So P, Francis J T, Netoff T I, Gluckman B J, Schiff S J
Center for Neuroscience, Children's National Medical Center, and the George Washington University School of Medicine, Washington, DC 20010, USA.
Biophys J. 1998 Jun;74(6):2776-85. doi: 10.1016/S0006-3495(98)77985-8.
A new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The conceptual foundation of this analysis is the abstraction of observed neuronal activities into a dynamical landscape characterized by a hierarchy of "unstable periodic orbits" (UPOs). UPOs are rigorously identified in data sets representative of three different levels of organization in mammalian brain. An analysis based on UPOs affords a novel alternative method of decoding, predicting, and controlling these neuronal systems.
一种新的非线性动力学分析方法被应用于神经元系统的复杂行为。该分析的概念基础是将观察到的神经元活动抽象为一个由“不稳定周期轨道”(UPOs)层次结构所表征的动力学格局。在代表哺乳动物大脑三个不同组织层次的数据集里,严格识别出了UPOs。基于UPOs的分析为解码、预测和控制这些神经元系统提供了一种全新的替代方法。