Suppr超能文献

基于MRI的高分辨率脑电图和脑磁图源模型的解剖学限制

Anatomical constraints on source models for high-resolution EEG and MEG derived from MRI.

作者信息

Srinivasan Ramesh

机构信息

Department of Cognitive Sciences, University of California, 3151 SSPA, Irvine, CA 92697-5100, USA.

出版信息

Technol Cancer Res Treat. 2006 Aug;5(4):389-99.

Abstract

Electroencephalography (EEG) remains the primary tool for measuring changes in dynamic brain function due to disease state with the millisecond temporal resolution of neuronal activity. In recent decades EEG has been supplanted by CT and MRI for the localization of tumors and lesions in the brain. In contrast to the excellent temporal resolution of EEG, the spatial information in EEG is limited by the volume conduction of currents through the tissues of the head. We have extracted source models (position and orientation) from MRI scans to investigate the theoretical relationship between brain sources and EEG recorded on the scalp. Although detailed information about the boundaries between different tissues can also be obtained from MRI, these models are only approximate because of our relatively poor knowledge of the conductivities of the different tissue compartments in living heads. We also compare the resolution of EEG with magnetoecephalography (MEG), which offers the advantage of requiring less detail about volume conduction in the head. The brain's magnetic field depends only on the position of sources in the brain and the position and orientation of the sensors. We demonstrate that EEG and MEG space average neural activity over comparably large volumes of the brain; however, they are preferentially sensitive to sources of different orientation suggesting a complementary role for EEG and MEG. High-resolution EEG methods potentially yield much better localization of source activity in superficial brain areas. These methods do not make any assumptions about the sources, and can be easily co-registered with the brain surface derived from MRI. While there is much information to be gained by using anatomical MRI to develop models of the generators of EEG/MEG, functional neuroimaging (e.g., fMRI) signals and EEG/MEG signals are not easily related.

摘要

脑电图(EEG)仍然是测量由于疾病状态导致的动态脑功能变化的主要工具,具有神经元活动的毫秒级时间分辨率。在最近几十年中,用于脑部肿瘤和病变定位的CT和MRI已经取代了EEG。与EEG出色的时间分辨率相比,EEG中的空间信息受电流通过头部组织的容积传导限制。我们已从MRI扫描中提取源模型(位置和方向),以研究脑源与头皮记录的EEG之间的理论关系。虽然也可以从MRI获得有关不同组织之间边界的详细信息,但由于我们对活体头部不同组织隔室电导率的了解相对较少,这些模型只是近似的。我们还将EEG的分辨率与脑磁图(MEG)进行了比较,MEG的优势在于对头部容积传导的细节要求较低。脑磁场仅取决于脑中源的位置以及传感器的位置和方向。我们证明,EEG和MEG对相当大的脑容积内的神经活动进行空间平均;然而,它们对不同方向的源具有优先敏感性,这表明EEG和MEG具有互补作用。高分辨率EEG方法有可能在浅表脑区中对源活动进行更好的定位。这些方法不对源做任何假设,并且可以很容易地与从MRI得出的脑表面进行配准。虽然使用解剖学MRI来开发EEG/MEG发生器模型可以获得很多信息,但功能神经成像(例如fMRI)信号和EEG/MEG信号之间不容易建立联系。

相似文献

2
EEG and MEG coherence: measures of functional connectivity at distinct spatial scales of neocortical dynamics.
J Neurosci Methods. 2007 Oct 15;166(1):41-52. doi: 10.1016/j.jneumeth.2007.06.026. Epub 2007 Jul 6.
3
The advantage of combining MEG and EEG: comparison to fMRI in focally stimulated visual cortex.
Neuroimage. 2007 Jul 15;36(4):1225-35. doi: 10.1016/j.neuroimage.2007.03.066. Epub 2007 Apr 19.
7
Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.
Neuroimage. 2015 Mar;108:328-42. doi: 10.1016/j.neuroimage.2014.12.040. Epub 2014 Dec 23.
8
High-resolution EEG (HR-EEG) and magnetoencephalography (MEG).
Neurophysiol Clin. 2015 Mar;45(1):105-11. doi: 10.1016/j.neucli.2014.11.011. Epub 2015 Jan 14.
10
Geometrical interpretation of fMRI-guided MEG/EEG inverse estimates.
Neuroimage. 2004 May;22(1):323-32. doi: 10.1016/j.neuroimage.2003.12.044.

引用本文的文献

1
Spurious correlations in surface-based functional brain imaging.
Imaging Neurosci (Camb). 2025 Feb 18;3. doi: 10.1162/imag_a_00478. eCollection 2025.
2
Spurious correlations in surface-based functional brain imaging.
bioRxiv. 2024 Jul 14:2024.07.09.602799. doi: 10.1101/2024.07.09.602799.
4
Assessment of Effective Network Connectivity among MEG None Contaminated Epileptic Transitory Events.
Comput Math Methods Med. 2021 Dec 28;2021:6406362. doi: 10.1155/2021/6406362. eCollection 2021.
5
Screening Tools and Assessment Methods of Cognitive Decline Associated With Age-Related Hearing Loss: A Review.
Front Aging Neurosci. 2021 Jul 14;13:677090. doi: 10.3389/fnagi.2021.677090. eCollection 2021.
6
Recent advances in the effects of microwave radiation on brains.
Mil Med Res. 2017 Sep 21;4(1):29. doi: 10.1186/s40779-017-0139-0.

本文引用的文献

1
Functional localization of brain sources using EEG and/or MEG data: volume conductor and source models.
Magn Reson Imaging. 2004 Dec;22(10):1533-8. doi: 10.1016/j.mri.2004.10.010.
2
Measurement of the conductivity of skull, temporarily removed during epilepsy surgery.
Brain Topogr. 2003 Fall;16(1):29-38. doi: 10.1023/a:1025606415858.
3
How can EEG/MEG and fMRI/PET data be combined?
Hum Brain Mapp. 2002 Sep;17(1):1-3. doi: 10.1002/hbm.10057.
4
Localizing acute stroke-related EEG changes: assessing the effects of spatial undersampling.
J Clin Neurophysiol. 2001 Jul;18(4):302-17. doi: 10.1097/00004691-200107000-00002.
6
Gating of human theta oscillations by a working memory task.
J Neurosci. 2001 May 1;21(9):3175-83. doi: 10.1523/JNEUROSCI.21-09-03175.2001.
7
Toward a quantitative description of large-scale neocortical dynamic function and EEG.
Behav Brain Sci. 2000 Jun;23(3):371-98; discussion 399-437. doi: 10.1017/s0140525x00003253.
9
The conductivity of the human skull: results of in vivo and in vitro measurements.
IEEE Trans Biomed Eng. 2000 Nov;47(11):1487-92. doi: 10.1109/TBME.2000.880100.
10
Conductivities of three-layer human skull.
Brain Topogr. 2000 Fall;13(1):29-42. doi: 10.1023/a:1007882102297.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验