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Brain imaging of locomotion in neurological conditions

Authors :
Allali, Gilles
Blumen, Helena M.
Devanne, Herve
Pirondini, Elvira
Delval, Arnaud
Van De Ville, Dimitri
Allali, Gilles
Blumen, Helena M.
Devanne, Herve
Pirondini, Elvira
Delval, Arnaud
Van De Ville, Dimitri
Publication Year :
2019

Abstract

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. (C) 2018 Elsevier Masson SAS. All rights reserved.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1099240163
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.neucli.2018.10.004