颅内立体脑电图测量的分布式源建模。

Distributed source modeling of intracranial stereoelectro-encephalographic measurements.

机构信息

Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.

Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada.

出版信息

Neuroimage. 2021 Apr 15;230:117746. doi: 10.1016/j.neuroimage.2021.117746. Epub 2021 Jan 14.

Abstract

Intracranial stereoelectroencephalography (sEEG) provides unsurpassed sensitivity and specificity for human neurophysiology. However, functional mapping of brain functions has been limited because the implantations have sparse coverage and differ greatly across individuals. Here, we developed a distributed, anatomically realistic sEEG source-modeling approach for within- and between-subject analyses. In addition to intracranial event-related potentials (iERP), we estimated the sources of high broadband gamma activity (HBBG), a putative correlate of local neural firing. Our novel approach accounted for a significant portion of the variance of the sEEG measurements in leave-one-out cross-validation. After logarithmic transformations, the sensitivity and signal-to-noise ratio were linearly inversely related to the minimal distance between the brain location and electrode contacts (slope≈-3.6). The signa-to-noise ratio and sensitivity in the thalamus and brain stem were comparable to those locations at the vicinity of electrode contact implantation. The HGGB source estimates were remarkably consistent with analyses of intracranial-contact data. In conclusion, distributed sEEG source modeling provides a powerful neuroimaging tool, which facilitates anatomically-normalized functional mapping of human brain using both iERP and HBBG data.

摘要

颅内立体脑电图(sEEG)为人类神经生理学提供了无与伦比的灵敏度和特异性。然而,由于植入物的覆盖稀疏且个体差异很大,因此脑功能的功能映射一直受到限制。在这里,我们开发了一种分布式、解剖逼真的 sEEG 源建模方法,用于进行个体内和个体间的分析。除了颅内事件相关电位(iERP),我们还估计了高宽带伽马活动(HBBG)的源,这是局部神经放电的一个潜在相关物。我们的新方法在留一交叉验证中解释了 sEEG 测量的很大一部分方差。对数转换后,灵敏度和信噪比与大脑位置和电极接触之间的最小距离呈线性反比关系(斜率≈-3.6)。丘脑和脑干的信噪比和灵敏度与电极接触植入附近位置的信噪比和灵敏度相当。HGGB 源估计与颅内接触数据的分析非常一致。总之,分布式 sEEG 源建模提供了一种强大的神经影像学工具,使用 iERP 和 HBBG 数据促进了人脑的解剖标准化功能映射。

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