Imaging early development of human neural circuits
人类神经回路早期发育的成像
基本信息
- 批准号:10684840
- 负责人:
- 金额:$ 44.92万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-16 至 2027-07-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAdolescentAdultAffectAlgorithmsAnatomyAtlasesBackBasal GangliaBirthBrainBrain Hypoxia-IschemiaBrain imagingChildCirculationCognitive deficitsCommon VentricleCommunicationCompensationCongenital DisordersDataDevelopmentDevelopmental Delay DisordersDiseaseDropoutEarly treatmentEnsureFetal DevelopmentFetusFunctional Magnetic Resonance ImagingGoalsHeadHeart DiseasesHumanHypoxiaImageImaging technologyImpairmentInfantKnowledgeLeadLifeMagnetic Resonance ImagingMental disordersMethodsMotionNeurodevelopmental DisorderNeurologyNeuronsNeurosciencesOrganOutcomePatientsPregnancyPrevention strategyProcessReference StandardsReportingResearchResourcesSample SizeSamplingScanningSchool-Age PopulationSecond Pregnancy TrimesterSeriesSignal TransductionSingle ventricle congenital heart diseaseSliceStructureTechniquesTechnologyTestingTherapeutic InterventionTimeWorkanalysis pipelinecohortcongenital brain disordercongenital heart disorderfetalfunctional MRI scanhigh riskimage processingimprovedin uteroin vivoindependent component analysisinnovationinnovative technologiesmigrationneuralneural circuitneurodevelopmentprenatalprospectivereal-time imagesreconstructionsuccesssynaptogenesistemporal measurementtool
项目摘要
Imaging early development of human neural circuits
The overall objective of this research is to create new imaging technology that dramatically improves our
ability to analyze the development of brain function and functional networks before birth. Functional
magnetic resonance imaging (fMRI) provides a unique capability to study neural circuits and brain
functional connections in-vivo. Fetal fMRI acquisition and analysis, however, has been hampered by
three important challenges: 1) fetal motion disrupts the spatial and temporal continuity of the MRI signal,
2) geometric distortion is exacerbated by the motion of fetal and maternal organs, and 3) the anatomy
and function of the developing fetal brain is distinctly different from those of young children and adults,
thus current processing pipelines and atlases are inadequate for reliable fetal fMRI analysis. To address
these challenges, we pursue three specific aims in this study, that are focused on 1) developing a
prospectively motion navigated fetal fMRI acquisition technology, based on fast real-time image
processing, that compensates for the fetal head motion and geometric distortions during acquisitions; 2)
developing a post-acquisition processing technique that reconstructs an fMRI time series from motion-
corrected fetal fMRI data that are scattered in space and time because of motion and motion correction;
and 3) assessing the utility of fetal fMRI and the developed technologies to evaluate early development
of neural circuits and brain function in fetuses with congenital heart disease compared to healthy fetuses.
This contribution is important because it 1) mitigates a critical barrier to making progress in the field of
developmental neurology and neuroscience by allowing reliable use of fetal fMRI in studying normal vs.
abnormal development of the brain function; 2) improves the efficiency and efficacy of fetal fMRI through
prospectively adjusting scans to compensate for motion and geometric distortions, thus strengthens our
ability to study large cohorts; 3) provides tools and resources, including atlas-based parcellation and a
processing pipeline for the analysis of fetal fMRI; and 4) generates important knowledge about the
origins of disrupted neural development due to hypoxia ischemia in congenital heart disease. The
technology, resources, and knowledge developed in this study have a broad impact and are crucial for
advanced studies in developmental neuroscience and neurology, aiming to elucidate the potentially
devastating effects of adverse early life conditions including congenital disorders of the brain and heart. It
is hoped that these studies lead to improved understanding of the underlying causes of
neurodevelopmental disorders, leading to preventive strategies, therapies, and in some cases, cure.
