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人脑 EEG 后 alpha 节律的精细结构:频率成分、皮质源及其时间行为。

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

机构信息

Laboratoire de recherche en neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Leenaards Memory Centre and Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland.

出版信息

Sci Rep. 2017 Aug 15;7(1):8249. doi: 10.1038/s41598-017-08421-z.

DOI:10.1038/s41598-017-08421-z
PMID:28811538
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5557761/
Abstract

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.

摘要

后部 alpha 节律(AR)的异质性是一个被广泛假设但很少被测试的现象。我们使用 3 向 PARAFAC 技术在皮质源空间中分解后部 AR,考虑到中密度 EEG 的空间、频率和时间方面。我们在 29 名健康成年人的一组中发现了 90%的多分量 AR 结构。典型的静息状态结构由 AR 的高频顶枕部成分(ARC1)和低频枕颞部成分(ARC2)组成,其特征是时间上的个体动态。在少数情况下,我们发现了 3 分量结构,其中有两个 ARC1 和一个 ARC2。AR 结构在数周到数月的时间内其频率和空间特征稳定,因此代表个体的 EEG alpha 表型。皮质拓扑、个体稳定性和与灵长类动物 AR 组织的相似性将 ARC1 与背侧视觉流联系起来,将 ARC2 与腹侧视觉流联系起来。了解有多少种和什么样的后部 AR 成分对 EEG 有贡献,对于临床神经科学来说是至关重要的,因为这是 AR 分割的客观基础,也是在各种正常和病理条件下解释 AR 动力学的基础,这些条件可以选择性地影响个别成分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/ed8d878ef194/41598_2017_8421_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/5842504ae95f/41598_2017_8421_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/26eb70e45987/41598_2017_8421_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/494a90431a15/41598_2017_8421_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/444ab38c68e8/41598_2017_8421_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/ed8d878ef194/41598_2017_8421_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/5842504ae95f/41598_2017_8421_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/26eb70e45987/41598_2017_8421_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/494a90431a15/41598_2017_8421_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/444ab38c68e8/41598_2017_8421_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2dc/5557761/ed8d878ef194/41598_2017_8421_Fig5_HTML.jpg

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