Mapping the structural and functional organisation of the human brain via in vivo neuroimaging and complex network analysis

通过体内神经成像和复杂网络分析绘制人脑的结构和功能组织

• 批准号: 2267801
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2267801
• 关键词: Mapping; structural; functional; organisation; human

Project Description: (maximum of 4,000 characters)Please make sure this description clearly indicates how the project sits within the BBSRC remit, how it enables new ways of working and how it aligns with the DTP themes (World Class Underpinning Biosciences, Industrial Biotechnology and Bioenergy or Agriculture and Food Security). If you have been awarded an in vivo skills supplement, please outline the in vivo skills the student will learn during the project. The performance of the wide range of cognitive tasks including remembering, speaking, deciding and planning depends upon the interaction of complex networks of widely distributed brain regions. In order to increase our understanding of how the brain performs these tasks, it is important to understand not only what brain regions are involved but how these regions communicate with each other, that is, their connectivity. Network connectivity has recently been explored by two advanced techniques, one which examines the anatomical white matter pathways along which information flows (structural connectivity), and another which examines the brain regions which function together to perform components of a task (functional connectivity). However, how the different types of connectivity relate to each other is complex, and to fully understand how cognitive processes occur, an understanding of this relationship, and how the brain's anatomical structure influences functioning is crucial. Importantly, this knowledge is not only essential in understanding normal performance, but also its change across the lifespan, and observed impairments in different neurological diseases.In order to improve our understanding of the organization and function of normal and impaired brain networks, researchers have begun to model the brain using complex network analysis (CNA). CNA is a statistical approach which can be used to provide measures to characterise different properties of particular brain networks, such as the efficiency with which information can be communicated throughout the network, and how resilient the network is to damage.The current project aims to use CNA to map and describe the organisation of the brain's cognitive networks, and understand the relationship between behavioural performance and network architecture and functioning. In order to achieve this, CNA will be used to explore the relationship between structural and functional connectivity data, and their impact on behavioural performance. The project will utilise the wide range of behavioural and neuroimaging data available within the Division of Neuroscience and Experimental Psychology. This includes a range of sophisticated imaging methodologies, including diffusion imaging (capable of identifying the brain's structural connectivity), and functional MRI (capable of identifying functional connectivity), across a range of populations including both healthy individuals and those with a range of neurological impairment.The current project exploits new ways of combining of innovative imaging and quantitative computational/analysis technologies for analysing in vivo measures of structural and functional brain connectivity. In doing so, it will develop and provide training in the core bioscience skills of mathematics and data analysis, aligning with the theme of World Class Underpinning Bioscience. Higher cortical brain function requires the coordinated action of a network of brain regions. A step change in our understanding of the relationship between anatomical structure and brain function requires the development and application of techniques that probe brain-wide network organisation and interactions. The proposed research will align and develop complex network analysis of structural and functional connectivity information to reveal the neural networks that underpin specialised, higher cortical functions. This novel underpinning technology can then be applied to a range of populations, enabling innovatio

项目描述：（最多 4,000 个字符）请确保此描述清楚地表明该项目如何属于 BBSRC 的职权范围、如何实现新的工作方式以及如何与 DTP 主题（世界级基础生物科学、工业生物技术和生物能源或农业和粮食安全）保持一致。如果您获得了体内技能补充，请概述学生在项目期间将学习的体内技能。包括记忆、说话、决策和计划在内的广泛认知任务的表现取决于广泛分布的大脑区域的复杂网络的相互作用。为了加深我们对大脑如何执行这些任务的理解，重要的是不仅要了解涉及哪些大脑区域，还要了解这些区域如何相互通信，即它们的连接性。最近通过两种先进技术探索了网络连接，一种检查信息流动所沿的解剖白质通路（结构连接），另一种检查共同发挥作用以执行任务组成部分的大脑区域（功能连接）。然而，不同类型的连接如何相互关联是复杂的，要充分理解认知过程是如何发生的，了解这种关系以及大脑的解剖结构如何影响功能至关重要。重要的是，这些知识不仅对于理解正常表现至关重要，而且对于理解其在整个生命周期中的变化以及在不同神经系统疾病中观察到的损伤也至关重要。为了提高我们对正常和受损大脑网络的组织和功能的理解，研究人员已经开始使用复杂网络分析（CNA）对大脑进行建模。 CNA 是一种统计方法，可用于提供表征特定大脑网络不同属性的措施，例如通过网络传递信息的效率以及网络对损坏的恢复能力。当前项目旨在使用 CNA 来映射和描述大脑认知网络的组织，并了解行为表现与网络架构和功能之间的关系。为了实现这一目标，CNA 将用于探索结构和功能连接数据之间的关系及其对行为表现的影响。该项目将利用神经科学和实验心理学部门提供的广泛的行为和神经影像数据。这包括一系列复杂的成像方法，包括扩散成像（能够识别大脑的结构连接）和功能性 MRI（能够识别功能连接），适用于一系列人群，包括健康个体和患有一系列神经损伤的人。当前的项目探索了创新成像和定量计算/分析技术相结合的新方法，用于分析大脑结构和功能的体内测量 连接性。在此过程中，它将开发并提供数学和数据分析等核心生物科学技能的培训，与世界级基础生物科学的主题相一致。高级皮质脑功能需要大脑区域网络的协调行动。我们对解剖结构和大脑功能之间关系的理解的一步改变需要开发和应用探测全脑网络组织和相互作用的技术。拟议的研究将调整和开发结构和功能连接信息的复杂网络分析，以揭示支撑专门的高级皮层功能的神经网络。这种新颖的基础技术可以应用于一系列人群，从而实现创新