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.
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。
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