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 人类新皮质神经溶剂（HNN）神经建模工具是通过大脑倡议资金开发的 （R01EB022889：09/2016-06/2020）要实现该计划的目标，以“开发创新技术以了解 大脑电路和电路合奏，以了解对人脑的理解和机制的理解 治疗其障碍”。HNN是一种具有生物物理的新皮质电路模型，具有适当的物理学 允许从宏观人类的磁磁和电脑摄影（M/EEG）桥接到其细胞 和电路级生成器。 HNN是一种假设开发和测试工具，其设计和功能 与其他M/EEG神经建模软件相比，是独一无二的。 HNN的关键值是连接功能 - 相关的人类信号到动物模型中的电路级动力学研究，包括来自革命性的数据 小鼠和猴子使用的遗传和成像工具（例如，神经胶状记录，钙和电压成像）。 这些链接对于发现大脑信息处理的新原理至关重要 当神经病理学破坏这种处理时的治疗方法。 M/EEG广泛使用，无数 这些信号从有关人脑功能和健康的信号中得出的推论：HNN提供了高度可访问的 研究人员的工具，可以与这些信号的详细神经元和电路建立主要的联系， 测试电路级现实中的新想法和基础结论。 神经科学社区积极从事HNN进行基础和临床研究，包括 阿尔茨海默氏病，自闭症谱系障碍，疼痛，抑郁和健康发育的研究。尽管 HNN已成功发展，在增长和长期可持续性方面仍然存在一些挑战。这 该提案的目标是支持HNN的传播，以广泛使用和社区驱动 发展。确定了维护HNN代码和文档的挑战，以确保可发现性， 将解决可访问性，互操作性和可重用性（AIM I），以及所需的键增强功能 将开发支持最终用户需求和模型衍生预测的实验验证（AIM II）。 用HNN的大规模神经解释M/EEG信号的复杂多尺度来源通常需要域 计算神经建模，人类M/EEG和神经动力学方面的专业知识。为了满足这一需求，我们将 继续与社区合作，通过研讨会，直接协作，将HNN整合到他们的项目中 并与最终用户群体进行咨询，并通过对可自由访问的超级分类器进行HNN模拟 （AIM III）。最终用户的反馈和有记录的支持需求将用于制定可持续性计划。一个 世界一流的指导委员会包括广泛采用神经科学软件的开发人员 他们的专业知识可帮助HNN作为转化神经科学工具发挥最大潜力。