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了人类所有的感知、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的中断引起的，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学和动力学图对于我们理解各种人类行为和精神疾病的潜在机制至关重要。然而，这一领域的重大进展受到现有神经记录和成像技术的技术限制的阻碍。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。目前迫切需要建立新的具有高空间和时间分辨率的非侵入性成像方法来揭示正常与患病大脑的神经回路动力学。为了满足这一关键需求，我们建议建立并验证一种新的多模态高光谱成像（MHI）技术，该技术基于功能磁共振成像（fMRI）和脑电图（EEG）的同时采集和联合分析，以允许在全脑动力学频谱的特定频率上对大脑活动和连接进行高分辨率映射。这种独特的技术与扩散MRI （dMRI）相结合，将立即可用来创建一个显著丰富的人类大脑连接组，它不仅可以描绘解剖学上特定大脑区域之间的详细连接，还可以为每个区域和每个连接分配颜色编码的“光谱特征”，表明它们在全脑神经回路中不同神经元时间尺度上参与分布式网络活动的不同程度。为实现这一目标，我们建议实现三个具体目标。1)基于虚拟脑（TVB）这一模拟全脑网络动态的神经信息学平台，通过现实计算模拟来开发和优化MHI。2)我们将结合MHI和dMRI神经束成像来创建一个包含结构和功能连接的光谱彩色编码的人类连接组。3)我们将验证用MHI成像的皮质活动和连通性与直接用皮质电图（ECoG）测量的皮质活动和连通性，这些患者来自同一组接受神经外科评估的植入硬膜下网格的癫痫患者。这项研究的结果将为揭示准确评估大脑功能和识别精神障碍诊断的生物标志物的网络基础提供一种新的成像工具。该项目将对描绘大脑的结构和功能连接产生重大的积极影响，为更好地理解和诊断精神健康铺平道路，并对精神障碍的治疗和预防有重大帮助。

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.