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.

hnnu24传播项目总结