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通过多变量自回归处理对自发和诱发脑电图进行全相干和部分相干分析。

Total and partial coherence analysis of spontaneous and evoked EEG by means of multi-variable autoregressive processing.

作者信息

Liberati D, Cursi M, Locatelli T, Comi G, Cerutti S

机构信息

Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy.

出版信息

Med Biol Eng Comput. 1997 Mar;35(2):124-30. doi: 10.1007/BF02534142.

DOI:10.1007/BF02534142
PMID:9136205
Abstract

The joint use of total and partial coherence between pairs of EEGs simultaneously recorded in a standard set, is shown to enhance what is caused by direct correlation between cortical subsystems and what is instead related to the spread of the electromagnetic field. A multi-variable autoregressive approach is employed in the computation, giving results even for a very short time window, thus allowing coherence to be investigated at the main cortical latencies of evoked potentials. In particular, when a combined visual and somatosensory stimulation is applied, cortical interactions are captured in the frequency domain.

摘要

同时记录在标准集合中的成对脑电图之间的总相干性和部分相干性的联合使用,被证明可以增强皮质子系统之间直接相关性所导致的结果以及与电磁场传播相关的结果。在计算中采用了多变量自回归方法,即使在非常短的时间窗口内也能给出结果,从而能够在诱发电位的主要皮质潜伏期研究相干性。特别是,当施加视觉和体感联合刺激时,在频域中捕捉到皮质相互作用。

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本文引用的文献

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Spectral and cross-spectral analysis of heart rate and arterial blood pressure variability signals.心率与动脉血压变异性信号的频谱及互谱分析
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