CRCNS Research Proposal: Modeling Human Brain Development as a Dynamic Multi-Scale Network Optimization Process
CRCNS 研究提案:将人脑发育建模为动态多尺度网络优化过程
基本信息
- 批准号:2207440
- 负责人:
- 金额:$ 26.2万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2026-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Over a period of almost two decades (from birth to young adulthood), the human brain undergoes profound changes, driven by genetic, environmental and experiential factors. These changes are part of a maturation process that leads to optimally organized neural circuits that support complex behaviors and cognitive processes, and facilitate learning across the lifespan. Fundamental questions remain about how developing brain circuits become optimally organized. Specifically, the underlying biophysical mechanisms -- the interval drivers of this process are incompletely understood at the macroscale of the human brain. This is in part due to the complexity of some developmental periods, such as adolescence, during which a constellation of endogenous and exogenous factors contribute to an avalanche of partially unique physiological changes that are difficult to track. Using neuroimaging data collected over years of development from almost 12,000 adolescents, advanced computational tools and engineering principles, the overarching goal of this project is to understand how internal mechanisms in the brain control its functional circuits to optimally support cognitive function. Research activities aim to quantify these mechanisms and their inherent changes, as the brain becomes increasingly optimally connected with age, and to map these changes onto fundamental aspects of cognitive processing.This research aims to transform mechanistic understanding of the optimization of human brain circuits during the uniquely complex developmental period of adolescence. For this purpose, it will integrate a historically large, longitudinal neuroimaging dataset with novel tools from network science and computer science, and principles of control theory. The primary hypothesis is that the brain’s topological optimization is partly driven by an internal control process, which has a quantifiable, age-varying impact on network topology and dynamics. Thus, neural maturation leads to parsimonious network topologies that maximize efficiency of information processing but also optimal network controllability, both of which are reflected on the efficiency and flexibility of cognitive processing. Findings from this project may have a transformative impact on the understanding of mechanistic principles underlying the emergence of the adult brain circuitry, and the impact of adolescence on its development. They may also provide critical insights towards the development of targeted therapies for improving cognitive outcomes in the diseased or atypically developing brain. Given cross-disciplinary and highly computational activities, this project also involves significant tool development for use by the neuroscience research community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在近二十年的时间里(从出生到成年),人类大脑经历了深刻的变化,受到遗传,环境和经验因素的驱动。这些变化是成熟过程的一部分,成熟过程导致最佳组织的神经回路,支持复杂的行为和认知过程,并促进整个生命周期的学习。基本的问题仍然是关于发育中的大脑回路如何变得最优。具体来说,在人类大脑的宏观尺度上,对这一过程的基本生物物理机制--间隔驱动器--的理解并不完全。这部分是由于某些发育时期的复杂性,如青春期,在此期间,一系列内源性和外源性因素导致难以跟踪的部分独特生理变化的雪崩。利用从近12,000名青少年多年来收集的神经成像数据,先进的计算工具和工程原理,该项目的总体目标是了解大脑的内部机制如何控制其功能电路,以最佳地支持认知功能。研究活动旨在量化这些机制及其内在变化,因为大脑与年龄的联系越来越优化,并将这些变化映射到认知处理的基本方面。这项研究旨在改变对人类大脑回路优化的机械理解在青春期独特复杂的发育时期。为此,它将整合一个历史性的大型纵向神经成像数据集,以及来自网络科学和计算机科学的新工具,以及控制理论的原理。主要的假设是,大脑的拓扑优化部分是由内部控制过程驱动的,这对网络拓扑和动态具有可量化的、年龄变化的影响。因此,神经成熟导致简约的网络拓扑结构,最大限度地提高信息处理的效率,但也是最佳的网络可控性,这两者都反映在认知处理的效率和灵活性。该项目的发现可能会对理解成人大脑回路出现的机械原理以及青春期对其发展的影响产生变革性影响。它们还可以为开发靶向治疗提供重要见解,以改善患病或发育中大脑的认知结果。鉴于跨学科和高度计算的活动,该项目还涉及重要的工具开发,供神经科学研究界使用。该奖项反映了NSF的法定使命,并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。
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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Jie Gao其他文献
Few-shot learning for short text classification
短文本分类的少样本学习
- DOI:
10.1007/s11042-018-5772-4 - 发表时间:
2018 - 期刊:
- 影响因子:3.6
- 作者:
Leiming Yan;Yuhui Zheng;Jie Gao - 通讯作者:
Jie Gao
Mucin2 is Required for Probiotic Agents-Mediated Blocking Effects on Meningitic E. coli-Induced Pathogenicities.
