课题基金 / 基金详情

Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field

Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
推进同步功能磁共振成像多光子成像技术,研究超高场下不同尺度的大脑功能和连接性
批准号:
10463737
负责人:
Wei Chen
金额:
$55.69万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-09-30 至 2025-08-31

项目摘要

项目成果

Wei Chen的其他基金

相似基金

相关文献

中文摘要
翻译
项目概要 了解健康或患病大脑中的神经回路和信号传导需要能够成像的新工具 神经元活动和功能连接在不同尺度上具有卓越的时空精度 微观尺度的神经细胞和微血管个体和群体、神经回路和皮质 层/列,以及介观(或层流)尺度到宏观神经网络的功能连接 规模和神经系统水平。基于血液的功能磁共振成像(fMRI) 氧合水平依赖(BOLD)对比在神经科学中占据了重要地位,它是 唯一能够无创地将人类神经元活动和动态变化映射到 神经计算单元级别、图像功能连接和静息态网络 (RSN) 覆盖整个大脑。然而,fMRI BOLD 信号是由血管之间复杂的相互作用决定的。 和代谢变化,从而间接反映神经元活动。潜在神经元活动的推断 fMRI BOLD 信号可能会受到微观和介观尺度上许多未知因素的影响。 尽管人们付出了巨大的努力来研究功能磁共振成像信号与神经元活动之间的相关性,但 BOLD 信号的神经生理学起源及其在绘制神经元活动和功能方面的特异性 皮质层水平的连接仍然难以捉摸。 为了应对技术挑战并解决关键的神经影像和神经科学问题,我们有 由超高场(UHF)功能磁共振成像和多光子显微镜专家组成的跨学科团队 影像研究领域 两家研究机构共同开发全球首台MRI完全兼容体积 双光子显微成像 (VTPMI) 系统,适用于现场最高的动物 MRI 扫描仪之一 16.4T 特斯拉。这种新颖的 VTPMI-fMRI 多模态神经影像系统将使同时 测量与兴奋性/抑制性神经元的活动和动态相关的关键神经生理学信息, 星形胶质细胞、不同大小的血管和超高分辨率功能磁共振成像数据,从而能够描绘细胞和层 活体大脑中的特定神经元活动。本项目开发的VTPMI-fMRI技术将 用于研究神经血管相关性和静息态 fMRI BOLD 信号的特异性 绘制麻醉和清醒大脑中特定层的功能连接,特别强调 研究抑制性中间神经元的作用。该项目的发现和知识将 具有变革意义,有利于在精细尺度上理解和解释人类 fMRI BOLD 信号 基本计算单位。
英文摘要
PROJECT SUMMARY Understanding the neural circuitry and signaling in health or diseased brain requires new tools that can image neuronal activity and functional connectivity with superior spatiotemporal precision across various scales from individual and population of neural cells and microvessel at microscopic scale, neural circuits and cortical layers/columns, and functional connectivity at mesoscopic (or laminar) scale to neural networks at macroscopic scale and the nervous system level. Functional magnetic resonance imaging (fMRI) based on the blood- oxygenation-level-dependent (BOLD) contrast has gained a prominent position in neuroscience, and it is the only neuroimaging modality that can noninvasively map human neuronal activity and dynamic change to the level of neural computational units, and image functional connectivity and resting-state networks (RSNs) covering the entire brain. However, the fMRI BOLD signal is determined by a complex interplay between vascular and metabolic changes, thus, indirectly reflecting neuronal activity. The inference of underlying neuronal activity on the fMRI BOLD signal can be affected by many unknown factors at microscopic and mesoscopic scales. Although great efforts have been made to study the correlation between fMRI signals and neuronal activity, the neurophysiology origin of the BOLD signal and its specificity in mapping neuronal activity and functional connectivity at cortical lamina level remains elusive. To tackle technical challenges and address critical neuroimaging and neuroscience questions, we have formed an interdisciplinary team with experts in the ultrahigh-field (UHF) fMRI and multi-photon microscopy imaging research fields from two research institutions to develop the world first MRI fully compatible volumetric two-photon microscopy imaging (VTPMI) system, which works in one of the highest field animal MRI scanners at 16.4T Tesla. This novel VTPMI-fMRI multimodal neuroimaging system will make it possible to simultaneously measure key neurophysiological information related to activities and dynamics of excitatory/inhibitory neurons, astrocytes, different sized vessels, and ultrahigh-resolution fMRI data, thus enables delineation of cell- and layer- specific neuronal activity in the living brain. The VTPMI-fMRI technology developed in this project will be employed to study the neuro-vascular correlation and the specificity of resting-state fMRI BOLD signals for mapping the layer-specific functional connectivity in anesthetized and awake brains, with particular emphasis on investigating the roles of inhibitory interneurons. The findings and knowledge from this project will be transformative and beneficial for understanding and interpreting the human fMRI BOLD signals at the fine scale of fundamental computational units.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.
  • 批准号:
    10564824
  • 项目类别:
  • 资助金额:
    $54.37万
  • 财政年份:
    2023
  • 负责人:
    Wei Chen
  • 依托单位:
Establishing translational neuroimaging tools for quantitative assessment of energy metabolism and metabolic reprogramming in healthy and diseased human brain at 7T
  • 批准号:
    10714863
  • 项目类别:
  • 资助金额:
    $63.02万
  • 财政年份:
    2023
  • 负责人:
    Wei Chen
  • 依托单位:
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
海外基金