Intrinsic Activity and Cognition in Parkinson Disease Assessed by Simultaneous fMRI/EEG

认知障碍是帕金森病(PD)最致残的非运动功能，并导致 最大程度的照顾者痛苦。绝大多数帕金森病患者最终将遭受认知障碍 虽然运动性帕金森症的治疗有所改善，但认知障碍已被证明 更难治疗。当认知障碍出现时，它往往具有受影响更大、受影响更小的特征。 受影响的区域表明不同的区域皮质参与。认知测量 通过神经心理测试的表现可以告诉我们哪些功能受损，但不能告诉我们为什么。更好的 了解损害的原因将有助于确定认知症状的治疗目标。这 将为开发脑(病理)生理学的生物标记物奠定基础，从而推进 治疗帕金森病的精准药物。这个项目利用了这样一个发现，即区域自发的大脑皮层 由fMRI测量的静息活动具有空间结构，该空间结构包括识别的相同认知网络 在任务期间。这些“内在网络”在帕金森病和许多其他疾病中会发生改变，提供了一个重要的 大脑结构和认知功能之间的生理联系。我们已经开发了基于fMRI的 灵敏地量化内在网络差异的方法，并表明人与人之间的网络不同 带着警局和控制组。虽然fmri具有良好的空间分辨率，但由于血流动力学延迟，它缺乏。 时间分辨率。因此，在PD中观察到的网络差异可能反映了时间上的差异，或者 动力学，我们无法在fMRI的时间分辨率下进行测量。我们希望将我们的创新 具有补充模式的框架，脑电(EEG)，它帮助我们区分 网络的空间范围和时间上的差异。最近，我们已经显示出一种系统的关系 注意网络活动与注意网络任务的时间进程之间的关系 控制。内在网络和与任务相关的活动之间的这种联系让我们可以问，内在网络是如何 帕金森病患者的活动与认知有关。我们假设，支持注意力的网络的变化 记忆与帕金森病患者在这些领域的认知表现特别相关，而时间 来自EEG的信息将有助于解决这一问题。我们将通过同时获取功能磁共振成像来验证这一假设 数据(用于网络结构的高空间局部化)和脑电(EEG)数据(用于高 时间分辨率)在帕金森病患者和对照组中，我们追求以下特定目标：(1)分析 并比较帕金森病患者和对照组在休息时的内在活动。(2)分析比较内在活跃性 在有和没有记忆负荷的隐蔽视觉空间注意任务中，来自PD和控制组。(3)分析 纵向变化的轨迹。

Cognitive impairment is the most disabling non-motor feature of Parkinson Disease (PD) and causes the greatest degree of caregiver distress. The large majority of patients with PD will eventually suffer cognitive impairment, and although treatment of motor parkinsonism has improved, cognitive impairment has proven more difficult to treat. When cognitive impairment appears, it tends to have a profile of more affected and less affected domains that suggests differential regional cortical involvement. Measurement of cognitive performance through neuropsychological tests tells us what functions are impaired but not why. A better understanding of the causes of impairment would help identify therapeutic targets for cognitive symptoms. This would lay the groundwork for developing biomarkers of brain (patho)physiology that would advance the goal of precision medicine for treatment of PD. This project exploits the discovery that regional spontaneous cortical activity measured by fMRI at rest has a spatial structure that includes the same cognitive networks identified during tasks. These “intrinsic networks” are altered in PD and many other diseases, providing an important physiological connection between brain structure and cognitive function. We have developed fMRI-based methods for sensitively quantifying differences in intrinsic networks and shown that networks differ in people with PD and controls. Although fMRI has good spatial resolution, because of hemodynamic delay it lacks temporal resolution. Therefore, differences in networks observed in PD may reflect differences in timing, or dynamics, that we cannot measure at the temporal resolution of fMRI. We want to integrate our innovative framework with a complementary modality, electroencephalography (EEG), which helps us to distinguish differences in spatial extent and timing of networks. Recently, we have shown a systematic relationship between intrinsic network activity and the time course of an attention network task that is different in PD and controls. This link between intrinsic networks and task-related activity allows us to ask how intrinsic network activity relates to cognition in PD. We hypothesize that alterations to networks that support attention and memory are specifically related to cognitive performance in these domains in PD, and that temporal information from EEG will help to resolve this. We will test this hypothesis by simultaneously acquiring fMRI data (for high spatial localization of network structure) and electroencephalography (EEG) data (for high temporal resolution) in subjects with PD and controls, as we pursue the following specific aims: (1) Analyze and compare intrinsic activity from PD and controls obtained at rest. (2) Analyze and compare intrinsic activity from PD and controls during a covert visuospatial attention task with and without a memory load. (3) Analyze trajectories of longitudinal change.