Multimodal mapping of the neurocircuitry of the human prefrontal cortex

人类前额皮质神经回路的多模态映射

基本信息

  • 批准号:
    9122980
  • 负责人:
  • 金额:
    $ 57.3万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

 DESCRIPTION (provided by applicant): The objective of the proposed research is to map the organization of human white matter (WM) with cutting-edge ex vivo imaging technologies. This work will produce microscopic-level information on several long-range WM projections, as well as a more targeted mapping of circuits that serve the prefrontal cortex (PFC). These circuits are of particular interest in psychiatric applications but they have been heretofore mapped extensively only in non-human primates. Specifically, recent work with tracer injection studies in macaque monkeys has established how small fiber bundles that originate in different areas of the PFC reach their destinations by using the large WM pathways, such as the cingulum bundle (CB), corpus callosum (CC) and uncinate fasciculus (UF), as their conduits. For example, the UF is composed of several sub-bundles: some that follow the entire trajectory of the UF and others that join the UF only for part of its trajectory to then jump off and join other large pathways, like the CB, CC, etc. Mapping these distinct components of larger WM pathways in the human brain is challenging both in vivo and ex vivo. Invasive injection studies are not applicable to humans and conventional 2D histological techniques like myelin staining cannot be used to infer the 3D orientation of axon bundles. Diffusion MRI (dMRI) can provide estimates of these orientations indirectly, by measuring the diffusion of water molecules through the WM. However, it is prone to errors in areas of complex WM architecture and requires validation by an independent source of measurements. In this work we will combine high-resolution, high-SNR ex vivo dMRI with polarization-sensitive optical coherence tomography (PS-OCT) in post mortem human brains to extract microscopic information on WM areas that confound conventional dMRI, and to perform a detailed mapping of the projections of the PFC. We will take advantage of the MGH Connectom scanner, a unique instrument that can achieve 8 times stronger diffusion-encoding gradients than routine scanners, and was designed specifically for high-SNR, high-resolution dMRI. We will develop a specialized receive coil array for imaging ex vivo human brains on the Connectom scanner, which will allow us to collect whole-brain dMRI data with unprecedented resolution and SNR. The gold-standard dMRI and PS-OCT data produced by this work will be used to construct a novel atlas of WM anatomy, which will be incorporated in a tool for automated global probabilistic tractography, building on prior work by the PI. This tool will allow both the new, detailed taxonomy of smaller WM bundles, as well as the classical definitions of large WM pathways, to be reconstructed automatically from routine-quality in vivo dMRI data that can be collected on conventional scanners. The proposed work promises to advance our understanding of the organization of human neurocircuitry; to move human dMRI studies from the current view of a WM pathway as a single bundle to one where multiple smaller bundles merge on and off a pathway at different parts along its trajectory; and to provide the tools for studying this detailed WM taxonomy using routine neuroimaging data.
 描述(由申请人提供):拟议研究的目的是利用尖端离体成像技术绘制人体白色物质(WM)的组织结构。这项工作将产生一些远程WM投射的微观信息,以及更有针对性的前额叶皮层(PFC)电路映射。这些回路在精神病学应用中特别有意义,但迄今为止,它们仅在非人类灵长类动物中被广泛绘制。具体来说,最近的工作与示踪剂注射研究猕猴已经建立了小纤维束,起源于不同地区的PFC到达其目的地使用大WM途径,如扣带束(CB),胼胝体(CC)和钩束(UF),作为他们的管道。例如,UF由几个子束组成:一些子束遵循UF的整个轨迹,另一些子束仅在其轨迹的一部分加入UF,然后跳离并加入其他大的通路,如CB、CC等。侵入性注射研究不适用于人类,并且传统的2D组织学技术如髓磷脂染色不能用于推断轴突束的3D取向。扩散MRI(dMRI)可以通过测量水分子通过WM的扩散来间接提供对这些方向的估计。然而,它在复杂WM架构的区域中容易出错,并且需要由独立的测量源进行验证。在这项工作中,我们将结合联合收割机高分辨率,高信噪比离体dMRI与偏振敏感光学相干断层扫描(PS-OCT)在死后人脑中提取WM区域的微观信息,混淆传统的dMRI,并执行PFC的投影的详细映射。我们将利用MGH Connectom扫描仪,这是一种独特的仪器,可以实现比常规扫描仪强8倍的扩散编码梯度,专为高SNR、高分辨率dMRI设计。我们将开发一种专门的接收线圈阵列,用于在Connectom扫描仪上对离体人脑进行成像,这将使我们能够以前所未有的分辨率和SNR收集全脑dMRI数据。这项工作产生的金标准dMRI和PS-OCT数据将用于构建WM解剖结构的新图谱,该图谱将被纳入自动化全局概率纤维束成像工具中,以PI先前的工作为基础。该工具将允许新的,详细的分类较小的WM束,以及大WM通路的经典定义,从常规质量的体内dMRI数据,可以在传统的扫描仪上收集自动重建。拟议中的工作有望推进我们对人类神经回路组织的理解;将人类dMRI研究从目前的WM通路作为一个单一的束,多个较小的束合并和关闭的路径在不同的部分沿着其轨迹;并提供工具,使用常规的神经影像学数据研究这种详细的WM分类。

