A Probabilistic Map of Human Visual Cortical Areas from Quantitative Microscopy

定量显微镜下人类视觉皮层区域的概率图

基本信息

  • 批准号:
    7661469
  • 负责人:
  • 金额:
    $ 34.76万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-08-01 至 2013-07-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Most of our knowledge on the organization of the human visual cortex derives from neuroimaging studies that have localized a number of cortical areas based on their functional characteristics. These functional maps are not anchored to precise anatomical landmarks, and no real effort has been made to correlate the topography of the functional borders with local differences in cortical architecture. This is due to the difficulty of systematically comparing functional and histological images. The overall goal of the work is to correlate detailed retinotopic maps acquired by functional MRI (fMRI) with anatomical maps produced by quantifying intracortical myelination histologically. We propose to make this comparison explicit by using high resolution, non-linear surface-based methods to minimize the variability between subjects and brains ex-situ. Cortical geometry will be warped based on reliable sulcal landmarks that are identified automatically on the surface. In order to make histological data amenable to 3-D spatial transformations, we will use tested algorithms for alignment, and reconstruction to produce digital 3-D models of specimens whose surfaces contain architectonic information. In addition, the accuracy and resolution of retinotopic maps will be enhanced by employing a professional team of subjects for repeated scans and improved retinotopic stimulation proven to set off stronger responses from higher order visual areas. This proposal utilizes the combined expertise of three laboratories in neuroanatomical techniques, neuroimaging and computational methods for morphometric analysis and transformation. It is the first time that these expert methodologies are combined to create comprehensive maps of the human visual cortex. The result of the proposed project is the multimodal localization of higher visual areas in relation to macroscopic surface (sulcal) landmarks. The maps and definitions produced by this project will constitute a necessary framework for further functional and anatomical studies, as well as new studies of connectivity afforded by high resolution MRI, fMRI, and MR-DTI. PUBLIC HEALTH RELEVANCE: Computer-aided microanatomical mapping methods will be used to conduct a topographic survey of the visual cortex in the human brain. Specimens will be processed according to multiple histological protocols to reveal complementary architectonic features. Quantification of myelination and neuronal density will be the basis for the statistical delineation of structural borders which will result in a digital, surface-based and probabilistic map of cortical visual areas.
描述(由申请人提供):我们关于人类视觉皮层组织的大部分知识来自神经成像研究,这些研究基于其功能特征定位了许多皮层区域。这些功能图没有固定在精确的解剖学标志上,也没有真实的努力将功能边界的地形图与皮质结构的局部差异联系起来。这是由于系统地比较功能和组织学图像的困难。这项工作的总体目标是将通过功能性MRI(fMRI)获得的详细视网膜定位图与通过定量皮质内髓鞘形成组织学产生的解剖图相关联。我们建议使用高分辨率,非线性表面为基础的方法,以尽量减少受试者和大脑异位之间的差异,使这种比较明确。皮质几何结构将根据表面上自动识别的可靠脑沟标志进行扭曲。为了使组织学数据服从3-D空间变换,我们将使用测试算法进行对齐和重建,以产生其表面包含结构信息的标本的数字3-D模型。此外,将通过雇用专业的受试者团队进行重复扫描和改进的视网膜定位刺激来提高视网膜定位图的准确性和分辨率,该视网膜定位刺激被证明可以从高阶视觉区域产生更强的反应。该提案利用了三个实验室在神经解剖技术、神经影像学和计算方法方面的专业知识,用于形态测量分析和转换。这是第一次将这些专家方法结合起来创建人类视觉皮层的全面地图。所提出的项目的结果是多模式定位的宏观表面(脑沟)地标的更高的视觉领域。该项目产生的地图和定义将构成进一步的功能和解剖学研究的必要框架,以及高分辨率MRI,fMRI和MR-DTI提供的连接性的新研究。 公共卫生相关性:计算机辅助的显微解剖映射方法将被用来进行人类大脑视觉皮层的地形调查。将根据多个组织学方案处理标本,以显示互补的结构特征。髓鞘形成和神经元密度的定量将是结构边界的统计学描绘的基础,这将导致皮质视觉区的数字化、基于表面的概率图。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Jacopo Annese其他文献

Jacopo Annese的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Jacopo Annese', 18)}}的其他基金

Multimodal Correlation of Imaging Markers and Neuropathogenesis of NeuroAIDS
影像学标志物与神经艾滋病神经发病机制的多模态相关性
  • 批准号:
    7933792
  • 财政年份:
    2009
  • 资助金额:
    $ 34.76万
  • 项目类别:
Multimodal Correlation of Imaging Markers and Neuropathogenesis of NeuroAIDS
影像学标志物与神经艾滋病神经发病机制的多模态相关性
  • 批准号:
    7622314
  • 财政年份:
    2009
  • 资助金额:
    $ 34.76万
  • 项目类别:
Multimodal Correlation of Imaging Markers and Neuropathogenesis of NeuroAIDS
影像学标志物与神经艾滋病神经发病机制的多模态相关性
  • 批准号:
    8264207
  • 财政年份:
    2009
  • 资助金额:
    $ 34.76万
  • 项目类别:
PROFILING OF CORTICAL AREAS BY MICRO-MRI
通过显微 MRI 分析皮质区域
  • 批准号:
    7956914
  • 财政年份:
    2009
  • 资助金额:
    $ 34.76万
  • 项目类别:
Multimodal Correlation of Imaging Markers and Neuropathogenesis of NeuroAIDS
影像学标志物与神经艾滋病神经发病机制的多模态相关性
  • 批准号:
    8442886
  • 财政年份:
    2009
  • 资助金额:
    $ 34.76万
  • 项目类别:
Multimodal Correlation of Imaging Markers and Neuropathogenesis of NeuroAIDS
影像学标志物与神经艾滋病神经发病机制的多模态相关性
  • 批准号:
    8073460
  • 财政年份:
    2009
  • 资助金额:
    $ 34.76万
  • 项目类别:
A Probabilistic Map of Human Visual Cortical Areas from Quantitative Microscopy
定量显微镜下人类视觉皮层区域的概率图
  • 批准号:
    8126313
  • 财政年份:
    2008
  • 资助金额:
    $ 34.76万
  • 项目类别:
A Probabilistic Map of Human Visual Cortical Areas from Quantitative Microscopy
定量显微镜下人类视觉皮层区域的概率图
  • 批准号:
    8311768
  • 财政年份:
    2008
  • 资助金额:
    $ 34.76万
  • 项目类别:
A Probabilistic Map of Human Visual Cortical Areas from Quantitative Microscopy
定量显微镜下人类视觉皮层区域的概率图
  • 批准号:
    7894622
  • 财政年份:
    2008
  • 资助金额:
    $ 34.76万
  • 项目类别:
PROFILING OF CORTICAL AREAS BY MICRO-MRI
通过显微 MRI 分析皮质区域
  • 批准号:
    7726197
  • 财政年份:
    2008
  • 资助金额:
    $ 34.76万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 34.76万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了