New approaches to the analysis of coordinated neuromagnetic source activity

从历史上看，神经科学家研究了大脑的哪个区域参与了感知，认知的特定功能。然而，一般来说，当我们说话、思考或移动时，整个大脑都在工作。因此，目前的研究集中在大脑区域是如何连接的。在脑电图（EEG）中，我们可以通过连接到头皮上的多个电极来无创地测量大脑活动，在脑磁图（MEG）中，我们可以在头部周围布置许多磁场传感器。我们比较两个电极或MEG传感器的信号，并寻找具有共同节律的振荡。我们的假设是，在两个传感器的同步振荡表明，潜在的神经群体相互作用。利用脑磁图，我们可以定位神经活动，并将同步性分析应用于神经磁源活动。结果表明，与传感器数据分析相比，大脑区域的功能连接精度要高得多。MEG源分析并不总是完美的，并且皮质源不能完全分离，特别是如果它们位于附近。由于这种限制，源信号可能表现出明显的同步性，这与功能连接无关。为了克服虚假同步的影响，我们将开发一系列的数据分析技术，这表明真正的功能协调和传播源活动的影响不敏感。从模拟研究中，我们将了解MEG源数据中同步测量的属性。我们将在感知和认知的研究中分析MEG数据。对于所有的研究，我们都提出了一个关于功能相关的大脑活动的可靠假设。基于源信号的生理特性，我们设计了我们的分析策略。具体来说，我们将采用同步的时间变化，相干性的虚部，大脑活动的频谱分量之间的同步性，相位重置的统计，刺激引起的振荡的变化，以及来自非线性动力学的测量，这些测量不受源分析限制的影响。研究结果将允许在基础研究和临床诊断中进行新的和改进的应用。

Historically, neuroscientists investigated which brain area is involved in specific functions of perception, cognition. However, generally the whole brain is engaged when we speak, think, or move. Thus current research focuses on how brain areas are connected. We can measure brain activity noninvasively with multiple electrodes attached to the scalp in electroencephalography (EEG) and many magnetic field sensors arranged around the head in magnetoencephalography (MEG). We compare the signals at two electrodes or MEG sensors and search for oscillations with common rhythms. Our hypothesis is that synchronous oscillation at two sensors indicates that the underlying neural populations interact with each other. With MEG we can localize the neural activity and apply the analysis of synchrony to neuromagnetic source activity. The results indicate with much higher precision, which brain areas are functional connected than the analysis of sensor data can provide. MEG source analysis is not always perfect, and the cortical sources cannot be separated entirely, specifically if they are located in close vicinity. Because of such limitation, the source signals may show apparent synchrony, which is not related to functional connectivity. To overcome the effects of spurious synchrony, we will develop a series of data analysis techniques, which indicate true functional coordination and are insensitive to effects of spreading source activity. From simulation studies we will learn about the properties of synchrony measures in MEG source data. We will analyze MEG data in studies of perception and cognition. For all studies we develop a solid hypothesis about the functionally relevant brain activity. Based on the physiological properties of the source signals we design our analysis strategy. Specifically we will employ measures like temporal changes in synchrony, the imaginary part of coherence, synchrony between spectral components of the brain activity, statistics of phase resets, changes in stimulus-induced oscillations, and measures from nonlinear dynamics, which are not affected by limitations in the source analysis. The results will allow new and improved applications in basic research and clinical diagnostics.