Making the connection: Methods to infer functional connectivity in brain studies

建立联系：推断大脑研究中功能连接的方法

• 批准号: 323602-2006
• 负责人: McKeown, Martin
• 金额: $ 4.65万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Collaborative Health Research Projects
• 财政年份: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=324896
• 关键词: Making; connection; Methods; infer; functional

In Parkinson's disease (PD), a common neurodegenerative disorder, there is discordance between brain cell loss and clinical disability because substantial compensatory mechanisms occur in PD, minimizing overall impairment. Thus measures of altered brain activity in PD are a product of both disease and compensatory processes, and disentangling these effects, while vital for understanding the mechanisms of disability, remains a challenge. As there is increasing evidence that normal and diseased brain functioning differ by altered patterns of dynamic connectivity between brain regions, it is critical to develop models assessing connectivity  using current technologies available for non-invasively assessing PD subjects, i.e. fMRI and EEG. Our specific aims are to isolate disease effects from compensatory mechanisms and to determine the effects of medication (L-Dopa) in PD across 3 main domains: Connectivity, Spatial Extent of Activity, and Temporal Dynamics. This joint initiative between UBC, SFU and UNC represents a new collaboration between clinician-scientists treating and performing fMRI research in PD (Drs. McKeown and Huang); scientists with expertise in brain segmentation and shape analysis (Drs. Abugharbieh and Beg), as well as network modeling & statistical inference (Dr. Wang).  The proposed research consists of the following technical components: 1.) Extend the newly developed dynamic causal models (DCM) for brain effective connectivity; 2.) Provide quantitative analysis of the spatial characteristics of fMRI activation; 3.) Determine the sensitivity of network models to mis-specification of manually-drawn regions of interest; and 4.) Expand Blind Source Separation (BSS) methods to the EEG data to infer transient synchronization between brain areas. This cross-disciplinary research effort has significant impact because it will advance understanding of both disease progression and the compensatory changes, and the developed methods will be widely applicable to other brain diseases.  Also, the Canadian pharmaceutical industry would substantially benefit from a means to differentiate between neuroprotective and symptomatic effects of novel therapies.

在帕金森病（PD）这种常见的神经退行性疾病中，脑细胞损失和临床残疾之间存在不一致，因为帕金森病中会出现大量的补偿机制，从而最大限度地减少总体损害。因此，帕金森病中大脑活动改变的测量是疾病和代偿过程的产物，解开这些影响虽然对于理解残疾机制至关重要，但仍然是一个挑战。越来越多的证据表明，正常和患病的大脑功能因大脑区域之间动态连接模式的改变而有所不同，因此使用当前可用于非侵入性评估 PD 受试者的技术（即功能磁共振成像和脑电图）来开发评估连接性的模型至关重要。我们的具体目标是将疾病影响与代偿机制分开，并确定药物（左旋多巴）在 3 个主要领域对 PD 的影响：连通性、活动的空间范围和时间动力学。 UBC、SFU 和 UNC 之间的这项联合倡议代表了治疗 PD 和进行功能磁共振成像研究的临床医生与科学家之间的新合作（McKeown 博士和 Huang 博士）；拥有大脑分割和形状分析（Abugharbieh 博士和 Beg 博士）以及网络建模和统计推断（Wang 博士）方面专业知识的科学家。  拟议的研究由以下技术组成部分组成：1.）扩展新开发的动态因果模型（DCM）以实现大脑有效连接； 2.) 提供fMRI激活空间特征的定量分析； 3.) 确定网络模型对手动绘制的感兴趣区域的错误指定的敏感性； 4.) 将盲源分离 (BSS) 方法扩展到脑电图数据，以推断大脑区域之间的瞬态同步。这项跨学科的研究工作具有重大影响，因为它将促进对疾病进展和代偿性变化的理解，并且所开发的方法将广泛适用于其他脑部疾病。  此外，加拿大制药业也将受益于区分新疗法的神经保护作用和症状作用的方法。