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皮层柱方向的估计可改善 MEG 源反演。

Estimates of cortical column orientation improve MEG source inversion.

机构信息

Institut des Sciences Cognitives Marc Jeannerod, CNRS UMR5229, Bron, France; Université Claude Bernard Lyon 1, Université de Lyon, France.

Université Claude Bernard Lyon 1, Université de Lyon, France; Lyon Neuroscience Research Center, CRNL, Brain Dynamics and Cognition Team, INSERM U1028, CNRS UMR5292, Lyon, France.

出版信息

Neuroimage. 2020 Aug 1;216:116862. doi: 10.1016/j.neuroimage.2020.116862. Epub 2020 Apr 16.

DOI:10.1016/j.neuroimage.2020.116862
PMID:32305564
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8417767/
Abstract

Determining the anatomical source of brain activity non-invasively measured from EEG or MEG sensors is challenging. In order to simplify the source localization problem, many techniques introduce the assumption that current sources lie on the cortical surface. Another common assumption is that this current flow is orthogonal to the cortical surface, thereby approximating the orientation of cortical columns. However, it is not clear which cortical surface to use to define the current source locations, and normal vectors computed from a single cortical surface may not be the best approximation to the orientation of cortical columns. We compared three different surface location priors and five different approaches for estimating dipole vector orientation, both in simulations and visual and motor evoked MEG responses. We show that models with source locations on the white matter surface and using methods based on establishing correspondences between white matter and pial cortical surfaces dramatically outperform models with source locations on the pial or combined pial/white surfaces and which use methods based on the geometry of a single cortical surface in fitting evoked visual and motor responses. These methods can be easily implemented and adopted in most M/EEG analysis pipelines, with the potential to significantly improve source localization of evoked responses.

摘要

从 EEG 或 MEG 传感器无创测量的脑活动的解剖源确定具有挑战性。为了简化源定位问题,许多技术引入了电流源位于皮质表面的假设。另一个常见的假设是,这种电流流与皮质表面正交,从而近似于皮质柱的方向。然而,尚不清楚使用哪个皮质表面来定义电流源位置,并且从单个皮质表面计算的法向量可能不是皮质柱方向的最佳逼近。我们在模拟和视觉及运动诱发 MEG 反应中比较了三种不同的表面位置先验和五种不同的估计偶极子矢量方向的方法。我们表明,源位于白质表面的模型和使用基于建立白质与软脑膜皮质表面之间对应关系的方法的模型在拟合视觉和运动诱发反应方面明显优于源位于软脑膜或软脑膜/白质组合表面的模型,以及使用基于单个皮质表面几何形状的方法的模型。这些方法可以很容易地在大多数 M/EEG 分析管道中实现和采用,具有显著改善诱发反应源定位的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/1fb48ebe0216/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/58414527e484/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/6307280d9d18/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/01294ba0d671/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/8cfc7411cf69/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/98b38936fa81/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/4ed77ef315da/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/1fb48ebe0216/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/58414527e484/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/6307280d9d18/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/01294ba0d671/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/8cfc7411cf69/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/98b38936fa81/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/4ed77ef315da/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b258/8417767/1fb48ebe0216/gr7.jpg

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