项目成果

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Anastasia Yendiki其他文献

Anastasia Yendiki的其他文献

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{{ truncateString('Anastasia Yendiki', 18)}}的其他基金

Bridging diffusion MRI and chemical tracing for validation and inference of fiber architectures
连接扩散 MRI 和化学示踪以验证和推断纤维结构
  • 批准号:
    10318985
  • 财政年份:
    2020
  • 资助金额:
    $ 57.3万
  • 项目类别:
Bridging Diffusion MRI and Chemical Tracing for Validation and Inference of Fiber Architectures
连接扩散 MRI 和化学示踪以验证和推断纤维结构
  • 批准号:
    10530636
  • 财政年份:
    2020
  • 资助金额:
    $ 57.3万
  • 项目类别:
Structural Connections Core
结构连接核心
  • 批准号:
    10411712
  • 财政年份:
    2015
  • 资助金额:
    $ 57.3万
  • 项目类别:
Structural Connections Core
结构连接核心
  • 批准号:
    10594021
  • 财政年份:
    2015
  • 资助金额:
    $ 57.3万
  • 项目类别:
Penalized-likelihood Algorithms for Time-Domain MR Diffusion Measure Estimation
时域MR扩散测度估计的惩罚似然算法
  • 批准号:
    8292088
  • 财政年份:
    2010
  • 资助金额:
    $ 57.3万
  • 项目类别:
Penalized-likelihood Algorithms for Time-Domain MR Diffusion Measure Estimation
时域MR扩散测度估计的惩罚似然算法
  • 批准号:
    8059859
  • 财政年份:
    2010
  • 资助金额:
    $ 57.3万
  • 项目类别:
Penalized-likelihood Algorithms for Time-Domain MR Diffusion Measure Estimation
时域MR扩散测度估计的惩罚似然算法
  • 批准号:
    8105518
  • 财政年份:
    2010
  • 资助金额:
    $ 57.3万
  • 项目类别:
Penalized-likelihood Algorithms for Time-Domain MR Diffusion Measure Estimation
时域MR扩散测度估计的惩罚似然算法
  • 批准号:
    7361635
  • 财政年份:
    2008
  • 资助金额:
    $ 57.3万
  • 项目类别:
Penalized-likelihood Algorithms for Time-Domain MR Diffusion Measure Estimation
时域MR扩散测度估计的惩罚似然算法
  • 批准号:
    7612656
  • 财政年份:
    2008
  • 资助金额:
    $ 57.3万
  • 项目类别:

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