Dynamic analysis of the ageing functional brain

大脑老化功能的动态分析

• 批准号: 2725895
• 金额: --
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2725895
• 关键词: Dynamic; analysis; ageing; functional; brain

Dynamic functional connectivity (dFC) in resting-state fMRI holds promise to delivercandidate biomarkers for prediction of brain function in health and disease. However,the reliability and interpretability of dFC metrics remain contested. Moreover, thesehave not been properly validated in a pre-clinical context (e.g. rodents) and integratedwith ancillary neurobiological endpoints. Using a complexity-science approach, theproject will quantify brain function using a large battery of phase-based dFC metrics.These will include tools originated from dynamical systems, stochastic and informationdynamics approaches. Moreover, these metrics will be used to form novel descriptionsof rodent brain function during the life-cycle at the meso- and macro-scale. We are in aunique position to fulfil the ambition of this project as, thanks to a 3-year BBSRCfunded project, we have already completed the longitudinal acquisition of structuraland functional MRI data over n=70 rats that were followed for two years with at least 4imaging points each. An "active lifestyle" sub-group also underwent environmentalenrichment and dietary restriction between their early and late life. We have alreadyshown that machine learning applied to structural data can predict life-span in thiscohort (Busini et al., 2022). We now plan to develop even more accurate predictorsfrom fMRI data. The PhD student will have the support of the staff of the NeuroimagingDepartment and of BRAIN, our preclinical imaging centre and in particular. 1stSupervisor: Prof Turkheimer has a focused interest in the development of brainfunctional markers and leads experimentation, data acquisition and analytics in thisarea. 2nd Supervisor: Dr Paul Expert is a physicist with an interest in complex systemsand modelling of brain function using networks and statistical learning 3rd Supervisor:Dr Diana Cash is preclinical scientist and expert in MRI, PET and methods such asbehaviour, histology, and autoradiography in rodents

静息态功能磁共振成像中的动态功能连接（dFC）有望为预测健康和疾病中的脑功能提供候选生物标志物。然而，dFC指标的可靠性和可解释性仍然存在争议。此外，这些尚未在临床前环境（例如啮齿动物）中得到适当验证，并与辅助神经生物学终点相结合。使用复杂性科学方法，该项目将使用大量基于相位的dFC度量来量化大脑功能。这些度量将包括源自动力系统，随机和信息动力学方法的工具。此外，这些指标将用于形成啮齿动物脑功能在生命周期中在中观和宏观尺度的新的promistionsof。我们处于一个独特的位置，以实现这个项目的野心，由于一个为期3年的BBSRC资助的项目，我们已经完成了纵向采集的结构和功能MRI数据超过n=70大鼠，被跟踪了两年，至少有4个成像点。一个“积极的生活方式”小组也经历了环境丰富和饮食限制之间的早期和晚期生活。我们已经证明，应用于结构数据的机器学习可以预测该队列的寿命（Busini等人，2022年）。我们现在计划从功能磁共振成像数据中开发更准确的预测器。博士生将得到NeuroimagingDepartment和BRAIN（我们的临床前成像中心）工作人员的支持。第一主管：Turkheimer教授专注于脑功能标记物的开发，并领导该领域的实验，数据采集和分析。第二监督员：Paul Expert博士是一位物理学家，对复杂系统以及使用网络和统计学习进行大脑功能建模感兴趣第三主管：Diana Cash博士是临床前科学家，也是MRI、PET以及啮齿动物行为、组织学和放射自显影等方法的专家