An open software solution to integrate non-invasive brain stimulation with functional imaging data

摘要 需要能够选择性地操纵人类大脑中的神经系统的非侵入性工具， 推进我们对大脑功能的神经科学理解，并开发新的非药物 精神疗法，是大脑倡议资助的主要重点。经颅磁刺激 (TMS)、经颅直流电刺激（tDCS）和经颅交流电刺激（tACS） 基于大脑中的感应电场来调节神经活动。这些电场分布可以 在真实的头部模型中使用有限元法（FEM）进行数值计算。但 由于缺乏一个综合的网络模型， 结合FEM和功能成像分析的分析平台，具有直接接口， 神经导航软件包 我们建议促进有限元建模在研究和临床环境中的广泛使用 通过扩展和缩放SimNIBS（“非侵入性脑刺激模拟”）-领先的开放式 源软件平台，用于生成基于FEM的电场分布模型， TMS、tDCS或tACS。首先，我们建议通过创建与商业的直接接口来扩展SimNIBS。 神经导航系统，并创建一个容器化的版本用于云计算。第二，我们的目标是 通过开发一个模块来扩展SimNIBS，该模块用于集成功能网络图， 基于个体化预测网络的状态功能性MRI能够优化靶向 数据区.最后，我们将创建一个非人类灵长类动物（NHP）SimNIBS模块， NHP数据促进了BRAIN计划的翻译和比较神经科学目标。

Abstract Noninvasive tools capable of selectively manipulating neural systems in the human brain are needed to advance our neuroscientific understanding of brain function and develop novel non-pharmacologic psychotherapeutics and are a major focus of Brain Initiative funding. Transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) modulate neural activity based on inducing electric fields in the brain. These electric field distributions can be numerically computed using the finite element method (FEM) in realistic head models. However, the use of such models to target specific functional networks is hampered due to the lack of an integrated analysis platform combining the FEM and functional imaging analysis with direct interfaces to neuronavigation packages. We propose to promote the widespread use of FEM modeling in research and clinical environments through extending and scaling SimNIBS (`Simulation of Non-Invasive Brain Stimulation') - the leading open source software platform for generating FEM-based models of the electric field distribution produced by TMS, tDCS or tACS. First, we propose to extend SimNIBS by creating direct interfaces with commercial neuronavigation systems and creating a containerized version for use in the cloud. Second, we aim to extend SimNIBS by developing a module for integrating functional network maps generated with resting state functional MRI to enable the optimization of targeting based on individualized predicted network profiles. Finally, we will create a non-human primate (NHP) SimNIBS module to allow for the processing of NHP data facilitating translational and comparative neuroscience goals of the BRAIN Initiative.