Mucin2 是益生菌介导的对脑膜炎大肠杆菌诱导的致病性的阻断作用所必需的。
- DOI:
10.4014/jmb.1502.02010 - 发表时间:
2015-10 - 期刊:
- 影响因子:0
- 作者:
Jingyi Yu;Xiaolong He;Puthiyakunnon S;Liang Peng;Yan Li;Li-Sha Wu;Wen Ling Peng;Ya Zhang;Jie Gao;Yao-Yuan Zhang;Swapna Boddu;Ming Long;Hong Cao;Sheng-He Huang - 通讯作者:
Sheng-He Huang
The Existence of Homoclinic Solutions for Second Order Differential Equation
- DOI:
10.4028/www.scientific.net/amm.195-196.728 - 发表时间:
2012-08 - 期刊:
- 影响因子:0
- 作者:
Jie Gao - 通讯作者:
Jie Gao
Study on photodissociation and photoconversion characteristics of CS2 in O2/O3 environment using real-time conversion products obtained by UV-DOAS
利用UV-DOAS获得的实时转换产物研究CS2在O2/O3环境中的光解离和光转换特性
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:7.7
- 作者:
Jie Gao;Mu Li;Huan Zhao;Yongqi Wu;Qiang Gao;Xijun Wu;Yucun Zhang;Yungang Zhang - 通讯作者:
Yungang Zhang
Nonylphenol ethoxylates biodegradation increases estrogenicity of textile wastewater in biological treatment systems
壬基酚聚氧乙烯醚生物降解增加生物处理系统中纺织废水的雌激素性
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:12.8
- 作者:
Xiwei He;Zhaodong Qi;Jie Gao;Kailong Huang;Mei Li;Dirk Springael;Xu-xiang Zhang - 通讯作者:
Xu-xiang Zhang
Jie Gao的其他文献
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{{ truncateString('Jie Gao', 18)}}的其他基金
Collaborative Research: AF: Small: Promoting Social Learning Amid Interference in the Age of Social Media
合作研究:AF:小:在社交媒体时代的干扰下促进社交学习
- 批准号:
2208663 - 财政年份:2022
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
Collaborative Research: Infrared Chiral Metasurface Enhanced Vibrational Circular Dichroism Biomolecule Sensing
合作研究:红外手性超表面增强振动圆二色性生物分子传感
- 批准号:
2230069 - 财政年份:2022
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
Collaborative Research: 2D ferroelectric nonlinear metasurface holograms
合作研究:二维铁电非线性超表面全息图
- 批准号:
2226875 - 财政年份:2022
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care
合作研究:PPoSS:大型:用于医疗保健计算筛查和监视的超大规模边缘学习的原理和基础设施
- 批准号:
2118953 - 财政年份:2021
- 资助金额:
$ 26.2万 - 项目类别:
Continuing Grant
CAREER: Flat Singular Optics: Generation and Detection of Optical Vortex Beams with Plasmonic Metasurfaces in Linear and Nonlinear Regimes
职业:平面奇异光学:在线性和非线性体系中使用等离激元超表面生成和检测光学涡旋光束
- 批准号:
2204163 - 财政年份:2021
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
Collaborative Research: From Brains to Society: Neural Underpinnings of Collective Behaviors Via Massive Data and Experiments
合作研究:从大脑到社会:通过大量数据和实验研究集体行为的神经基础
- 批准号:
2126582 - 财政年份:2021
- 资助金额:
$ 26.2万 - 项目类别:
Continuing Grant
Collaborative Research: From Brains to Society: Neural Underpinnings of Collective Behaviors Via Massive Data and Experiments
合作研究:从大脑到社会:通过大量数据和实验研究集体行为的神经基础
- 批准号:
1939459 - 财政年份:2019
- 资助金额:
$ 26.2万 - 项目类别:
Continuing Grant
CAREER: Flat Singular Optics: Generation and Detection of Optical Vortex Beams with Plasmonic Metasurfaces in Linear and Nonlinear Regimes
职业:平面奇异光学:在线性和非线性体系中使用等离激元超表面生成和检测光学涡旋光束
- 批准号:
1653032 - 财政年份:2017
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
Collaborative Research: ATD: Theory and Algorithms for Discrete Curvatures on Network Data from Human Mobility and Monitoring
合作研究:ATD:人体移动和监测网络数据离散曲率的理论和算法
- 批准号:
1737812 - 财政年份:2017
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
NeTS: Small: Geometric and Topological Analysis on Trajectory Sensing: Collection, Classification and Anonymization
NeTS:小型:轨迹感知的几何和拓扑分析:收集、分类和匿名化
- 批准号:
1618391 - 财政年份:2016
- 资助金额:
$ 26.2万 - 项目类别:
Standard Grant
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