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首页> 外文期刊>Journal of Neuroscience Methods >Assessing the strength of directed influences among neural signals using renormalized partial directed coherence
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Assessing the strength of directed influences among neural signals using renormalized partial directed coherence

机译：使用重归一化的部分有向相干性评估神经信号中有向影响的强度

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摘要

Partial directed coherence is a powerful tool used to analyze interdependencies in multivariate systems based on vector autoregressive modeling. This frequency domain measure for Granger-causality is designed such that it is normalized to [0,1]. This normalization induces several pitfalls for the inter-pretability of the ordinary partial directed coherence, which will be discussed in some detail in. this paper. In order to avoid these pitfalls, we introduce renormalized partial directed coherence and calculate confidence intervals and significance levels. The performance of this novel concept is illustrated by application to model systems and to electroencephalography and electromyography data from a patient suffering from Parkinsonian tremor
机译：部分有向相干性是用于基于向量自回归建模分析多元系统中相互依赖性的强大工具。设计用于Granger因果关系的频域度量，以使其标准化为[0,1]。这种归一化为普通的部分有向相干的可解释性带来了一些陷阱，本文将对此进行详细讨论。为了避免这些陷阱，我们引入了重新规范化的部分定向相干性，并计算了置信区间和显着性水平。该新颖概念的性能通过应用于模型系统以及帕金森氏病患者的脑电图和肌电图数据得到说明

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