Human Neocortical Neurosolver

人类新皮质神经解算器

• 批准号: 9535315
• 负责人: MATTI HAMALAINEN
• 金额: $ 50.97万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9535315
• 关键词: Anatomy; Animal Model; Animals; Architecture; Area; Autistic Disorder; Biophysics; Brain; Collaborations; Computer software; Coupling; Custom; Data; Development; Disease; Documentation; Electrocorticogram; Electroencephalography; Foundations; Frequencies; Genetic; Goals; Growth; Human; Image; Intuition; Magnetoencephalography; Measures; Mental disorders; Methods; Modality; Modeling; Neurosciences; Output; Pathologic; Pathology; Pattern; Property; Pythons; Research; Research Personnel; Resources; Schizophrenia; Sensory; Signal Transduction; Software Tools; Source; Specificity; Structure; Techniques; Testing; Time; Translations; Work; design; dipole moment; experience; human imaging; information processing; insight; mathematical model; millisecond; neocortical; nervous system disorder; neural model; neurophysiology; novel; optogenetics; relating to nervous system; response; sensor; sensory cortex; software development; source localization; success; temporal measurement; tool; two-photon; user-friendly

Abstract The field of neuroscience is experiencing unprecedented growth in the ability to record from and manipulate brain circuits in humans and in animal models. MEG/EEG are the leading methods to non-invasively record human neural dynamics with millisecond temporal resolution. However, it is still extremely difficult to interpret the underlying cellular and circuit level generators of these `macro-scale' signals without simultaneous invasive recordings. This difficulty limits the translation of MEG/EEG finding into novel principles of information processing, or into new treatment modalities for neural pathologies. As such, there is a pressing need, and a unique opportunity, to bridge the `macro-scale' single with the underlying `meso-scale” cellular and circuit level generators. This problem is ideal for neural modeling where we can have specificity at both scales. We propose to build a user-friendly GUI driven neural modeling software tool, “Human Neocortical Neurosolver (HNN)” that enables researchers without mathematical or neural modeling experience to test and develop hypotheses on the cellular and circuit level origin of their source localized MEG/EEG or ECoG data. Our software will work from a foundation of detailed anatomical and biophysical constraints to generate hypotheses as to the neural origin of observed neocortical brain signals. We will work with identified test-case users with existing MEG/EEG data to develop our model into a tool they can use to test and develop specific hypotheses on the neural origin of activity from one or multiple brain areas. We will also integrate the model with the source localization software MNE, so researchers can compute MEG/EEG source estimates and test hypotheses on the neural origin of their data in one integrated software package. We will build resources for freely using and expanding the software through the Neuroscience Gateway Portal, and online documentation and a user forum for interaction between users and developers.

抽象的 神经科学领域正在经历记录和操纵能力的前所未有的增长 人类和动物模型中的脑电路。 MEG/EEG是非侵入性记录的主要方法 人类神经动力学以毫秒临时分辨率。但是，仍然很难解释 这些“宏观”信号的基础细胞和电路级发电机，而无需同时具有侵入性 录音。这种困难将MEG/EEG的翻译限制为新的信息原理 处理，或进入神经病理的新治疗方式。因此，有紧迫的需求，一个 独特的机会，用基础的“中尺度”蜂窝和电路水平桥接“宏观尺度”单曲 发电机。这个问题是神经建模的理想选择，我们在两个尺度上都可以具有特殊性。我们 建立用户友好的GUI驱动神经建模软件工具的建议，“人类新皮层神经质量 （HNN）”，使研究人员没有数学或神经建模经验来测试和发展 源源局部MEG/EEG或ECOG数据的细胞和电路水平来源的假设。我们的 软件将从详细的解剖学和生物物理约束的基础上起作用，以产生假设 关于观察到的新皮层脑信号的神经起源。我们将与已确定的测试案例用户一起使用 现有的MEG/EEG数据将我们的模型开发为可以用于测试和开发特定假设的工具 关于一个或多个大脑区域活动的神经起源。我们还将将模型与源集成 本地化软件MNE，因此研究人员可以计算MEG/EEG来源估算和检验假设 他们数据的神经起源在一个集成的软件包中。我们将免费使用和 通过神经科学网关门户以及在线文档和用户论坛扩展软件 用于用户和开发人员之间的互动。