School of Kinesiology, University of British Columbia, Vancouver, BC, Canada.
Pacific Parkinson's Research Centre, Vancouver, BC, Canada.
Neuroimage Clin. 2021;30:102676. doi: 10.1016/j.nicl.2021.102676. Epub 2021 Apr 16.
Individuals with Parkinson's disease often experience postural instability, a debilitating and largely treatment-resistant symptom. A better understanding of the neural substrates contributing to postural instability could lead to more effective treatments. Constraints of current functional neuroimaging techniques, such as the horizontal orientation of most MRI scanners (forcing participants to lie supine), complicates investigating cortical and subcortical activation patterns and connectivity networks involved in healthy and parkinsonian balance control. In this cross-sectional study, we utilized a newly-validated MRI-compatible balance simulator (based on an inverted pendulum) that enabled participants to perform balance-relevant tasks while supine in the scanner. We utilized functional MRI to explore effective connectivity underlying static and dynamic balance control in healthy older adults (n = 17) and individuals with Parkinson's disease while on medication (n = 17). Participants performed four tasks within the scanner with eyes closed: resting, proprioceptive tracking of passive ankle movement, static balancing of the simulator, and dynamic responses to random perturbations of the simulator. All analyses were done in the participant's native space without spatial transformation to a common template. Effective connectivity between 57 regions of interest was computed using a Bayesian Network learning approach with false discovery rate set to 5%. The first 12 principal components of the connection weights, binomial logistic regression, and cross-validation were used to create 4 separate models: contrasting static balancing vs {rest, proprioception} and dynamic balancing vs {rest, proprioception} for both controls and individuals with Parkinson's disease. In order to directly compare relevant connections between controls and individuals with Parkinson's disease, we used connections relevant for predicting a task in either controls or individuals with Parkinson's disease in logistic regression with Least Absolute Shrinkage and Selection Operator regularization. During dynamic balancing, we observed decreased connectivity between different motor areas and increased connectivity from the brainstem to several cortical and subcortical areas in controls, while individuals with Parkinson's disease showed increased connectivity associated with motor and parietal areas, and decreased connectivity from brainstem to other subcortical areas. No significant models were found for static balancing in either group. Our results support the notion that dynamic balance control in individuals with Parkinson's disease relies more on cortical motor areas compared to healthy older adults, who show a preference of subcortical control during dynamic balancing.
帕金森病患者通常会出现姿势不稳的情况，这是一种使人虚弱且在很大程度上难以治疗的症状。如果能更深入地了解导致姿势不稳的神经基础，或许就能找到更有效的治疗方法。目前的功能神经影像学技术存在一定的局限性，例如大多数磁共振成像（MRI）扫描仪的水平方位（迫使参与者仰卧），这使得研究健康人和帕金森病患者的平衡控制所涉及的皮质和皮质下激活模式和连接网络变得复杂。在这项横断面研究中，我们使用了一种新验证的、兼容 MRI 的平衡模拟器（基于倒立摆），使参与者能够在扫描仪中仰卧时进行与平衡相关的任务。我们利用功能磁共振成像（fMRI）技术来探索健康老年人（n=17）和正在接受药物治疗的帕金森病患者（n=17）在进行静态和动态平衡控制时的有效连接。参与者在扫描仪内闭眼完成四项任务：休息、被动脚踝运动的本体感觉跟踪、模拟器的静态平衡和模拟器随机扰动的动态响应。所有分析都是在参与者的原始空间中进行的，而无需转换到公共模板。使用贝叶斯网络学习方法计算了 57 个感兴趣区域之间的有效连接，并将假发现率设置为 5%。使用连接权重的前 12 个主成分、二项逻辑回归和交叉验证创建了 4 个单独的模型：将静态平衡与{休息、本体感觉}进行对比，将动态平衡与{休息、本体感觉}进行对比，分别用于健康对照组和帕金森病患者。为了直接比较健康对照组和帕金森病患者之间的相关连接，我们使用在健康对照组或帕金森病患者中预测任务的相关连接，在逻辑回归中使用最小绝对值收缩和选择算子正则化。在动态平衡中，我们观察到健康对照组不同运动区域之间的连接减少，而脑干与几个皮质和皮质下区域的连接增加，而帕金森病患者表现出与运动和顶叶区域相关的连接增加，以及与其他皮质下区域的连接减少。在两组中都没有找到与静态平衡相关的显著模型。我们的研究结果支持这样一种观点，即帕金森病患者的动态平衡控制更多地依赖于皮质运动区域，而健康老年人在进行动态平衡时则更喜欢皮质下控制。
