Computational Modeling Core

项目概要：计算建模核心 我们的团队为这个大脑倡议U19建议催产素调制的神经回路功能和行为 位于纽约大学格罗斯曼医学院，计算建模核心的工作人员位于 纽约大学神经科学研究所以及催产素U19项目和其他核心实验室。这种接近有助于 他们的互动，这产生了一些正在进行的合作，并将促进发展， 验证、实施、标准化和推广催产素功能的计算分析 这是这个计算建模核心的基础。核心主任Kenway Louie博士是一位 在网络建模和行为分析方面拥有丰富经验的计算神经科学家， 领导一个博士后水平的工作人员团队，在建议的建模技术方面具有专业知识。 这个计算建模核心将作为计算建模的集中资源 与项目团队实验室研究中的催产素机制相关，协调理论，分析和模拟 跨项目实验室的方法。这种研究支持将使理论上的合作 在四个项目实验室之间，标准化计算建模方法，以预测 细胞，突触和电路的变化，提供了一个集成的，分层的建模框架，为不同的社会 行为，并提供直接和强大的访问催产素的计算检查 调节所有U19团队成员的电路功能和行为。计算建模核心的目标1 是开发催产素功能和个体动物行为的基于电路的模型。使用已建立的 动态速率模型定制感兴趣的电路，这种方法将识别特定的催产素相关的 与研究中的大脑区域相关的实验操作，允许与实验数据进行比较 以及关于回路特异性催产素功能的假设检验。目标2是开发基于主体的模型（ABM） 多主体社会行为，这将研究催产素如何有助于神经之间的关系， 计算、个体动物行为和涌现的多智能体社会行为。这项工作将使 关于特定操作的效果的预测（例如，催产素受体敲除）对特定行为的影响 (e.g.,社会等级形成），在经验行为中测试ABM预测，并完善我们对 催产素在不同社会行为中的计算和认知作用。目标3：建立统一的理论 该框架综合了不同数据集的建模方法，特别是利用了 目标1的动态建模和目标2的ABM框架，以捕获社会行为的多个时间尺度。 我们将与数据科学和行为核心密切合作，以标准化模型结构，模拟 行为和神经数据以及元数据管理。我们亦会透过以下措施，确保我们的工作可供查阅： 一个专门的U19计算建模核心源代码存储库。

Project Summary: Computational Modeling Core Our team for this BRAIN Initiative U19 proposal on Oxytocin Modulation of Neural Circuit Function and Behavior is located at NYU Grossman School of Medicine, and staff for the Computational Modeling Core are located in the NYU Neuroscience Institute alongside the Oxytocin U19 Project and other Core labs. This proximity facilitates their interactions, which has produced a number of ongoing collaborations and will promote the development, validation, implementation, standardization, and dissemination of computational analyses of oxytocin function that are the foundation of this proposed Computational Modeling Core. Core Director Dr. Kenway Louie is a computational neuroscientist with extensive experience in network modeling and behavioral analysis, who will lead a team of postdoctoral-level staff with expertise in the proposed modeling techniques. This Computational Modeling Core will serve as a centralized resource for computational modeling relevant to oxytocin mechanisms in Project team lab research, coordinating theoretical, analytic, and simulation approaches across the Project labs. This research support will enable theoretically-motivated collaborations between the four Project labs, standardize computational modeling approaches to predict behavioral effects of cellular, synaptic, and circuit changes, provide an integrated, hierarchical modeling framework for different social behaviors, and provide straightforward and robust access to the computational examination of oxytocin modulation of circuit function and behavior for all U19 team members. Aim 1 of the Computational Modeling Core is to develop circuit-based models of oxytocin function and individual animal behavior. Using established dynamical rate models customized to circuits of interest, this approach will identify specific oxytocin-related experimental manipulations relevant to the brain areas under study, allowing comparison to experimental data and hypothesis testing about circuit-specific oxytocin function. Aim 2 is to develop agent-based models (ABM) of multi-agent social behaviors, which will examine how oxytocin contributes to the relationship between neural computations, individual animal behavior, and emergent multi-agent social behaviors. This work will make predictions about the effect of specific manipulations (e.g., oxytocin receptor knockout) on specific behaviors (e.g., social hierarchy formation), test ABM predictions in empirical behavior, and refine our understanding of the computational and cognitive role of oxytocin in different social behaviors. Aim 3 is to develop a unified theoretical framework that synthesizes modeling approaches for diverse datasets, specifically drawing on both the dynamical modeling of Aim 1 and ABM frameworks of Aim 2, to capture multiple timescales of social behavior. We will work closely with the Data Science and Behavior Cores to standardize model structures, simulated behavioral and neural data, and metadata curation. We will also ensure accessibility of our work by maintaining a dedicated U19 Computational Modeling Core source code repository.