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首页> 美国卫生研究院文献>Proceedings of the National Academy of Sciences of the United States of America >Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations
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Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations

机译：使用功能性MRI约束的脑磁图数据对人脑活动的时空成像：蒙特卡洛模拟

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The goal of our research is to develop an experimental and analytical framework for spatiotemporal imaging of human brain function. Preliminary studies suggest that noninvasive spatiotemporal maps of cerebral activity can be produced by combining the high spatial resolution (millimeters) of functional MRI (fMRI) with the high temporal resolution (milliseconds) of electroencephalography (EEG) and magnetoencephalography (MEG). Although MEG and EEG are sensitive to millisecond changes in mental activity, the ability to resolve source localization and timing is limited by the ill-posed “inverse” problem. We conducted Monte Carlo simulations to evaluate the use of MRI constraints in a linear estimation inverse procedure, where fMRI weighting, cortical location and orientation, and sensor noise statistics were realistically incorporated. An error metric was computed to quantify the effects of fMRI invisible (“missing”) sources, “extra” fMRI sources, and cortical orientation errors. Our simulation results demonstrate that prior anatomical and functional information from MRI can be used to regularize the EEG/MEG inverse problem, giving an improved solution with high spatial and temporal resolution. An fMRI weighting of approximately 90% was determined to provide the best compromise between separation of activity from correctly localized sources and minimization of error caused by missing sources. The accuracy of the estimate was relatively independent of the number and extent of the sources, allowing for incorporation of physiologically realistic multiple distributed sources. This linear estimation method provides an operator-independent approach for combining information from fMRI, MEG, and EEG and represents a significant advance over traditional dipole modeling.
机译：我们研究的目的是为人脑功能的时空成像开发实验和分析框架。初步研究表明，可以通过将功能性MRI（fMRI）的高空间分辨率（mm）与脑电图（EEG）和磁脑电图（MEG）的高时间分辨率（毫秒）相结合来制作非侵入性的大脑活动时空图。尽管MEG和EEG对心理活动的毫秒变化很敏感，但解决不适的“逆”问题限制了分辨源位置和时间的能力。我们进行了蒙特卡洛模拟，以评估线性估计逆过程中MRI约束的使用，在该过程中，fMRI权重，皮质位置和方向以及传感器噪声统计被切实地纳入其中。计算了误差度量以量化功能磁共振成像不可见（“缺失”）源，“额外”功能磁共振成像源和皮质方向误差的影响。我们的仿真结果表明，来自MRI的先前解剖和功能信息可用于规范化EEG / MEG反问题，从而提供具有高时空分辨率的改进解决方案。确定了约90％的fMRI权重，以在将活动与正确定位的源分离以及最小化由丢失源引起的错误之间取得最佳折衷。估计的准确性相对独立于来源的数量和程度，从而可以纳入生理上现实的多个分布式来源。这种线性估计方法提供了一种独立于操作员的方法，用于组合来自fMRI，MEG和EEG的信息，与传统的偶极子建模相比，它具有显着的进步。

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