Schöner G, Kelso J A
Center for Complex Systems, Florida Atlantic University, Boca Raton 33431.
Science. 1988 Mar 25;239(4847):1513-20. doi: 10.1126/science.3281253.
In the search for principles of pattern generation in complex biological systems, an operational approach is presented that embraces both theory and experiment. The central mathematical concepts of self-organization in nonequilibrium systems (including order parameter dynamics, stability, fluctuations, and time scales) are used to show how a large number of empirically observed features of temporal patterns can be mapped onto simple low-dimensional (stochastic, nonlinear) dynamical laws that are derivable from lower levels of description. The theoretical framework provides a language and a strategy, accompanied by new observables, that may afford an understanding of dynamic patterns at several scales of analysis (including behavioral patterns, neural networks, and individual neurons) and the linkage among them.
在探索复杂生物系统中模式生成的原理时，提出了一种将理论与实验相结合的操作性方法。非平衡系统中自组织的核心数学概念（包括序参量动力学、稳定性、涨落和时间尺度）被用于展示如何将大量时间模式的经验观察特征映射到可从较低描述层次推导出来的简单低维（随机、非线性）动力学定律上。该理论框架提供了一种语言和一种策略，并伴随着新的可观测指标，这可能有助于理解多个分析尺度上的动态模式（包括行为模式、神经网络和单个神经元）以及它们之间的联系。
