Adam P Horin1, Peter S Myers2, Kristen A Pickett3, Gammon M Earhart4, Meghan C Campbell5. 1. Program in Physical Therapy, Washington University School of Medicine, St Louis, MO, United States. 2. Department of Neurology, Washington University School of Medicine, St Louis, MO, United States. 3. Occupational Therapy Program, Department of Kinesiology, University of Wisconsin-Madison, Madison, United States; Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States. 4. Program in Physical Therapy, Washington University School of Medicine, St Louis, MO, United States; Department of Neurology, Washington University School of Medicine, St Louis, MO, United States; Department of Neuroscience, Washington University School of Medicine, St Louis, MO, United States. 5. Department of Neurology, Washington University School of Medicine, St Louis, MO, United States; Department of Radiology, Washington University School of Medicine, St Louis, MO, United States. Electronic address: meghanc@wustl.edu.
Abstract
INTRODUCTION: Parkinson's disease (PD) is a movement disorder caused by dysfunction in the basal ganglia (BG). Clinically relevant gait deficits, such as decreased velocity and increased variability, may be caused by underlying neural dysfunction. Reductions in resting-state functional connectivity (rs-FC) between networks have been identified in PD compared to controls; however, the association between gait characteristics and rs-FC of brain networks in people with PD has not yet been explored. The present study aimed to investigate these associations. METHODS: Gait characteristics and rs-FC MRI data were collected for participants with PD (N = 50). Brain networks were identified from a set of seeds representing cortical, subcortical, and cerebellar regions. Gait outcomes were correlated with the strength of rs-FC within and between networks of interest. A stepwise regression analysis was also conducted to determine whether the rs-FC strength of brain networks, along with clinical motor scores, were predictive of gait characteristics. RESULTS: Gait velocity was associated with rs-FC within the visual network and between motor and cognitive networks, most notably BG-thalamus internetwork rs-FC. The stepwise regression analysis showed strength of BG-thalamus internetwork rs-FC and clinical motor scores were predictive of gait velocity. CONCLUSION: The results of the present study demonstrate gait characteristics are associated with functional organization of the brain at the network level, providing insight into the neural mechanisms of clinically relevant gait characteristics. This knowledge could be used to optimize the design of gait rehabilitation interventions for people with neurological conditions.
INTRODUCTION: Parkinson's disease (PD) is a movement disorder caused by dysfunction in the basal ganglia (BG). Clinically relevant gait deficits, such as decreased velocity and increased variability, may be caused by underlying neural dysfunction. Reductions in resting-state functional connectivity (rs-FC) between networks have been identified in PD compared to controls; however, the association between gait characteristics and rs-FC of brain networks in people with PD has not yet been explored. The present study aimed to investigate these associations. METHODS: Gait characteristics and rs-FC MRI data were collected for participants with PD (N = 50). Brain networks were identified from a set of seeds representing cortical, subcortical, and cerebellar regions. Gait outcomes were correlated with the strength of rs-FC within and between networks of interest. A stepwise regression analysis was also conducted to determine whether the rs-FC strength of brain networks, along with clinical motor scores, were predictive of gait characteristics. RESULTS: Gait velocity was associated with rs-FC within the visual network and between motor and cognitive networks, most notably BG-thalamus internetwork rs-FC. The stepwise regression analysis showed strength of BG-thalamus internetwork rs-FC and clinical motor scores were predictive of gait velocity. CONCLUSION: The results of the present study demonstrate gait characteristics are associated with functional organization of the brain at the network level, providing insight into the neural mechanisms of clinically relevant gait characteristics. This knowledge could be used to optimize the design of gait rehabilitation interventions for people with neurological conditions.
Authors: Robert L White; Meghan C Campbell; Dake Yang; William Shannon; Abraham Z Snyder; Joel S Perlmutter Journal: Mov Disord Date: 2019-12-19 Impact factor: 10.338
Authors: Benjamin A Seitzman; Caterina Gratton; Scott Marek; Ryan V Raut; Nico U F Dosenbach; Bradley L Schlaggar; Steven E Petersen; Deanna J Greene Journal: Neuroimage Date: 2019-10-18 Impact factor: 6.556