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Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools

Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools
使用新颖的计算建模和分析工具解码神经回路中的星形胶质细胞信号传导
批准号:
10650384
负责人:
Guoqiang Yu
金额:
$68.14万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
未结题
起止时间:
2017-04-14 至 2027-04-30

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中文摘要
翻译
星形胶质细胞是人脑中最丰富的胶质细胞,其数量明显多于神经元。长期以来被认为 星形胶质细胞主要是被动细胞,越来越多地被认为是主动调节的重要参与者, 在神经回路和行为中的作用由于单个星形胶质细胞与数千个突触相互作用,其他胶质细胞 细胞和血管,它很好地定位于在不同的时空维度上链接神经元信息 以达到更高水平的大脑整合。事实上,神经元-星形胶质细胞在突触处的通讯调节 呼吸、记忆形成、运动功能和睡眠,并且与许多神经精神障碍有关。 所有这些结果为研究星形胶质细胞的功能提供了强有力的理论基础,这将提供前所未有的 深入了解星形胶质细胞如何调节和保护大脑,以及这些功能如何 将其用于基于星形胶质细胞的治疗靶点。 虽然对星形胶质细胞的功能意义有适度的理解,但其机制和 全面了解星形胶质细胞在神经回路和行为中的积极功能作用, 大部分缺乏。破译星形胶质细胞功能作用的一个主要挑战是其复杂的信号传导 模式存在于空间和时间域中。在上一个奖项的资助下,我们举办了一个活动- 分解框架和方法AQuA(星形胶质细胞定量和分析)来模拟复杂的 星形胶质细胞信号传导AQuA被认为是星形胶质细胞分析的范式转变和转折点, 评论论文,现在被世界上许多实验室广泛使用。 随着技术的进步,主要是由大脑倡议,大规模,多路成像和操纵 星形胶质细胞-神经元网络中的多个电路组件的组合现在是可行的。日益复杂和 大量的成像数据集需要进一步开发功能强大的计算工具,而不是AquA。的 大容量的全脑活动数据和新的信号成像能力超过Ca 2+需要显着 在速度、可扩展性、准确性和灵活性方面的改进。同时记录多个内部/外部- 细胞信号需要新的建模框架和计算方法。因此,在我们以前的基础上, 成功,这个更新项目的总体目标是进一步开发新的计算方法, 分析工具来解码星形胶质细胞在神经回路和行为中的功能作用。 我们将与实验生物学家合作,建立原型,验证和整合我们的计算工具, 跨物种和生物学问题的湿实验室实验。我们期待一个紧密合作的团队科学 计算科学家和实验科学家之间的合作将带来新的发现。最终,成功的 结果将显著提高我们对星形胶质细胞在神经系统中功能的机制和理论理解。 电路和行为。这些理解对于开发新的治疗药物至关重要, 在过去的30年里,神经和神经精神疾病的治疗策略没有改变。
英文摘要
Astrocyte is the most abundant glia cell and significantly outnumbers neuron in the human brain. Long thought to be primarily passive cell, astrocyte has been increasingly recognized as essential player with active regulatory role in neural circuitry and behaviors. Since a single astrocyte interacts with thousands of synapses, other glial cells and blood vessels, it is well positioned to link neuronal information in different spatial-temporal dimensions to achieve higher level brain integration. Indeed, neuron-astrocyte communication at synapses regulates breathing, memory formation, motor function, and sleep, and are implicated in many neuropsychiatric disorders. All these results provide strong rationale for studying astrocyte function, which will provide unprecedented insights to our understanding how astrocytes function to regulate and protect brain and how these functions can be exploited for astrocyte-based therapeutic targets. Although there is a moderate understanding of functional significance of astrocytes, a mechanistic and comprehensive understanding of the active functional roles of astrocytes in neural circuitry and behaviors is largely lacking. One major challenge in deciphering the functional roles of astrocyte is its complex signaling patterns resided in both spatial and temporal domains. Funded by last award, we have developed an event- decomposition framework and the method AQuA (Astrocyte Quantification and Analysis) to model the complex astrocyte signaling. AQuA was considered as a paradigm shift and turning point for astrocyte analysis by multiple review papers and is now widely used by many labs in the world. With the technical advances largely enabled by BRAIN Initiative, large-scale, multiplex imaging and manipulation of multiple