Collins D R, Park H, Turvey M T
Center for the Ecological Study of Perception and Action, University of Connecticut, Storrs, CT 06269, USA.
Motor Control. 1998 Jul;2(3):228-40. doi: 10.1123/mcj.2.3.228.
Von Holst (1939/1973) parsed intersegmental coordination into relative and absolute to distinguish moderate and extreme forms. Kelso and DeGuzman (1992) discussed an interpretation of relative coordination in terms of the chaotic phenomenon of intermittency. The data of concern (DeGuzman & Kelso, 1991) do not, however, exclude a stochastic interpretation, which is detailed here following earlier suggestions. The key difference is modeling relative coordination by stochastic variability about weak attractors rather than by deterministic variability about remnants of attractors ("ghost attractors"). The intermittency interpretation is not robust in the presence of noise and, therefore, is not well disposed to account for uncertainty in detailing a model of behavioral data or its parameters. In contrast, the stochastic interpretation is based upon an approximation of unknown underlying processes in the form of Gaussian white noise. A stochastic method for estimating model parameters from a stationary probability distribution and a mean first passage time is illustrated using experimental and simulated data.
冯·霍尔斯特(1939/1973)将节段间协调分为相对协调和绝对协调,以区分适度和极端形式。凯尔索和德古兹曼(1992)从间歇性的混沌现象角度讨论了对相对协调的一种解释。然而,相关数据(德古兹曼和凯尔索,1991)并不排除一种随机解释,在此按照先前的建议详细阐述这种解释。关键区别在于,相对协调是通过围绕弱吸引子的随机变异性来建模,而不是通过围绕吸引子残余(“幽灵吸引子”)的确定性变异性来建模。间歇性解释在存在噪声的情况下并不稳健,因此,在详细阐述行为数据模型或其参数时,不太适合解释不确定性。相比之下,随机解释基于以高斯白噪声形式对未知潜在过程的近似。使用实验数据和模拟数据说明了一种从平稳概率分布和平均首次通过时间估计模型参数的随机方法。