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肌肉通过过滤宽带输入来表达非神经支配神经网络的运动模式。

Muscles express motor patterns of non-innervating neural networks by filtering broad-band input.

作者信息

Morris L G, Thuma J B, Hooper S L

机构信息

Department of Physiology and Biophysics, Mt. Sinai Medical School, Box 1218, 1 Gustave L. Levy Place, New York, New York 10029, USA.

出版信息

Nat Neurosci. 2000 Mar;3(3):245-50. doi: 10.1038/72955.

Abstract

We describe three slow muscles that responded to low-frequency modulation of a high-frequency neuronal input and, consequently, could express the motor patterns of neural networks whose neurons did not directly innervate the muscles. Two of these muscles responded to different frequency components present in the same input, and as a result each muscle expressed the motor pattern of a different, non-innervating, neural network. In an analogous manner, the distinct dynamics of the multiple intracellular processes that most cells possess may allow each process to respond to, and hence differentiate among, specific frequency ranges present in broad-band input.

摘要

我们描述了三种慢肌,它们对高频神经元输入的低频调制做出反应,因此能够表达神经网络的运动模式,而这些神经网络的神经元并不直接支配这些肌肉。其中两块肌肉对同一输入中存在的不同频率成分做出反应,结果每块肌肉都表达了不同的、非支配性神经网络的运动模式。以类似的方式,大多数细胞所拥有的多个细胞内过程的不同动态可能使每个过程对宽带输入中存在的特定频率范围做出反应,并因此进行区分。

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