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使用中脑多巴胺神经元的峰峰间期,预测误差的标度并未证实不规则放电背后存在混沌动力学。

Scaling of prediction error does not confirm chaotic dynamics underlying irregular firing using interspike intervals from midbrain dopamine neurons.

作者信息

Canavier C C, Perla S R, Shepard P D

机构信息

Department of Psychology, University of New Orleans, GP2001, 2000 Lakeshore Drive, New Orleans, LA 70471, USA.

出版信息

Neuroscience. 2004;129(2):491-502. doi: 10.1016/j.neuroscience.2004.08.003.

Abstract

Dopamine neurons in the substantia nigra pars compacta often fire in an irregular, single spike mode in vivo, and a similar firing pattern can be observed in vitro when small conductance calcium-activated potassium channel blockers are applied to the bath. It is not clear whether the irregular firing is due to stochastic processes or nonlinear deterministic processes. A previous study [Neuroscience 104 (2001) 829] used nonlinear forecasting methods applied to a continuous function derived from the interspike interval (ISI) data from irregularly firing dopamine neurons to show that the predictability scaled exponentially with forecast horizon and was consistent with nonlinear deterministic chaos. However, we show here that the observed exponential scaling is also consistent with a stochastic process, because it did not differ significantly from that of shuffled surrogate data. On the other hand, nonlinear forecasting directly from the ISI data using the package TISEAN provided some evidence for nonlinear deterministic structure in four of five records obtained in vitro and in two of nine records obtained in vivo. Although we cannot rule out a role for nonlinear chaotic dynamics in structuring the firing pattern, we suggest an alternate hypothesis that includes a mechanism by which the firing pattern can become more variable in the presence of a constant level of background noise.

摘要

黑质致密部的多巴胺能神经元在体内常以不规则的单个峰电位模式放电,当在浴液中应用小电导钙激活钾通道阻滞剂时,在体外也可观察到类似的放电模式。尚不清楚这种不规则放电是由于随机过程还是非线性确定性过程所致。先前的一项研究[《神经科学》第104卷(2001年)第829页]使用非线性预测方法,对从不规则放电的多巴胺能神经元的峰电位间隔(ISI)数据导出的连续函数进行分析,结果表明可预测性随预测时间呈指数缩放,且与非线性确定性混沌一致。然而,我们在此表明,观察到的指数缩放也与随机过程一致,因为它与打乱的替代数据的指数缩放没有显著差异。另一方面,使用TISEAN软件包直接从ISI数据进行非线性预测,为体外获得的5条记录中的4条以及体内获得的9条记录中的2条的非线性确定性结构提供了一些证据。虽然我们不能排除非线性混沌动力学在构建放电模式中所起的作用,但我们提出了另一种假设,其中包括一种机制,即在恒定水平的背景噪声存在下,放电模式如何变得更具变异性。

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