Dynamic Network Neuroscience and Control Theory: Toward Interventions for Cognitive Control Dysfunction

动态网络神经科学与控制理论：认知控制功能障碍的干预措施

• 批准号: 9604631
• 负责人: John Medaglia
• 金额: $ 40.87万
• 依托单位: DREXEL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-19 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9604631
• 关键词: Dynamic; Network; Neuroscience; Control; Theory

 DESCRIPTION (provided by applicant): Executive functions, and in particular cognitive control functions, contribute to or are affected by numerous psychiatric and neurological conditions. Understanding how brain network dynamics support cognitive control function is crucial for clarifying the basis of resilience to injury and identifying opportunities for substantive advancements in intervention. While network science (e.g., graph theory) has led to enlightenment in the organization of the brain and basis of human cognition, elucidating translational implications requires an explicit focus. I propose to do so. I aim to apply recent innovations in dynamic network analysis (recent extensions of graph theory) and network control theory in neuroimaging data to examine the basis of cognitive control function in health and dysfunction in stroke. The program integrates approaches from cognitive neuroscience, network science, and control theory. The goal is to produce a theoretical advance in the use of noninvasive brain stimulation treatments for cognitive dysfunction. The specific aims for this project are to: 1) Quantify structural and dynamic brain network properties underlying cognitive control function in health and dysfunction following stroke 2) Use network control theory to intervene in brain networks that support cognitive control There are two main components of this project: (1) the analysis of network structure and function underlying adaptive cognitive control and (2) the use of network control theory applied to diffusion tractography data to (a) discriminate between network mechanisms of cognitive control and (b) facilitate cognitive control recovery in individuals that have suffered from stroke. This would provide a substantial advance in our knowledge of how cognitive control processes exert their influences across brain networks. While some research has begun to emerge in this area, I propose to use state of the art techniques within dynamic network analysis in conjunction with well-validated behavioral measures. This will serve as an important benchmark for work outside of the current application. It will also begin to characterize reference states underlying adaptive task performance that will be used to guide later control theory-based approaches to brain stimulation. Here, network control theory will be used to target noninvasive brain stimulation on an individual basis. This could lead to a substantive advance in our understanding of the variance in responsiveness to noninvasive brain stimulation and lead to a control theory based framework for intervention in cognitive control dysfunction. More broadly, the outcome this work will provide a step toward true integration between network neuroscience and systems engineering-based translation in neurological and psychiatric populations. These fields are developing rapidly, but an explicit focus on cognition and integration with the physical sciences will be required to conceptualize potent opportunities for intervention. This project offers the first opportunity to establish this intersection and promote a new interdisciplinary conversation between the fields represented.

 描述（应用程序提供）：执行功能，特别是认知控制功能，对或受众多精神病和神经系统状况的影响。了解大脑网络动力学如何支持认知控制功能对于阐明对伤害的韧性和确定实质性进步的机会的基础至关重要。尽管网络科学（例如，图理论）导致了大脑组织和人类认知基础的迷惑，但阐明翻译的含义需要明确的重点。我建议这样做。我的目标是在动态网络分析（图理论的最新扩展）和网络控制理论中应用最新创新，以检查中风中健康和功能障碍在健康和功能障碍中的认知控制功能的基础。该计划整合了认知神经科学，网络科学和控制理论的方法。目的是在使用非侵入性脑模拟治疗方面产生理论上的进步。 The specific aims for this project are to: 1) Quantify structural and dynamic brain network properties underlying cognitive control function in health and dysfunction following stroke 2) Use network control theory to intervene in brain networks that support cognitive control There are two main components of this project: (1) the analysis of network structure and function underlying adaptive cognitive control and (2) the use of network control theory applied to diffusion tractography data to (a)区分认知控制的网络机制和（b）促进患有中风的个体的认知控制恢复。这将在我们了解认知控制过程如何在大脑网络中发挥影响的知识提供了重大进步。尽管一些研究已经开始在这一领域中出现，但我建议在动态网络分析中使用最先进的技术，并结合经过验证的行为度量。这将是当前申请以外工作的重要基准。它还将开始表征自适应任务性能的基本参考状态，该态度将用于指导以后的基于控制理论的大脑刺激方法。在这里，网络控制理论将用于单独靶向无创脑刺激。这可能会导致我们对无创脑刺激反应能力的差异的理解，并导致基于控制理论的认知控制功能障碍的框架。更广泛地说，这项工作的结果将为网络神经科学与基于系统工程的神经学和精神病学人群的翻译之间的真正整合提供一步。这些领域正在迅速发展，但是要明确关注与物理科学的认知和融合，以概念化有效的干预机会。该项目提供了建立此十字路口的第一个机会，并促进了所代表的领域之间的新跨学科对话。