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

帕金森氏病（PD）是一种常见的神经退行性疾病，由于PD中存在大量代偿机制，使整体损害最小化，因此脑细胞损失与临床残疾之间存在不一致。因此，PD患者脑活动改变的测量是疾病和代偿过程的产物，解开这些影响对理解残疾机制至关重要，但仍然是一个挑战。由于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，利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）开发评估连接的模型至关重要。我们的具体目标是将疾病效应从代偿机制中分离出来，并确定药物（左旋多巴）在PD中三个主要领域的作用：连通性、活动的空间范围和时间动力学。UBC， SFU和UNC之间的联合倡议代表了临床科学家在PD治疗和执行fMRI研究之间的新合作。McKeown and Huang)；在大脑分割和形状分析方面具有专长的科学家(dr。Abugharbieh和Beg)，以及网络建模和统计推断（王博士）。建议的研究包括以下技术部分：1.)扩展新开发的脑有效连接动态因果模型（DCM）；2)。对fMRI激活的空间特征进行定量分析；3)。确定网络模型对手工绘制的感兴趣区域的错误说明的敏感性；和4)。将盲源分离（BSS）方法扩展到脑电数据中，推断脑区之间的瞬态同步。这一跨学科的研究工作具有重要的影响，因为它将促进对疾病进展和代偿变化的理解，并且所开发的方法将广泛适用于其他脑部疾病。此外，加拿大制药业将从一种区分新疗法的神经保护作用和症状作用的方法中获益。

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.