BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging

项目摘要 我们正在请求对R 01 EB 026299（头脑风暴：用于高级 电生理学和MEG/EEG成像），以扩展我们的Brainstorm软件， 一个开源的阿尔茨海默氏病（AD）分析工具包（AD）。新的软件功能将 旨在促进多模式电生理学（与其他成像和数据结合）的使用 收集方法）分期，理解和治疗阿尔茨海默病。R 01 EB 026299提供了 支持开发Brainstorm，一种Matlab/Java多平台（Linux、macOS、Windows）软件环境 用于电生理（e-phys）数据的分析和可视化。这个开源软件扮演了一个 在临床和认知神经科学研究中发挥越来越大的促进作用，体现在以下方面： 发表文章报告使用Brainstorm进行的分析，> 36，000个用户帐户，18，000次下载/月， 在线论坛上有45，000个帖子，2，500名研究人员参加了面对面或在线头脑风暴 培训活动。本研究建议的研究项目完全符合现时拨款的范围，详情载于 R 01 EB 026299竞争性续约的具体目标：“根据此次续约，我们将继续提供 在探索和开发创新的同时，为用户提供支持、文档和培训 与当前分析和研究相关的方法、计算工具和集成软件解决方案 涉及电子物理数据。”AD的神经病理学特征在于神经元细胞损失的阶段性扩散， 神经纤维缠结和多个皮质和皮质下脑区域中的斑块。tau蛋白的积累 现已成为AD病理生理学的另一个标志。针对tau蛋白和tau蛋白的PET配体的开发- 淀粉样蛋白导致早期和临床前AD的检测越来越敏感。然而，PET研究 昂贵的，并没有直接阐明这些蛋白质的积累，或一般的AD， 神经元功能我们将利用头脑风暴中现有的和计划中的计算工具来开发 使用EEG/MEG数据进行AD早期检测和了解其 随着疾病的发展，神经生理学对行为和认知的影响。我们将使用纵向 PREVENT-AD数据库（包括MRI、β-淀粉样蛋白和tau PET和MEG研究，以及医疗记录 和广泛的认知测试）来开发和测试方法和软件。AD开发 本补编下的数据将包括以下两个主要部分： 处理，统计分析和机器学习（ML）在全脑水平，将允许用户提取 脑磁图和脑电图数据的时空特征，并研究它们与β- 淀粉样蛋白和tau蛋白（PET），以及相关的结构测量，如皮质厚度和局部脑 体积（MRI）;（ii）电生理学局部分析的计算方法。我们将开发工具， 研究电生理学标记物，重点是内嗅和嗅周皮质和海马。

PROJECT SUMMARY We are requesting a supplement to R01 EB026299 (Brainstorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging) under NOT-AG-22-025 to extend our Brainstorm software to develop an open-source Alzheimer's Disease (AD) analytical toolkit (AD Toolbox). The new software features will be designed to promote the use of multimodal electrophysiology (in conjunction with other imaging and data collection methods) in staging, understanding, and treating Alzheimer's Disease. R01 EB026299 provides support for developing Brainstorm, a Matlab/Java multi-platform (Linux, macOS, Windows) software environment for analysis and visualization of electrophysiological (e-phys) data. This open-source software plays an increasingly enabling role in clinical and cognitive neuroscience research as reflected in the following: 2,300 published articles reporting analyses using Brainstorm, >36,000 user accounts, 18,000 downloads/month, 45,000 posts on the online forum, and 2,500 researchers who have attended in-person or online Brainstorm training events. The research proposed here is fully within the scope of the current grant, as summarized in the Specific Aims of the competing renewal for R01 EB026299: “Under this renewal, we will continue to provide support, documentation, and training to Brainstorm users while exploring and developing innovative methodologies, computational tools, and integrated software-solutions relevant to current analysis and research involving e-phys data.” The neuropathology of AD is characterized by staged spreading of neuronal cell loss, neurofibrillary tangles, and plaques in multiple cortical and subcortical brain regions. The build-up of tau protein has now become another hallmark of AD pathophysiology. The development of PET ligands for both tau and - amyloid has resulted in increasingly sensitive tests for early-stage and preclinical AD. However, PET studies are expensive and do not shed direct light on the impact of the build-up of these proteins, or AD in general, on neuronal function. We will leverage current and planned computational tools within Brainstorm to develop methodologies for the use of EEG/MEG data in the early detection of AD and in understanding its neurophysiological impact on behavior and cognition as the disease progresses. We will use the longitudinal PREVENT-AD database (which includes MRI, -amyloid and tau PET, and MEG studies, plus medical records and extensive cognitive testing) to develop and test methodology and software. The AD Toolbox developed under this supplement will include the following two major components: (i) Computational methods for data processing, statistical analysis, and machine learning (ML) at the whole-brain level that will allow users to extract spatio-temporal features from MEG and EEG data and study their relationship with spatial protein maps of beta- amyloid and tau (PET), as well as relevant structural measures, such as cortical thickness and regional brain volume (MRI); (ii) Computational methods for localized analysis of electrophysiology. We will develop tools for investigating electrophysiologic markers, focusing on the entorhinal and perirhinal cortex and hippocampus .