Collaborative Research: Multidimensional Curve Estimation for Diffusion MRI
合作研究:扩散 MRI 的多维曲线估计
基本信息
- 批准号:1208917
- 负责人:
- 金额:$ 4.84万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-08-01 至 2014-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Integral curves are natural models for a variety of biological phenomena, from neuron fibers in brain imaging data to jet streams in atmospheric data. Traditionally they have been modeled as solutions to differential equations defined on fields of direction vectors that are observed with noise in a 3D domain. But advances in imaging technology now provide much more complex directional information--functions defined on the 3D sphere-at each location in the domain. Integral curves traced from this enhanced directional data have the potential to dramatically increase our understanding of biological phenomena such as brain connectivity, but the statistical properties of integral curve estimators for this cutting-edge data are not well understood. Therefore in this project the investigators will provide a solid theoretical foundation for integral curve estimation in 3D fields of complex directional data and apply it to large corpuses of real data sets from ongoing scientific studies. The primary plan will be to model directional data locally using high-order supersymmetric tensors, and pose integral curve estimation in terms of ODEs defined on the field of their pseudo-eigenvectors. The investigators will show that the proposed integral curve estimators enjoy optimal convergence rates in a minimax sense, and prove that balloon estimators of the pseudo-eigenvector fields will lead to improved convergence. Then integral curve estimators will be linked to accompanying random processes to allow construction of uniform confidence bands around point estimates for curves; and adaptive estimation of these confidence bands will be explored to make them practically useful. The investigators will then study whether estimation may be improved further by selecting arbitrary 3D measurement locations, possibly using enhanced imaging techniques. Finally, a test for branching of integral curves will be constructed, for example at locations where axon fibers diverge or cross.The proposed work has the potential to dramatically increase the usefulness of diffusion magnetic resonance imaging (MRI) data, a technology with tremendous potential to probe the "wiring diagram" of the brain-- its connectivity-- in living people. Currently, brain connectivity measurements are widely regarded as brittle, complicated, and difficult to validate. For each individual receiving a diffusion MRI scan, the investigators will estimate curves describing the trajectories of axon fibers, the electrical "wires" of the brain. These fibers connect brain regions into distributed networks that give rise to thought; the evolution of this brain wiring in response to normal development, gene expression, aging, disease, drugs, and environmental factors is of primary interest to a broad swath of neuroscience. Simply providing scientific end-users with a sense of whether or not they should believe the estimated fiber trajectories provided to them by computer programs will greatly enhance their ability to make confident decisions about relations between such trajectories and other scientific data. In addition, the proposed methodology is also relevant in meteorology. There, isolines, fronts, jetstreams, and pressure troughs in weather data can be modeled by similar curve trajectories that can be used to enhance existing weather maps. Finally, this proposal has an exciting educational impact. The investigators, a statistician and a computer scientist with neuroscience training, envision building an interdisciplinary team of promising young researchers in statistics and neuroimaging who gain exposure to both the mathematical and neuroscience aspects of curve estimation through joined group meetings, graduate courses, and web resources related to theory and applications. This unique cross-pollination will prepare the trainees to contribute to the broadly interdisciplinary research teams that are ascendant in the sciences.
