Regional Brain Activity Estimation from M/EEG Data

根据 M/EEG 数据估计区域大脑活动

• 批准号: 6403941
• 负责人: Mark E Pflieger
• 金额: $ 10万
• 依托单位: SOURCE SIGNAL IMAGING, INC.
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-25 至 2002-03-24
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6403941
• 关键词: bioimaging /biomedical imaging; brain disorder diagnosis; brain electrical activity; brain imaging /visualization /scanning; brain mapping; computer assisted diagnosis; computer data analysis; computer program /software; diagnosis design /evaluation; diagnosis quality /standard; electroencephalography; functional magnetic resonance imaging; human data; magnetoencephalography; noninvasive diagnosis

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.

多模式功能神经成像的不断发展推动了基础系统神经科学、临床神经学和神经精神病学领域富有成效的新研究方向的发展。基于活动相关血流动力学变化测量的主要方式是功能磁共振成像(FMRI)，它还没有达到快速神经电活动成像所需的毫秒分辨率。虽然具有不确定和可变的空间分辨率，但磁/脑电信号(M/EEG)可以达到这种时间分辨率。我们的目标是使用基于校准的信号分辨率和空间分辨率特征的阈值来估计M/EEG中大脑感兴趣区(ROI)的快速神经电活动。感兴趣区可从结构或功能磁共振数据中获得。我们描述了一种新的方法，区域活动估计(REGAE)，它与现有的M/EEG源分析方法有很大的不同。REGAE优化和校准了ROI信号分辨率和空间分辨率之间的理论权衡。这些校准曲线允许用户根据指定的决策标准微调ROI信号检测器。这项工作的目的是：(A)实现REGAE原型软件，(B)系统地表征影响REGAE分辨率和分辨率的因素，包括传感器配置、信噪比和感兴趣区域位置，以及(C)将REGAE与现有的商业EMSE Suite软件(http://www.sourcesignal.com/sw-desc.htm).)集成拟议的商业应用：我们建议的软件和方法是对现有EEG、MEG和MRI系统的非侵入性、非放射学和相对低成本的补充，并提供目前无法独立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。如果临床价值被证明，基于这种方法的系统可能会在精神病学、神经学和心理学领域找到应用。