CRCNS Research Proposal: Modeling Human Brain Development as a Dynamic Multi-Scale Network Optimization Process

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，因为大脑随着年龄的增长变得越来越优化，并将这些变化映射到认知处理的基本方面。这项研究旨在转变对青春期独特复杂发育时期人类大脑回路优化的机械理解。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。

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.