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和这些区域之间的活动协调，以实现成功的功能。一种假设是，精确的时间安排对协调起着至关重要的作用。先前的工作使用电极记录动物大脑中的神经活动，表明不同节奏的神经振荡关系表明大脑区域之间的协调。在人类中，我们用脑磁图（MEG）在头部外部非侵入性地记录相关的神经磁信号。使用数学方法来解决“逆问题”，我们可以估计大脑皮层内产生的大脑活动。在这项研究计划中，我们正在研究两个或两个以上远距离皮层来源的大脑活动之间的同步性。源分析的逆解可能会影响所观察到的同步措施。因此，我们将进行模拟研究，以了解我们的方法的属性，并提高灵敏度。除了具有相同节奏的振荡的同步性之外，另一个重要的原则是不同频率的大脑节奏彼此相互作用。已经发现，在记忆任务期间，海马体中的高频振荡具体地发生在低频振荡的某个阶段。我们将开发新的信号处理方法，用于检测不同节奏的大脑活动之间的相互作用和协调。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增长而变化。一个目标是在早期阶段预测阿尔茨海默氏症等疾病，以便通过早期干预延迟疾病的发作。我们将使用我们的大脑成像方法来监测康复训练的结果。这对改善康复方案至关重要。行为措施往往不够敏感，无法区分真正的学习效果和补偿机制。此外，我们将了解更多关于脑振荡对认知过程的作用。

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.