人类神经回路的早期发育成像
这项研究的总体目标是创造新的成像技术,大大提高我们的
分析出生前大脑功能和功能网络发展的能力。功能
磁共振成像(fMRI)提供了研究神经回路和大脑的独特能力,
体内功能连接。然而,胎儿功能磁共振成像的采集和分析受到以下因素的阻碍:
三个重要的挑战:1)胎儿运动破坏了MRI信号的空间和时间连续性,
2)胎儿和母体器官的运动加剧了几何失真,以及3)解剖结构
发育中的胎儿大脑的功能与幼儿和成人的大脑功能明显不同,
因此,目前的处理管道和图谱不足以进行可靠的胎儿fMRI分析。解决
这些挑战,我们追求三个具体目标,在这项研究中,这是集中在1)开发一个
基于快速实时图像的前瞻性运动导航胎儿fMRI采集技术
处理,其补偿采集期间的胎头运动和几何失真; 2)
开发一种采集后处理技术,从运动中重建fMRI时间序列,
由于运动和运动校正而在空间和时间上分散的校正的胎儿fMRI数据;
评估胎儿功能磁共振成像的实用性和已开发的技术,以评估早期发育
先天性心脏病胎儿的神经回路和大脑功能与健康胎儿相比。
这一贡献是重要的,因为它1)减轻了在生物技术领域取得进展的一个关键障碍,
发育神经学和神经科学,允许可靠地使用胎儿功能磁共振成像研究正常与
脑功能发育异常; 2)通过以下方式提高胎儿fMRI的效率和功效:
前瞻性地调整扫描以补偿运动和几何失真,从而增强了我们的
研究大型队列的能力; 3)提供工具和资源,包括基于地图集的分割和
用于分析胎儿fMRI的处理管道;以及4)产生关于胎儿fMRI的重要知识。
先天性心脏病缺氧缺血性神经发育障碍的起源的
本研究中开发的技术、资源和知识具有广泛的影响,对
发展神经科学和神经学的先进研究,旨在阐明潜在的
包括先天性大脑和心脏疾病在内的早期不良生活条件的毁灭性影响。它
希望这些研究能够提高对这些疾病的根本原因的理解。
神经发育障碍,导致预防策略,治疗,并在某些情况下,治愈。
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)
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ALI GHOLIPOUR-BABOLI其他文献
ALI GHOLIPOUR-BABOLI的其他文献
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{{ truncateString('ALI GHOLIPOUR-BABOLI', 18)}}的其他基金
Imaging early development of human neural circuits
人类神经回路早期发育的成像
- 批准号:
10503458 - 财政年份:2022
- 资助金额:
$ 44.92万 - 项目类别:
Enhanced Imaging of the Fetal Brain Microstructure
胎儿脑微结构的增强成像
- 批准号:
10580011 - 财政年份:2022
- 资助金额:
$ 44.92万 - 项目类别:
Enhanced Imaging of the Fetal Brain Microstructure
胎儿脑微结构的增强成像
- 批准号:
10345136 - 财政年份:2022
- 资助金额:
$ 44.92万 - 项目类别:
Advancing Microstructural and Vascular Neuroimaging in Perinatal Stroke
推进围产期卒中的微观结构和血管神经影像学
- 批准号:
10552663 - 财政年份:2019
- 资助金额:
$ 44.92万 - 项目类别:
Advancing microstructural and vascular neuroimaging in perinatal stroke
推进围产期卒中的微观结构和血管神经影像学
- 批准号:
10332741 - 财政年份:2019
- 资助金额:
$ 44.92万 - 项目类别:
Motion-robust super-resolution diffusion weighted MRI of early brain development
早期大脑发育的运动稳健超分辨率扩散加权 MRI
- 批准号:
9284277 - 财政年份:2014
- 资助金额:
$ 44.92万 - 项目类别:
Motion-robust super-resolution diffusion weighted MRI of early brain development
早期大脑发育的运动稳健超分辨率扩散加权 MRI
- 批准号:
8764291 - 财政年份:2014
- 资助金额:
$ 44.92万 - 项目类别:
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