Structural templates for imaging EEG cortical sources in infants.

Structural templates for imaging EEG cortical sources in infants.
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DOI:
10.1016/j.neuroimage.2020.117682
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发表时间:
2021-02-15
期刊:
影响因子:
5.7
通讯作者:
Elsabbagh M
Elsabbagh M
中科院分区:
医学1区
文献类型:
--
作者:
O'Reilly C;Larson E;Richards JE;Elsabbagh M

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脑电图(EEG)源重建是一种强大的方法,允许解剖定位的电生理大脑活动。用于估计皮质源的算法需要头部和大脑的解剖模型,通常使用磁共振成像(MRI)重建。当这样的扫描不可用时,群体平均值可以用于成人,但没有平均表面模板可用于婴儿的皮质源成像。为了解决这个问题,我们介绍了一个新的系列的13个解剖模型之间的零和24个月的年龄。这些模板是根据MRI平均值和头部组织的边界元法(BEM)分割构建的,可作为神经发育MRI数据库的一部分。使用Infant FreeSurfer管道估计分离软脑膜、灰质和白色物质的表面。皮肤的表面以及外和内颅骨表面使用立方体行进算法提取,然后进行拉普拉斯平滑和网格抽取。我们对这些网格进行了后处理,以纠正拓扑错误并确保网格不漏水。使用100个7个月大的婴儿的高密度EEG记录,这些模板的源重建证明和验证。希望这些模板将支持健康婴儿以及临床儿科人群中基于EEG的神经成像和功能连接的未来研究。
Electroencephalographic (EEG) source reconstruction is a powerful approach that allows anatomical localization of electrophysiological brain activity. Algorithms used to estimate cortical sources require an anatomical model of the head and the brain, generally reconstructed using magnetic resonance imaging (MRI). When such scans are unavailable, a population average can be used for adults, but no average surface template is available for cortical source imaging in infants. To address this issue, we introduce a new series of 13 anatomical models for subjects between zero and 24 months of age. These templates are built from MRI averages and boundary element method (BEM) segmentation of head tissues available as part of the Neurodevelopmental MRI Database. Surfaces separating the pia mater, the gray matter, and the white matter were estimated using the Infant FreeSurfer pipeline. The surface of the skin as well as the outer and inner skull surfaces were extracted using a cube marching algorithm followed by Laplacian smoothing and mesh decimation. We post-processed these meshes to correct topological errors and ensure watertight meshes. Source reconstruction with these templates is demonstrated and validated using 100 high-density EEG recordings from 7-month-old infants. Hopefully, these templates will support future studies on EEG-based neuroimaging and functional connectivity in healthy infants as well as in clinical pediatric populations.
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