Path Toward MRI with Direct Sensitivity to Neuro-Electro-Magnetic Oscillations

 描述（申请人提供）：为响应NIH RFA-MH-14-217“下一代人脑成像计划”，我们提出了一个全面的计划，组织急需的技术资源和跨学科的研究团队，开发下一代MRI技术，可以直接检测人脑中的神经电活动，具有高的空间和时间分辨率，使用具有3特斯拉磁场强度的扫描仪，这是大多数神经成像研究人员可以使用的。通过我们令人鼓舞的初步研究，我们已经确定，通过直接使MRI信号对神经电磁振荡（NEMO）敏感，可以精确地映射大脑活动。同时，我们还确定了MRI硬件、采集方法和对比机制方面的关键挑战，以充分实现这种方法。我们将通过组织三个创新技术核心来应对这些挑战（以技术目标的形式），目的是在整个大脑中实现超均匀磁场，以确保NEMO信号的稳健检测，达到可以分辨细粒度皮层微结构的超高空间分辨率，以及构建非侵入性人脑-机器接口（BMI），其对功能性神经成像信号进行建模和分类，并驱动附接的机器人外骨骼。为了建立一个直接和敏感的MRI检测神经电活动的令人信服的证据，基于我们坚实的技术基础，我们还提出了四个创新的试点项目（以科学目的的形式）使用高分辨率MRI构建具有因果信息的静态神经元模型，在体内研究动态NEMO信号，在驱动和内在神经元振荡期间具有增强的灵敏度，并对动态神经成像信号进行建模和分类，并通过我们的非侵入性人体BMI在机器人外骨骼中复制和验证人类行为。为了帮助评估我们的研究进展，并从大脑研究界的研究人员和领导者那里获得重要的投入，我们将组织由我们的跨学科研究团队和我们的科学咨询委员会协调的年度研讨会。我们预计，通过这些全面的规划和研究活动，我们将能够确定一条明确的道路，以达到下一代人脑成像技术，该技术可以精确，非侵入性和明确地映射大脑活动，具有前所未有的空间和时间分辨率。

 DESCRIPTION (provided by applicant): In response to the NIH RFA-MH-14-217 on "Planning for Next Generation Human Brain Imaging", we propose a comprehensive plan to organize the much needed technological resources and interdisciplinary research team for developing the next generation MRI technology that can directly detect neuroelectric activities in the human brain with a high spatial and temporal resolution, using scanners with the 3 Tesla magnetic field strength that is accessible by the majority of neuroimaging researchers. Through our encouraging preliminary investigations, we have determined that it is possible to precisely map brain activities by directly sensitizing the MRI signal to the neuro-electro-magnetic oscillations (NEMO). At the same time, we have also identified key challenges in MRI hardware, acquisition methods, and contrast mechanisms to fully enable this approach. We will address these challenges by organizing three innovative technical cores (in the form of Technical Aims) for the purpose of enabling an ultra-uniform magnetic field throughout the brain to ensure a robust detection of the NEMO signal, reaching ultra-high spatial resolutions that can resolve fine-grained cortical microstructures, and building a non-invasive human brain-machine interface (BMI) that models and classifies the functional neuroimaging signals and drives an attached robotic exoskeleton. To establish convincing evidences toward a direct and sensitive MRI detection of neuroelectric activity, and based on our solid technical foundation, we also propose four innovative pilot projects (in the form of Scientific Aims) to construct a static neural networ with causal information using high-resolution MRI, to investigate dynamic NEMO signals in vivo with enhanced sensitivity during both driven and intrinsic neuronal oscillations, and to model and classify the dynamic neuroimaging signals and to replicate and validate the human behavior in the robotic exoskeleton through our non-invasive human BMI. To help evaluate our research progress and receive critical input from researchers and leaders in the brain research community, we will organize annual workshops coordinated by our interdisciplinary research team and our scientific advisory committee. We anticipate that through these comprehensive planning and research activities, we will be able to define a clear path to reach the next generation human brain imaging technology that can precisely, non-invasively, and unambiguously map brain activities with unprecedented spatial and temporal resolution.