Multimodal Integration of functional and structural imaging of the human brain

神经影像学领域的技术进步使我们对人脑的认识取得了前所未有的进步。 磁共振成像（MRI）、功能性MRI（fMRI）和脑电图（EEG）等工具为以安全和非侵入性方式准确研究大脑功能和结构提供了补充信息。 由于这些工具对大脑中的不同过程敏感，因此人们普遍认为，将它们组合起来将产生比单独使用任何一种工具时所获得的信息更上级的信息。 然而，仍然存在与多模态数据融合相关的几个问题，这些问题最终限制了可靠地提取和解释其假设包含的丰富信息的能力。 因此，本提案的目标是建立一个基于开发新的计算和建模技术的研究计划，以优化非侵入性神经成像工具的集成。 这一方法将基于一个三步进程，目标是改进数据（1）采集、（2）分析和（3）解释。 拟议的研究计划将导致最先进的脑电图功能磁共振成像分析工具，用于研究神经血管耦合和大脑连接。 这些工具肯定会增加我们对大脑功能的基础知识，并可能在许多临床应用中发挥核心作用。

Technical advances in the field of neuroimaging have led to unprecedented advances in our knowledge of the human brain. Tools such as Magnetic Resonance Imaging (MRI), functional MRI (fMRI) and Electroencephalography (EEG) provide complementary information for accurately studying brain function and structure in a safe and non-invasive manner. Since these tools are sensitive to different process in the brain, it is generally believed that combing them will yield information that is superior to that achieved when using either in isolation. However, there still exits several problems associated with multimodal data fusion which ultimately limit the ability to reliably extract and interpret the wealth of information it is hypothesized to contain. The goal of this proposal is to therefore establish a research program based on the development of novel computational and modeling techniques for optimizing the integration of non-invasive neuroimaging tools. This method will be based on a three-step process targeting improvements in data (1) acquisition, (2) analysis and (3) interpretation. The proposed research program will result in state-of-the-art EEG-fMRI analysis tools for studying neurovascular coupling and brain connectivity. These tools will most certainly increase our fundamental knowledge of brain function and potentially play a central role in many clinical applications.