Dissemination of the Human Neocortical Neurosolver (HNN) software for circuit level interpretation of human MEG/EEG

传播用于人类 MEG/EEG 电路级解释的人类新皮质神经解算器 (HNN) 软件

• 批准号: 10726032
• 负责人: STEPHANIE Ruggiano JONES
• 金额: $ 76.69万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10726032
• 关键词: Address; Adopted; Adoption; Alzheimer' s Disease; Animal Model; Area; BRAIN initiative; Basic Science; Biophysics; Brain; Calcium; Clinical Research; Code; Collaborations; Communities; Complement; Complex; Computer software; Consultations; Data; Development; Disease; Documentation; Educational process of instructing; Educational workshop; Electroencephalography; Electrophysiology (science); Ensure; FAIR principles; Fee-for-Service Plans; Feedback; Fostering; Frequencies; Funding; Genetic; Goals; Growth; Guidelines; Health; Human; Image; Imaging Device; Letters; Link; Maintenance; Mental Depression; Mental disorders; Methods; Modeling; Monkeys; Mus; Neocortex; Neurons; Neurosciences; Pain; Parameter Estimation; Physics; Publishing; Pythons; Reproducibility; Research Personnel; Running; Schizophrenia; Sensory; Service delivery model; Signal Transduction; Software Design; Software Tools; Source; Standardization; Techniques; Testing; Training; Update; Validation; Work; Writing; application programming interface; autism spectrum disorder; base; code development; design; graphical user interface; hackathon; information processing; innovative technologies; insight; neocortical; nervous system disorder; neural; neural model; neuropathology; open source; program dissemination; response; scripting interface; simulation; software development; success; supercomputer; tool; translational neuroscience; user-friendly; voltage

HNN U24 DISSEMINATION PROJECT SUMMARY The Human Neocortical Neurosolver (HNN) neural modeling tool was developed with BRAIN Initiative funding (R01EB022889: 09/2016–06/2020) to meet the Initiative’s goal to “develop innovative technologies to understand brain circuits and ensembles of circuits that inform understanding of the human brain and mechanisms for treating its disorder”. HNN is a biophysically principled neocortical circuit model with appropriate physics that allow bridging from macroscale human magneto- and electro-encephalography (M/EEG) signals to their cellular and circuit level generators. HNN is a hypothesis development and testing tool whose design and capabilities are unique compared to other M/EEG neural modeling software. A key value of HNN is to connect functionally- relevant human signals to circuit level dynamics studied in animal models, including data from revolutionary genetic and imaging tools used in mice and monkeys (e.g., Neuropixel recordings, calcium, and voltage imaging). These links are essential to discovering new principles of brain information processing and to developing treatments when this processing is disrupted by neuropathology. There is widespread use of M/EEG, and myriad inferences drawn from these signals about human brain function and health: HNN provides a highly accessible tool for researchers to make principled connections to the detailed neurons and circuits underlying these signals, to test new ideas and ground conclusions in circuit-level reality. The neuroscience community is actively engaged in the use of HNN for basic and clinical research, including studies of Alzheimer’s disease, autism spectrum disorder, pain, depression, and healthy development. While HNN was successfully developed, there remain several challenges for growth and long-term sustainability. The goal of this proposal is to support dissemination of HNN for broadly accessibly use and community-driven development. Identified challenges in maintenance of HNN’s code and documentation that ensure Findability, Accessibility, Interoperability, and Reusability will be addressed (Aim I), and key enhancements necessary to support end-user needs and experimental validation of model-derived predictions will be developed (Aim II). Interpreting the complex multiscale origin of M/EEG signals with HNN’s large-scale neural often requires domain expertise in computational neural modeling, human M/EEG, and neural dynamics. To support this need, we will continue to work with the community to integrate HNN into their projects through workshops, direct collaboration, and consultation with end-user groups, and by enabling HNN simulation on freely accessible supercomputers (Aim III). End-user feedback and documented support needs will be used to develop a Plan for Sustainability. A world-class Steering Committee includes developers of widely-adopted neuroscience software who will share their expertise to help HNN reach its maximal potential as translational neuroscience tool.

HNN U24 传播项目摘要 人类新皮质神经解算器 (HNN) 神经建模工具是在 BRAIN Initiative 的资助下开发的 （R01EB022889：09/2016–06/2020）以实现该倡议的目标“开发创新技术来理解 大脑回路和回路集合，有助于理解人脑及其机制 HNN 是一种基于生物物理学原理的新皮质回路模型，具有适当的物理原理， 允许将宏观人类磁磁图和脑电图 (M/EEG) 信号桥接至细胞 HNN 是一种假设开发和测试工具，其设计和功能如下。 与其他 M/EEG 神经建模软件相比，HNN 的一个关键价值是功能连接。 在动物模型中研究的与电路级动态相关的人类信号，包括来自革命性的数据 用于小鼠和猴子的遗传和成像工具（例如神经像素记录、钙和电压成像）。 这些联系对于发现大脑信息处理的新原理和开发大脑信息处理的新原理至关重要。 M/EEG 被广泛使用，并且有无数的处理过程被神经病理学破坏时的治疗。 从这些关于人脑功能和健康的信号中得出的推论：HNN 提供了一种高度可访问性 为研究人员提供与这些信号背后的详细神经元和电路进行原则性连接的工具， 在电路级现实中测试新想法和基本结论。 神经科学界积极致力于使用 HNN 进行基础和临床研究，包括 阿尔茨海默病、自闭症谱系障碍、疼痛、抑郁和健康发展的研究。 HNN 已成功开发，但其增长和长期可持续性仍存在一些挑战。 该提案的目标是支持 HNN 的传播，以供广泛使用和社区驱动 确定了维护 HNN 代码和文档以确保可查找性的挑战， 将解决可访问性、互操作性和可重用性（目标 I），并进行必要的关键增强 支持最终用户的需求，并将开发模型预测的实验验证（目标 II）。 使用 HNN 的大规模神经网络解释 M/EEG 信号的复杂多尺度起源通常需要域 为了支持这一需求，我们将在计算神经建模、人类 M/EEG 和神经动力学方面拥有专业知识。 继续与社区合作，通过研讨会、直接合作将 HNN 整合到他们的项目中， 与最终用户群体进行协商，并在可免费访问的超级计算机上启用 HNN 模拟 （目标 III）。最终用户的反馈和记录的支持需求将用于制定可持续发展计划 A。 世界一流的指导委员会开发人员包括广泛采用的神经科学软件，他们将分享 他们的专业知识帮助 HNN 发挥其作为转化神经科学工具的最大潜力。