Parametric Brain Imaging via Modeling and Analysis of Electroencephalographic Signals

脑功能和生理参数将通过其对脑电图（EEG）信号的影响进行高时间分辨率的空间成像，这是一种现有方法无法实现的成像形式。这将通过改进现有的基于生理学的脑电图生成模型和开发基于模型预测拟合到多电极脑电图数据的分析工具来实现。研究结果将用于探索正常受试者脑电图的时空特征，以探索潜在的基本机制，并推断具有实际意义的新参数变化。

Parameters of brain function and physiology will be spatially imaged with high time resolution via their effects on electroencephalographic (EEG) signals, a form of imaging that is impossible with existing methods. This will be achieved by improving existing physiologically-based models of the generation of EEGs and developing analysis tools based on fitting of model predictions to multielectrode EEG data. The results will be used to probe spatiotemporal features of EEGs in normal subjects to explore the underlying fundamental mechanisms and to infer novel parameter variations of practical relevance.