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探究适应过程中神经交互的变化。

Probing changes in neural interaction during adaptation.

作者信息

Zhu Liqiang, Lai Ying-Cheng, Hoppensteadt Frank C, He Jiping

机构信息

Department of Electrical Engineering, Center for Systems Science and Engineering Research, Arizona State University, Tempe, Arizona 85287, USA.

出版信息

Neural Comput. 2003 Oct;15(10):2359-77. doi: 10.1162/089976603322362392.

Abstract

A procedure is developed to probe the changes in the functional interactions among neurons in primary motor cortex of the monkey brain during adaptation. A monkey is trained to learn a new skill, moving its arm to reach a target under the influence of external perturbations. The spike trains of multiple neurons in the primary motor cortex are recorded simultaneously. We utilize the methodology of directed transfer function, derived from a class of linear stochastic models, to quantify the causal interactions between the neurons. We find that the coupling between the motor neurons tends to increase during the adaptation but return to the original level after the adaptation. Furthermore, there is evidence that adaptation tends to affect the topology of the neural network, despite the approximate conservation of the average coupling strength in the network before and after the adaptation.

摘要

开发了一种程序,用于探究猴子大脑初级运动皮层中神经元之间的功能相互作用在适应过程中的变化。训练一只猴子学习一项新技能,即在外部扰动的影响下移动其手臂以到达目标。同时记录初级运动皮层中多个神经元的尖峰序列。我们利用从一类线性随机模型推导出来的定向传递函数方法,来量化神经元之间的因果相互作用。我们发现,运动神经元之间的耦合在适应过程中趋于增加,但在适应后恢复到原始水平。此外,有证据表明,尽管适应前后网络中的平均耦合强度大致保持不变,但适应往往会影响神经网络的拓扑结构。

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