Gilles Allali1,2, Maxime Montembeault3,4, Simona M Brambati3, Louis Bherer3,5, Helena M Blumen6, Cyrille P Launay7, Teresa Liu-Ambrose8, Jorunn L Helbostad9, Joe Verghese6, Olivier Beauchet10,11,12. 1. Department of Neurology, Geneva University Hospital, University of Geneva, Switzerland. 2. Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, New York. 3. Centre de recherche de l'Institut universitaire de gériatrie de Montréal, Quebec, Canada. 4. Département de psychologie, Institut de cardiologie de Montréal et centre EPIC, Université de Montreal, Quebec, Canada. 5. Département de Médecine, Institut de cardiologie de Montréal et centre EPIC, Université de Montreal, Quebec, Canada. 6. Departments of Neurology and Medicine, Albert Einstein College of Medicine, Bronx, New York. 7. Division of Geriatric Medicine and Geriatric Rehabilitation, Department of Medicine, Lausanne University Hospital, Switzerland. 8. Aging, Mobility and Cognitive Neuroscience Laboratory, University of British Columbia, Vancouver, Canada. 9. Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway. 10. Department of Medicine, Division of Geriatric Medicine, Sir Mortimer B. Davis - Jewish General Hospital and Lady Davis Institute for Medical Research, Montreal, Quebec, Canada. 11. Dr. Joseph Kaufmann Chair in Geriatric Medicine, Faculty of Medicine, McGill University, Montreal, Quebec, Canada. 12. Centre of Excellence on Aging and Chronic Diseases of McGill Integrated University Health Network, Montreal, Quebec, Canada.
Abstract
BACKGROUND: Structural and functional brain imaging methods have identified age-related changes in brain structures involved in gait control. This cross-sectional study aims to investigate gray matter networks associated with gait control in aging using structural covariance analysis. METHODS: Walking speed were measured in 326 nondemented older community-dwellers (age 71.3 ± 4.5; 41.7% female) under three different walking conditions: normal walking and two challenging tasks: motor (ie, fast speed) and an attention-demanding dual task (ie, backward counting). RESULTS: Three main individual gray matter regions were positively correlated with walking speed (ie, slower walking speed was associated with lower brain volumes): right thalamus, right caudate nucleus, and left middle frontal gyrus for normal walking, rapid walking, and dual-task walking condition, respectively. The structural covariance analysis revealed that prefrontal regions were part of the networks associated with every walking condition; the right caudate was associated specifically with the hippocampus, amygdala and insula for the rapid walking condition, and the left middle frontal gyrus with a network involving the cuneus for the dual-task condition. CONCLUSION: Our results suggest that brain networks associated with gait control vary according to walking speed and depend on each walking condition. Gait control in aging involved a distributed network including regions for emotional control that are recruited in challenging walking conditions.
BACKGROUND: Structural and functional brain imaging methods have identified age-related changes in brain structures involved in gait control. This cross-sectional study aims to investigate gray matter networks associated with gait control in aging using structural covariance analysis. METHODS: Walking speed were measured in 326 nondemented older community-dwellers (age 71.3 ± 4.5; 41.7% female) under three different walking conditions: normal walking and two challenging tasks: motor (ie, fast speed) and an attention-demanding dual task (ie, backward counting). RESULTS: Three main individual gray matter regions were positively correlated with walking speed (ie, slower walking speed was associated with lower brain volumes): right thalamus, right caudate nucleus, and left middle frontal gyrus for normal walking, rapid walking, and dual-task walking condition, respectively. The structural covariance analysis revealed that prefrontal regions were part of the networks associated with every walking condition; the right caudate was associated specifically with the hippocampus, amygdala and insula for the rapid walking condition, and the left middle frontal gyrus with a network involving the cuneus for the dual-task condition. CONCLUSION: Our results suggest that brain networks associated with gait control vary according to walking speed and depend on each walking condition. Gait control in aging involved a distributed network including regions for emotional control that are recruited in challenging walking conditions.
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