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
• 负责人: Jacopo Annese
• 金额: $ 34.41万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 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
• 来源: https://reporter.nih.gov/project-details/7894622
• 关键词: 3-Dimensional; Algorithms; Anatomy; Architecture; Area; Atlases; Base of the Brain; Brain; Brain Mapping; Cerebral hemisphere; Cerebrum; Characteristics; Communities; Computational Technique; Computer Assisted; Computing Methodologies; Data; Data Set; Functional Imaging; Functional Magnetic Resonance Imaging; Gene Expression; Goals; Histocytochemistry; Histologic; Human; Image; Image Analysis; Individual; Internet; Knowledge; Laboratories; Lesion; Magnetic Resonance Imaging; Maps; Methodology; Methods; Microscopic; Modeling; Myelin; Myelography; Neocortex; Neurons; Neurosciences; Online Systems; Parietal; Pattern; Population; Probability; Process; Protocols documentation; Quantitative Microscopy; Relative (related person); Research; Research Personnel; Resolution; Sampling; Scanning; Series; Specimen; Staining method; Stains; Surface; Surveys; System; Techniques; Temporal Lobe; Testing; Time; Tissues; Visual Cortex; Work; base; computerized tools; density; digital; extrastriate visual cortex; graphical user interface; image processing; imaging modality; improved; mathematical model; myelination; neuroimaging; population based; public health relevance; reconstruction; response; retinotopic; tool; virtual

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都来自神经影像学研究，这些研究根据功能特征定位了许多皮层区域。这些功能图并没有锚定到精确的解剖标志，也没有真正努力将功能边界的地形与皮质结构的局部差异联系起来。这是由于系统比较功能图像和组织学图像的困难。这项工作的总体目标是将功能性 MRI (fMRI) 获得的详细视网膜专题图与通过组织学量化皮质内髓鞘形成产生的解剖图关联起来。我们建议通过使用高分辨率、非线性表面方法来使这种比较变得明确，以尽量减少受试者和异位大脑之间的变异性。皮质几何形状将根据表面自动识别的可靠脑沟标志而变形。为了使组织学数据能够进行 3D 空间转换，我们将使用经过测试的算法进行对齐和重建，以生成其表面包含结构信息的标本的数字 3D 模型。此外，通过聘请专业的受试者团队进行重复扫描和改进的视网膜专题刺激，视网膜专题图的准确性和分辨率将得到提高，经证明可以从更高阶的视觉区域引发更强的反应。该提案利用了三个实验室在神经解剖技术、神经成像和形态测量分析和转换计算方法方面的综合专业知识。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综合地图。该项目的结果是与宏观表面（脑沟）地标相关的较高视觉区域的多模态定位。该项目产生的地图和定义将为进一步的功能和解剖学研究以及高分辨率 MRI、fMRI 和 MR-DTI 提供的连接性新研究构成必要的框架。 公共健康相关性：计算机辅助显微解剖绘图方法将用于对人脑视觉皮层进行地形测量。标本将根据多种组织学协议进行处理，以揭示互补的结构特征。髓鞘形成和神经元密度的量化将成为结构边界统计描绘的基础，这将产生皮质视觉区域的数字化、基于表面的概率图。