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

• 批准号: 2207440
• 负责人: Jie Gao
• 金额: $ 26.2万
• 依托单位: Rutgers University New Brunswick
• 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: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2207440&HistoricalAwards=false
• 关键词: CRCNS; Research; Proposal; Modeling; Human

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（从出生到成年期），人类大脑经历了遗传，环境和专家因素驱动的深刻变化。这些变化是成熟过程的一部分，该过程导致最佳组织的神经回路，该神经回路支持复杂的行为和认知过程，并促进整个寿命的学习。关于发展脑电路如何最佳组织的基本问题仍然存在。具体而言，潜在的生物物理机制 - 在人脑的宏观上，该过程的间隔驱动因素未完全理解。这部分是由于某些发育时期（例如青少年）的复杂性，在此期间，内源性和外源性因素的星座促成了难以跟踪的部分独特生理变化的雪崩。使用近12,000名青少年，高级计算工具和工程原理的多年开发数据的神经影像学数据，该项目的总体目标是了解大脑中的内部机制如何控制其功能电路以最佳支持认知功能。研究活动旨在量化这些机制及其继承变化，因为大脑变得越来越最佳地与年龄联系在一起，并将这些变化映射到认知处理的基本方面。这项研究旨在改变在青少年独特的复杂发育时期对人脑回路优化的理解。为此，它将将历史悠久的纵向神经成像数据集与网络科学和计算机科学的新工具以及控制理论原理整合在一起。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，该过程对网络拓扑和动力学产生了可量化的，年龄变化的影响。因此，神经饱和导致了简约的网络拓扑结构，从而最大程度地提高了信息处理效率，也可以最佳的网络可控性，这两者都反映在认知处理的效率和灵活性上。该项目的发现可能会对对成人脑电路出现的机械原理的理解以及青少年对其发展的影响产生变革性的影响。他们还可能为开发有针对性疗法的发展提供关键的见解，以改善解散或非典型大脑中的认知结果。鉴于跨学科和高度的计算活动，该项目还涉及神经科学研究社区使用的重要工具开发。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，认为通过评估来获得珍贵的支持。