Regional Brain Activity Estimation from M/EEG Data

多模式功能神经影像学的持续发展为基础系统神经科学、临床神经病学和神经精神病学的新研究领域提供了动力。主要的方式，功能性磁共振成像（fMRI），这是基于活动相关的血流动力学变化的测量，还没有达到快速神经电活动成像所需的毫秒分辨率。磁和脑电图（M/EEG）可以实现这种时间分辨率，虽然具有不确定和可变的空间分辨率。我们的目标是估计快速的神经电活动在大脑区域的利益（ROI）从M/EEG，使用一个阈值的基础上校准的信号的可辨别性和空间分辨率特性。ROI可以从结构或功能MRI数据获得。我们描述了一种新的方法，区域活动估计（REGAE），这与现有的M/EEG源分析方法有很大不同。REGAE优化和校准ROI信号可分辨性和空间分辨率之间的理论权衡。这些校准曲线允许用户针对指定的决策标准微调ROI信号检测器。这项工作的目的是：（a）实施区域地球观测和分析系统原型软件，（B）系统地说明影响区域地球观测和分析系统可分辨性和分辨率的因素，包括传感器配置、信噪比和感兴趣区域的位置，（c）将区域地球观测和分析系统与现有的商用电磁监测系统成套软件（http：//www.sourcesignal.com/sw-desc.htm）结合起来。拟定商业应用：我们提出的软件和方法是对现有EEG、MEG和MRI系统的非侵入性、非放射性和相对低成本的补充，并且提供了目前无法独立地从这些系统获得的信息。由此产生的软件将直接应用于临床和认知神经科学研究。如果临床价值得到证明，基于这种方法的系统可能会在精神病学，神经病学和心理学领域找到应用。

Ongoing development of multimodal functional neuroimaging has been fueling productive new lines of research, in basic systems neuroscience, clinical neurology and neuropsychiatry. The dominant modality, functional Magnetic Resonance Imaging (fMRI), which is based on the measurement of activity-related hemodynamic changes, has not attained the millisecond resolution required for imaging of fast neuroelectric activity. Magneto- and electro-encephalography (M/EEG) can achieve this temporal resolution, although with uncertain and variable spatial resolution. Our objective is to estimate fast neuroelectric activity in brain regions of interest (ROIs) from M/EEG, using a threshold based on calibrated signal discriminability and spatial resolution characteristics. ROIs may be obtained from structural or functional MRI data. We describe a new method, REGional Activity Estimation (REGAE), that differs substantially from existing methods of M/EEG source analysis. REGAE optimizes and calibrates the theoretical tradeoff between ROI signal discriminability and spatial resolution. These calibration curves permit the user to fine-tune a ROI signal detector for a specified decision criterion. The aims of this work are: (a) to implement REGAE prototype software, (b) to systematically characterize factors that influence REGAE discriminability and resolution, including sensor configuration, signal-to-noise ratio, and ROI location, and (c) to integrate REGAE with existing commercial EMSE Suite software (http://www.sourcesignal.com/sw-desc.htm). PROPOSED COMMERCIAL APPLICATION: The software and methods that we propose are non-invasive, non- radiological and relatively low cost addition to existing EEG, MEG and MRI systems, and provide information that is not currently available from these systems independently. The resulting software will have direct application in clinical and cognitive neuroscience research. If clinical value is demonstrated, systems based on this methodology may find applications in the areas of psychiatry, neurology and psychology.