研究大脑的时空组织并产生更复杂的动力学，定义和假设了三个结构层次（皮质单元、种群和系统），其中定义了传导延迟的新假设表示和新的连接方式。这是一个新的时延 NMM，它可以模拟多种类型的 EEG 活动，因为动力学信息被考虑在三个复杂级别。该分析中获得的结果提供了额外的理论基础，并表明了理解神经动力学的具体特征。