Multimodal Hyperspectral Imaging of Brain Activity and Connectivity

描述（由申请人提供）：大量大脑区域之间的动态相互作用产生所有人类感知，认知和行为。越来越多的人认识到，大多数精神障碍是由分布式神经回路中断引起的，其结构和功能仍然知之甚少。因此，绘制人类大脑网络的解剖和动力学对于我们理解各种人类行为和精神疾病的机制至关重要。然而，现有神经记录和成像技术的技术限制阻碍了该领域的重大进展。迄今为止，还没有一种单一的非侵入性神经成像技术能够提供全脑神经元相互作用的完整时空模式。迫切需要建立具有高空间和时间分辨率的新的非侵入性成像方法，以揭示正常与患病大脑中的神经回路动力学。为了满足这一关键需求，我们建议建立和验证一种新的多模态高光谱成像（MHI）技术，基于功能性磁共振成像（fMRI）和脑电图（EEG）的同时采集和联合分析，以允许高分辨率映射大脑活动和连接在特定频率下的全频谱大脑动力学。这种独特的技术与弥散MRI（dMRI）相结合，将立即可用于创建一个显着丰富的人脑连接体，不仅描绘解剖学上特定的大脑区域之间的详细连接，而且还分配给每个区域和每个连接颜色编码的“光谱签名”，表明它们在整个全脑神经回路的各种神经元时间尺度上参与分布式网络活动的不同程度。为达致这个目标，我们建议达致三个具体目标。1)我们将通过基于虚拟大脑（TVB）的逼真计算模拟来开发和优化MHI，虚拟大脑是一个模拟全脑网络动态的神经信息学平台。2)我们将结合联合收割机MHI和dMRI纤维束成像技术来创建一个光谱颜色编码的人类连接体，它需要结构和功能的连接。3)我们将验证使用MHI成像的皮质活动和连通性，与使用皮质电描记术（ECoG）直接测量的皮质活动和连通性进行对比，这些皮质活动和连通性来自接受植入硬膜下网格的神经外科评价的同一组癫痫患者。这项研究的结果将提供一种新的成像工具，以揭示准确评估大脑功能和识别诊断精神障碍的生物标志物的网络基础。该项目将在描绘大脑的结构和功能连接方面产生显著的积极影响，为更好地理解和诊断精神健康铺平道路，并大大有助于治疗和预防精神障碍。

DESCRIPTION (provided by applicant): Dynamic interactions among large sets of brain regions produce all human perception, cognition and behavior. It is increasingly recognized that most mental disorders are caused by disruptions of distributed neural circuits, the structure and function of which still remain poorly known. Therefore, mapping the anatomy and dynamics of human brain networks is critical for us to understand the mechanisms underlying a variety of human behaviors and mental illness. However, significant progress in this area is hindered by technical limitations of existing neural recording and imaging techniques. To date, there is no single non-invasive neuroimaging technique ca- pable of providing a complete spatiotemporal pattern of whole-brain neuronal interactions. There is a critical need to establish new non-invasive imaging methods with high spatial and temporal resolution to uncover neural circuit dynamics in normal vs. diseased brains. To meet this critical need, we propose to establish and validate a novel multimodal hyperspectral imaging (MHI) technique, based on simultaneous acquisition and joint analysis of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), to permit high- resolution mapping of brain activity and connectivity at specific frequencies over the full spectrum of brain dynamics. This unique technique combined with diffusion MRI (dMRI) will be immediately usable to create a significantly enriched human brain connectome that will not only depict detailed connections among anatomically specific brain regions, but also assign to each region and each connection color-coded "spectral signatures" indicating their differential degrees of involvement in distributed network activities over various neuronal time scales across whole-brain neural circuits. To achieve this objective, we propose to accomplish three specific aims. 1) We will develop and optimize MHI through realistic computation simulations based on the virtual brain (TVB), a neuroinformatic platform to simulate the whole-brain network dynamics. 2) We will combine MHI and dMRI tractography to create a spectrally color-coded human connectome that entails both structural and functional connectivity. 3) We will validate the cortical activity and connectivity imaged with MHI against those directly measured with electrocorticography (ECoG) from the same group of epilepsy patients undergoing neuro- surgical evaluation with implanted subdural grids. The outcome from the proposed research will provide a new imaging tool to uncover the network basis for accurately assessing brain functions and identifying biomarkers for diagnosis of mental disorders. This project will have a significantly positive impact in delineating the brain's structural and functional connectivity, paving the way for better understanding and diagnosis of mental health, and significantly aid treatment and prevention of mental disorders.