circuit components in astrocyte-neuron network are now feasible. The increased complexity and amount of imaging dataset demand further development of powerful computational tools beyond AQuA. The large volume whole-brain activity data and the new imaging capability of signals beyond Ca2+ require significant improvements in speed, scalability, accuracy, and flexibility. The simultaneous recording of multiple intra/extra- cellular signals calls for new modeling framework and computational methods. Thus, building on our previous success, the overarching goal of this renewal project is to further develop novel computational methods and analytical tools to decode the functional roles of astrocytes in neural circuits and behavior. We will team up with experimental biologists to prototype, validate and integrate our computational tools with wet-lab experiments across species and biological questions. We expect a team science of close collaborations between computational and experimental scientists will enable new discoveries. Ultimately, a successful outcome will significantly enhance our mechanistic and theoretical understanding of astrocyte function in neural circuitry and behaviors. These understandings will be essential to development of new therapeutic drugs and strategies, which haven’t been changed in the past 30 years for neurological and neuropsychiatric disorders.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
DOI: 10.3389/fninf.2017.00048
发表时间: 2017
期刊: Frontiers in neuroinformatics
影响因子: 3.5
作者: [Wang Y, Shi G, Miller DJ, Wang Y, Wang C, Broussard G, Wang Y, Tian L, Yu G]
通讯作者: Yu G
DETECTION AND TRACKING OF MIGRATING OLIGODENDROCYTE PROGENITOR CELLS FROM IN VIVO FLUORESCENCE TIME-LAPSE IMAGING DATA.
从体内荧光延时成像数据检测和跟踪迁移的少突胶质细胞祖细胞。
DOI: 10.1109/isbi.2018.8363730
发表时间: 2018
期刊: Proceedings. IEEE International Symposium on Biomedical Imaging
影响因子: --
作者: [Wang,Yinxue, Ali,Maria, Wang,Yue, Kucenas,Sarah, Yu,Guoqiang]
通讯作者: Yu,Guoqiang
SynQuant: an automatic tool to quantify synapses from microscopy images
SynQuant:一种从显微镜图像中量化突触的自动工具
DOI: 10.1093/bioinformatics/btz760
发表时间: 2019
期刊: Bioinformatics
影响因子: 5.8
作者: [Wang, Yizhi, Wang, Congchao, Ranefall, Petter, Broussard, Gerard Joey, Wang, Yinxue, Shi, Guilai, Lyu, Boyu, Wu, Chiung-Ting, Wang, Yue, Tian, Lin]
通讯作者: Tian, Lin
Asymmetric independence modeling identifies novel gene-environment interactions.
不对称独立模型识别新的基因-环境相互作用。
DOI: 10.1038/s41598-019-38983-z
发表时间: 2019
期刊: Scientific reports
影响因子: 4.6
作者: [Yu,Guoqiang, Miller,DavidJ, Wu,Chiung-Ting, Hoffman,EricP, Liu,Chunyu, Herrington,DavidM, Wang,Yue]
通讯作者: Wang,Yue
Time-resolved laser speckle contrast imaging of resting-state functional connectivity in neonatal brain
  • 批准号:
    10760193
  • 项目类别:
  • 资助金额:
    $28.91万
  • 财政年份:
    2023
  • 负责人:
    Guoqiang Yu
  • 依托单位:
Development of a Wearable Fluorescence Imaging Device for IntraoperativeIdentification of Brain Tumors
  • 批准号:
    10697009
  • 项目类别:
  • 资助金额:
    $102.79万
  • 财政年份:
    2023
  • 负责人:
    Guoqiang Yu
  • 依托单位:
Integrating Astrocytes into Models of Neural Circuits Regulating Behavior
Data Science Core
海外基金