CCSS: Brain Network Analysis Using Communication Theory

大脑是一个通信网络，大脑区域之间的连接产生了我们的思想。沿着数据收集技术的进步，大脑研究人员越来越依赖先进的计算工具来分析大型复杂的数据集。与此同时，在信息论革命的推动下，通信领域积累了丰富的系统建模、信号提取和分析方法。在信息论和神经科学融合的推动下，该项目旨在通过利用先进的通信工具开发新的大脑分析技术。该项目产生的新技术可以扩大和加深我们对大脑功能和性能的理解，并可直接用于诊断和治疗与年龄有关的痴呆症;此外，通过将这些新的技术进步纳入本科/研究生课程和外联活动，该项目对培养通信和计算神经科学的高技能和多样化的劳动力具有重要影响。是开发定量，信息理论建模和表征大脑连接，神经元活动水平，能力和稳定性的创新方法，并探索这些新技术在理解大脑功能和人类行为反应中的应用。更具体地说，（i）该项目引入了单个脑区的信息守恒框架，在文献中首次将脑区的神经元活动水平与其信息处理能力相关联;（ii）该项目建立了有向信息与动态因果建模之间的条件等价性，并为脑因果分析提供了一个信息论框架;（iii）该项目引入了定量表征单个大脑区域稳定性的新方法，并使研究大脑稳定性和能力如何影响人类行为反应成为可能。该奖项反映了NSF的法定使命，并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，被认为值得支持。

The brain is a communication network, and connectivity between the brain regions generates our minds. Along with improvements in data-gathering techniques, brain researchers are increasingly relying on advanced computational tools to analyze large, complex data sets. At the same time, driven by the revolution in information theory, the communications area has accumulated rich methodologies for system modeling, signal extraction and analysis. Driven by the convergence of information theory and neuroscience, this project aims to develop new techniques for brain analysis by exploiting advanced tools in communications. The new technologies resulted from this project can expand and deepen our understanding of brain functions and performances, and can be applied directly to the diagnosis and treatment of age-related dementia; moreover, by integrating these new technological advances into the undergraduate/graduate curricula and outreach activities, this project has significant impacts on the training of a highly skilled and diverse workforce for communications and computational neuroscience.The goal of the project is to develop innovative methods for quantitative, information-theoretic modeling and characterization of brain connectivity, neuronal activity level, capacities and stability, and to explore the applications of these new techniques in understanding brain functions and human behavioral responses. More specifically, (i) this project introduces an information conservation framework for individual brain regions; for the first time in literature, the neuronal activity level of a brain region is related to its information processing capacity; (ii) this project establishes the conditional equivalence between directed information and dynamic causal modeling, and provides a information-theoretic framework for brain causality analysis; (iii) this project introduces new approaches for quantitative characterization of the stability of individual brain regions, and makes it possible to investigate how brain stability and capacities impact the human behavioral response.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.