NCS-FO: Data-driven modeling of visual cortex

NCS-FO：视觉皮层的数据驱动建模

• 批准号: 1734854
• 负责人: Robert Shapley
• 金额: $ 60万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734854&HistoricalAwards=false
• 关键词: NCS; FO; Data; driven; modeling

One of the great challenges of modern neuroscience is a comprehensive theory of the function of the cerebral cortex. The overall aim of the present project is to answer this challenge with a new model of the visual cortex. The modeling process will lead to the discovery of common, canonical neural mechanisms behind a multitude of visual phenomena, giving special emphasis to canonical computations that are performed not just in the visual cortex but also in other regions of the cerebral cortex. The project aims to enhance understanding of cortical function by looking beyond structure to study the dynamics of cortical activity. An important part of the project's broader impact will be to provide interdisciplinary training for young researchers in response to society's need for an educated workforce with multi-disciplinary skills bridging mathematics and neurobiology. Additionally, the principal investigators will reach out to broad scientific audiences as well as high school students. Specifically, the results of this project will be disseminated by giving invited scientific lectures to national and international scientific meetings. The investigators also participate in university-sponsored outreach events for New York City-area high school students, such as the annual C-Splash lectures at the NYU Courant Institute of Mathematical Sciences. This project adopts an integrative strategy to apply ideas from dynamical systems theory to theoretical neuroscience. The project will construct a next-generation model of the visual cortex that is realistic and comprehensive in the way it reproduces the dynamics of cortex and its visual functions. The model will be constrained by hundreds of sets of visual neuroscience data and by all that is known about cortical neuroanatomy. Such a model is a tool to advance neuroscience and a step toward building robotic intelligent systems that emulate human perception. The visual cortex will be modeled as a large network of spiking, conductance-based neurons. It will be analyzed as a complex dynamical system. Specific projects are: 1) network models of local circuitries; 2) extended models of the visual cortex covering a substantial portion of the visual field, and 3) dynamical interactions on neuronal scale to perceptual organization of two- and three-dimensional objects. The modeling and analysis will have wide impact beyond visual cortex in studies of the functional, dynamical consequences of canonical computations that are performed throughout the cerebral cortex. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE). This award is co-funded by the Division of Mathematical Sciences in the Directorate for Mathematical and Physical Sciences (MPS).

现代神经科学面临的最大挑战之一是对大脑皮层功能的全面理论。本项目的总体目标是用一种新的视觉皮层模型来回答这一挑战。建模过程将导致发现许多视觉现象背后的共同的、规范的神经机制，特别强调不仅在视觉皮层而且在大脑皮层的其他区域执行的规范计算。该项目旨在通过超越结构来研究皮质活动的动力学，从而增强对皮质功能的理解。该项目更广泛影响的一个重要部分将是为年轻研究人员提供跨学科培训，以满足社会对受过教育的劳动力的需求，这些劳动力具有连接数学和神经生物学的多学科技能。此外，主要研究人员将接触广泛的科学受众以及高中生。具体而言，该项目的成果将通过在国家和国际科学会议上举办特邀科学讲座的方式传播。研究人员还参加了大学主办的针对纽约城区高中生的外展活动，例如纽约大学柯朗数学科学研究所的年度C-Splash讲座。本计画采用整合策略，将动力系统理论的思想应用于理论神经科学。该项目将构建下一代视觉皮层模型，该模型在再现皮层及其视觉功能的动态方面是现实和全面的。该模型将受到数百组视觉神经科学数据和所有已知的皮层神经解剖学的约束。这种模型是推进神经科学的工具，也是构建模仿人类感知的机器人智能系统的一步。视觉皮层将被建模为一个大型的尖峰网络，基于电导的神经元。它将被分析为一个复杂的动力系统。具体项目有：1）局部电路的网络模型; 2）覆盖视野的相当大一部分的视皮层的扩展模型;以及3）神经元尺度上的动态相互作用以感知二维和三维物体的组织。建模和分析将产生广泛的影响，超越视觉皮层的功能，动力学后果的规范计算，在整个大脑皮层的研究。该项目由理解神经和认知系统的综合策略（NSF-NCS）资助，这是一个由计算机和信息科学与工程（CISE），教育和人力资源（EHR），工程（ENG）以及社会，行为和经济科学（SBE）董事会共同支持的多学科计划。 该奖项由数学和物理科学局（MPS）数学科学部共同资助。

项目成果

Unraveling the mechanisms of surround suppression in early visual processing.

• DOI: 10.1371/journal.pcbi.1008916
• 发表时间: 2021-04
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Li Y;Young LS
• 通讯作者: Young LS

A case study in the functional consequences of scaling the sizes of realistic cortical models

缩放现实皮质模型尺寸的功能后果的案例研究

• DOI: 10.1371/journal.pcbi.1007198
• 发表时间: 2019
• 期刊: PLoS Computational Biology
• 影响因子: 4.3
• 作者: Madhura R. Joglekar;Logan Chariker;R. Shapley;L. Young
• 通讯作者: L. Young

Rhythm and Synchrony in a Cortical Network Model

• DOI: 10.1523/jneurosci.0675-18.2018
• 发表时间: 2018-10-03
• 期刊: JOURNAL OF NEUROSCIENCE
• 影响因子: 5.3
• 作者: Chariker, Logan;Shapley, Robert;Young, Lai-Sang
• 通讯作者: Young, Lai-Sang

Malleability of gamma rhythms enhances population-level correlations

• DOI: 10.1007/s10827-021-00779-4
• 发表时间: 2021-04-05
• 期刊: JOURNAL OF COMPUTATIONAL NEUROSCIENCE
• 影响因子: 1.2
• 作者: Saraf，Sonica;Young，Lai-Sang
• 通讯作者: Young，Lai-Sang

Contrast response in a comprehensive network model of macaque V1

• DOI: 10.1167/jov.20.4.16
• 发表时间: 2020-04-01
• 期刊: JOURNAL OF VISION
• 影响因子: 1.8
• 作者: Chariker, Logan;Shapley, Robert;Young, Lai-Sang
• 通讯作者: Young, Lai-Sang