Fine Structure of Posterior Alpha Rhythm in Human EEG: Frequency Components, Their Cortical Sources, and Temporal Behavior.

Fine Structure of Posterior Alpha Rhythm in Human EEG: Frequency Components, Their Cortical Sources, and Temporal Behavior.
复制标题

DOI:
10.1038/s41598-017-08421-z
复制
发表时间:
2017-08-15
期刊:
影响因子:
4.6
通讯作者:
Knyazeva MG
Knyazeva MG
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Barzegaran E;Vildavski VY;Knyazeva MG

文献摘要

参考文献

被引文献

相似文献

后α节律(AR)的异质性是一种广泛假设但很少测试的现象。我们分解后AR的皮质源空间与3路PARAFAC技术,考虑到空间,频率和时间方面的中密度EEG。我们发现一组29名健康成人中90%的多组分AR结构。典型的静息态结构由AR的高频枕顶成分(ARC 1)和低频枕颞成分(ARC 2)组成,其特征在于个体在时间上的动态变化。在少数情况下,我们发现了一个三组分结构,有两个ARC 1和一个ARC 2。AR结构的频率和空间特征在数周至数月内保持稳定,因此代表了个体EEG α表型。皮质地形,个人的稳定性,以及灵长类动物AR组织的相似性,将ARC 1与背侧视觉流联系起来,ARC 2与腹侧视觉流联系起来。了解有多少和什么样的后AR组件有助于EEG是必不可少的临床神经科学的客观基础AR分割和解释AR动态在各种条件下,正常和病理,这可以选择性地影响个别组件。
Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon. We decomposed the posterior AR in the cortical source space with a 3-way PARAFAC technique, taking into account the spatial, frequency, and temporal aspects of mid-density EEG. We found a multicomponent AR structure in 90% of a group of 29 healthy adults. The typical resting-state structure consisted of a high-frequency occipito-parietal component of the AR (ARC1) and a low-frequency occipito-temporal component (ARC2), characterized by individual dynamics in time. In a few cases, we found a 3-component structure, with two ARC1s and one ARC2. The AR structures were stable in their frequency and spatial features over weeks to months, thus representing individual EEG alpha phenotypes. Cortical topography, individual stability, and similarity to the primate AR organization link ARC1 to the dorsal visual stream and ARC2 to the ventral one. Understanding how many and what kind of posterior AR components contribute to the EEG is essential for clinical neuroscience as an objective basis for AR segmentation and for interpreting AR dynamics under various conditions, both normal and pathological, which can selectively affect individual components.
DOI: 10.1016/s0169-7439(00)00071-x
发表时间: 2000-08-14
影响因子: 3.9
作者:
Andersson, CA;Bro, R
通讯作者: Bro, R
DOI: 10.1016/s1388-2457(00)00526-5
发表时间: 2001-02-01
影响因子: 4.7
作者:
de Jongh, A;de Munck, JC;van Dijk, BW
通讯作者: van Dijk, BW
DOI: 10.1016/j.mri.2004.10.010
发表时间: 2004-12-01
影响因子: 2.5
作者:
da Silva, FL
通讯作者: da Silva, FL
DOI: 10.1016/j.neurobiolaging.2014.09.011
发表时间: 2015-02
影响因子: 4.2
作者:
Babiloni C;Del Percio C;Boccardi M;Lizio R;Lopez S;Carducci F;Marzano N;Soricelli A;Ferri R;Triggiani AI;Prestia A;Salinari S;Rasser PE;Basar E;Famà F;Nobili F;Yener G;Emek-Savaş DD;Gesualdo L;Mundi C;Thompson PM;Rossini PM;Frisoni GB
通讯作者: Frisoni GB
DOI: 10.1016/j.tics.2012.10.007
发表时间: 2012-12
影响因子: 19.9
作者:
Klimesch, Wolfgang
通讯作者: Klimesch, Wolfgang