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Estimating coupling direction between neuronal populations with permutation conditional mutual information.用置换条件互信息估计神经元群体之间的耦合方向。
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Application of Matched-Filtering to Extract EEG Features and Decouple Signal Contributions from Multiple Seizure Foci in Brain Malformations.匹配滤波在提取脑电图特征及解耦脑畸形中多个癫痫病灶信号贡献方面的应用
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Phase/amplitude reset and theta-gamma interaction in the human medial temporal lobe during a continuous word recognition memory task.在连续单词识别记忆任务期间,人类内侧颞叶中的相位/幅度重置及theta-γ相互作用。
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Kulback-Leibler and renormalized entropies: applications to electroencephalograms of epilepsy patients.库尔贝克-莱布勒散度与重归一化熵:在癫痫患者脑电图中的应用
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癫痫中用于网络特征描述的多尺度信息。

Multiscale information for network characterization in epilepsy.

作者信息

Stamoulis Catherine, Chang Bernard S

机构信息

Departments of Neurology and Radiology and the Clinical Research Program, Children’s Hospital Boston and Harvard Medical School, Boston, MA 02115, USA.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5908-11. doi: 10.1109/IEMBS.2011.6091461.

DOI:10.1109/IEMBS.2011.6091461
PMID:22255684
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3261516/
Abstract

We have developed a multiscale approach for the estimation of neuronal network coordination in the epileptic brain, from continuous (long-term) non-invasive electroencephalograms (EEG). The proposed approach specifically assesses the effect of large-scale network behavior on local network coordination, at individual dominant frequencies (modes) of the EEG spectrum. For this purpose a set of conditional information parameters is proposed to explicitly quantify the effect of global network correlation in the brain on pairwise (local) mutual information, via conditioning. These parameters are shown to be modulated in a frequency-specific manner at baseline, as well as during seizure evolution.

摘要

我们已经开发出一种多尺度方法,用于从连续(长期)无创脑电图(EEG)估计癫痫大脑中的神经网络协调性。所提出的方法专门在EEG频谱的各个主导频率(模式)下,评估大规模网络行为对局部网络协调性的影响。为此,提出了一组条件信息参数,以通过条件作用明确量化大脑中全局网络相关性对成对(局部)互信息的影响。这些参数在基线以及癫痫发作演变过程中以频率特异性方式受到调制。