Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA; Department of Medicine, Division of Geriatrics, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
Neurophysiol Clin. 2018 Dec;48(6):337-359. doi: 10.1016/j.neucli.2018.10.004. Epub 2018 Oct 25.
Impaired locomotion is a frequent and major source of disability in patients with neurological conditions. Different neuroimaging methods have been used to understand the brain substrates of locomotion in various neurological diseases (mainly in Parkinson's disease) during actual walking, and while resting (using mental imagery of gait, or brain-behavior correlation analyses). These studies, using structural (i.e., MRI) or functional (i.e., functional MRI or functional near infra-red spectroscopy) brain imaging, electrophysiology (i.e., EEG), non-invasive brain stimulation (i.e., transcranial magnetic stimulation, or transcranial direct current stimulation) or molecular imaging methods (i.e., PET, or SPECT) reveal extended brain networks involving both grey and white matters in key cortical (i.e., prefrontal cortex) and subcortical (basal ganglia and cerebellum) regions associated with locomotion. However, the specific roles of the various pathophysiological mechanisms encountered in each neurological condition on the phenotype of gait disorders still remains unclear. After reviewing the results of individual brain imaging techniques across the common neurological conditions, such as Parkinson's disease, dementia, stroke, or multiple sclerosis, we will discuss how the development of new imaging techniques and computational analyses that integrate multivariate correlations in "large enough datasets" might help to understand how individual pathophysiological mechanisms express clinically as an abnormal gait. Finally, we will explore how these new analytic methods could drive our rehabilitative strategies.
运动障碍是神经系统疾病患者经常出现的主要致残原因。为了在实际行走和静息状态下(通过步态想象或脑-行为相关分析)了解不同神经疾病(主要是帕金森病)中的运动大脑基础,已经使用了不同的神经影像学方法。这些研究使用结构(例如 MRI)或功能(例如 fMRI 或功能近红外光谱)脑成像、电生理学(例如 EEG)、非侵入性脑刺激(例如经颅磁刺激或经颅直流电刺激)或分子成像方法(例如 PET 或 SPECT),揭示了涉及关键皮质(例如前额叶皮质)和皮质下区域(基底节和小脑)的广泛脑网络与运动有关。然而,每种神经疾病中遇到的各种病理生理机制对步态障碍表型的具体作用仍不清楚。在回顾了常见神经疾病(如帕金森病、痴呆、中风或多发性硬化症)中各种脑成像技术的结果后,我们将讨论如何通过开发新的成像技术和计算分析来整合“足够大的数据集”中的多元相关性,以帮助了解个体病理生理机制如何在临床上表现为异常步态。最后,我们将探讨这些新的分析方法如何推动我们的康复策略。