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）信号的影响以高时间分辨率进行空间成像，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EEG生成模型和开发基于模型预测与多电极EEG数据拟合的分析工具来实现。 结果将被用来探测正常受试者的EEG的时空特征，探索潜在的基本机制，并推断新的参数变化的实际意义。

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.