积分曲线是各种生物现象的自然模型,从大脑成像数据中的神经元纤维到大气数据中的射流。传统上,它们被建模为定义在3D域中观察到的具有噪声的方向向量的场上的微分方程的解。但是,成像技术的进步现在提供了更复杂的方向信息-在三维球体上定义的功能-在域中的每个位置。从这种增强的方向数据中追踪的积分曲线有可能极大地提高我们对大脑连接等生物现象的理解,但这种尖端数据的积分曲线估计的统计特性还没有得到很好的理解。因此,在这个项目中,研究人员将提供一个坚实的理论基础,在三维领域的复杂方向数据的积分曲线估计,并将其应用到大型语料库的真实的数据集正在进行的科学研究。主要计划是使用高阶超对称张量局部地对方向数据进行建模,并根据定义在其伪特征向量上的常微分方程估计姿态积分曲线。研究人员将表明,建议的积分曲线估计享有最佳的收敛速度在极大极小意义上,并证明气球估计的伪特征向量场将导致改善收敛。然后,积分曲线估计将被链接到随机过程,以允许建设统一的置信带周围的点估计曲线和自适应估计这些置信带将被探索,使他们实际上有用的。然后,研究人员将研究是否可以通过选择任意的3D测量位置(可能使用增强的成像技术)来进一步改善估计。最后,将构建积分曲线分支的测试,例如在轴突纤维分叉或交叉的位置。拟议的工作有可能大大增加扩散磁共振成像(MRI)数据的有用性,这是一种具有巨大潜力的技术,可以探测活体大脑的“接线图”-其连接性。目前,大脑连接测量被广泛认为是脆弱的,复杂的,难以验证。对于每个接受弥散MRI扫描的个体,研究人员将估计描述轴突纤维(大脑的电“线”)轨迹的曲线。这些纤维将大脑区域连接成分布式网络,从而产生思想;这种大脑布线的进化对正常发育、基因表达、衰老、疾病、药物和环境因素的反应是神经科学的主要兴趣。简单地为科学最终用户提供他们是否应该相信计算机程序提供给他们的估计的纤维轨迹的感觉,将大大提高他们对这些轨迹和其他科学数据之间的关系做出自信决定的能力。此外,拟议的方法也适用于气象学。在那里,天气数据中的等值线、锋面、急流和气压槽可以通过类似的曲线轨迹来建模,这些曲线轨迹可以用来增强现有的天气图。最后,这项建议具有令人兴奋的教育影响。研究人员是一名统计学家和一名接受神经科学培训的计算机科学家,他们设想建立一个由统计学和神经成像领域有前途的年轻研究人员组成的跨学科团队,他们通过参加小组会议,研究生课程以及与理论和应用相关的网络资源来接触曲线估计的数学和神经科学方面。这种独特的交叉授粉将使学员为在科学领域占优势的广泛的跨学科研究团队做出贡献。
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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Owen Carmichael其他文献
Quantitative Comparison of Neuroimage Registration for fMRI Analyses by AIR, SPM, and a Fully Deformable Model
通过 AIR、SPM 和完全可变形模型进行 fMRI 分析的神经图像配准的定量比较
- DOI:
- 发表时间:
2005 - 期刊:
- 影响因子:0
- 作者:
Minjie Wu;Owen Carmichael;H. Aizenstein - 通讯作者:
H. Aizenstein
Total body skeletal muscle mass estimated by magnetic resonance imaging and creatine (methyl‐d3) dilution in athletes
通过磁共振成像和肌酸(甲基-d3)稀释估算运动员的全身骨骼肌质量
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:4.1
- 作者:
Tessa E Morris;S. Stimpson;Ram R Miller;M. Barton;Michael S. Leonard;Owen Carmichael;K. van Someren;S. Harridge - 通讯作者:
S. Harridge
ANTICHOLINERGIC MEDICATION USE IS ASSOCIATED WITH REDUCED FMRI ACTIVITY DURING VISUAL EPISODIC ENCODING IN COGNITIVELY NORMAL OLDER ADULTS
抗胆碱能药物的使用与认知正常的老年人视觉情景编码期间 FMRI 活动的减少有关
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
M. Espeland;Owen Carmichael;K. Hayden;R. Neiberg;A. Newman;Jeffery N. Keller;T. Wadden;S. Rapp;James O Hill;E. Horton;K. Johnson;L. Wagenknecht;R. Wing - 通讯作者:
R. Wing
Cardiovascular risk in childhood and young adulthood is associated with the hemodynamic response function in midlife: The Bogalusa Heart Study
儿童和青年期的心血管风险与中年时期的血流动力学反应功能有关:博加卢萨心脏研究
- DOI:
10.1016/j.neuroimage.2025.121338 - 发表时间:
2025-08-15 - 期刊:
- 影响因子:4.500
- 作者:
Kai-Cheng Chuang;Maryam Naseri;Sreekrishna Ramakrishnapillai;Kaitlyn Madden;Julia St Amant;Kevin McKlveen;Kathryn Gwizdala;Ramasudhakar Dhullipudi;Lydia Bazzano;Owen Carmichael - 通讯作者:
Owen Carmichael
The Effects of the Form of Sugar (Solid vs. Beverage) on Body Weight and Neuronal Activity: A 28 Day Randomized Pilot Study (P08-001-19)
- DOI:
10.1093/cdn/nzz044.p08-001-19 - 发表时间:
2019-06-01 - 期刊:
- 影响因子:0
- 作者:
John Apolzan;Owen Carmichael;S Nicole Fearnbach;Krystal Kirby;Sreekrishna Ramakrishnapillai;Robbie Beyl;Kishore Gadde;J Jason Collier;Corby Martin - 通讯作者:
Corby Martin
Owen Carmichael的其他文献
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{{ truncateString('Owen Carmichael', 18)}}的其他基金
Collaborative Research: Multidimensional Curve Estimation for Diffusion MRI
合作研究:扩散 MRI 的多维曲线估计
- 批准号:
1443252 - 财政年份:2014
- 资助金额:
$ 4.84万 - 项目类别:
Standard Grant
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