Synchrony in neuromagnetic oscillations as an indicator for coordination of brain activity underlying cognitive processes

认知涉及多个大脑区域以及这些区域之间的活动协调，以实现成功的功能。一种假设是，精确的时间对协调起着至关重要的作用。之前使用电极记录动物大脑中的神经活动的工作表明，不同节律下的神经振荡关系表明大脑区域之间的协调。在人类中，我们使用脑磁图(MEG)非侵入性地记录头部外的相关神经磁信号。使用数学方法解决“逆问题”，我们可以估计大脑活动产生的来源在大脑皮层。在这个研究项目中，我们正在研究两个或多个遥远的皮层来源的大脑活动之间的同步性。震源分析的逆解可能会影响观测到的同步度。因此，我们将进行模拟研究，以了解我们的方法的性质，并提高灵敏度。除了具有相同节奏的振荡同步之外，另一个重要的原理是不同频率的大脑节奏相互作用。已经发现，在记忆任务中，海马体中的高频振荡专门发生在低频振荡的特定阶段。我们将开发新的信号处理方法来检测不同节律的大脑活动之间的这种相互作用和协调。我们将应用新的大脑研究方法来研究认知功能如何随着年龄的变化而变化。一个目标是在最早阶段预测像阿尔茨海默氏症这样的疾病，以便通过早期干预推迟疾病的发病。我们将使用我们的脑成像方法来监测康复训练的结果。这对改善康复计划很重要。行为测量往往不够敏感，无法区分真正的学习效果和补偿机制。此外，我们还将更多地了解大脑振荡在认知过程中的作用。

Cognition involves multiple brain areas and coordination of activity between these areas for successful function. One hypothesis is that precise timing plays a crucial role for coordination. Previous work using recording of neural activity with electrodes in the animal brain suggested that the relations of neural oscillations at various rhythms indicate coordination between brain areas. In humans we record related neuromagnetic signals noninvasively outside of the head with magnetoencephalography (MEG). Using mathematical methods for solving the 'inverse problem', we can estimate the brain activity generated at sources within the cortex. In this research program we are studying the synchrony between brain activity in two or more distant cortical sources. The inverse solution for source analysis may affect the observed synchrony measures. Therefore we will perform simulation studies to learn about the properties of our methods and to improve the sensitivity. In addition to synchrony of oscillations with the same rhythm another important principle is that brain rhythm at different frequencies interact with each other. It has been found that during a memory task, high frequency oscillations in the hippocampus occurred specifically at a certain phase of low frequency oscillations. We will develop new signal processing methods for detecting such interactions and coordinations between brain activities at different rhythms. We will apply the new brain research methods for studying how cognitive function changes with aging. One goal is to predict diseases like Alzheimer's at earliest stage in order to delay the onset of the disease through early intervention. We will use our brain imaging methods for monitoring the outcome of rehabilitation training. This is important for improving the rehabilitation programs. Behavioural measures are often not sensitive enough for differentiating between true learning effects and compensatory mechanisms. Moreover we will learn more about the role of brain oscillations for cognitive processes.