The plasticity of resting-state brain networks associated with motor imagery training in chronic stroke patients - 15/07/18

Résumé |
Introduction/Background |
Motor imagery training (MIT) is a widely used non-invasive treatment technique in stroke patients. Despite its clinical efficacy, little is known regarding the neural substrates underlying MIT. The aim of this study was to investigate the plasticity of resting-state brain networks associated with MIT in chronic stroke patients.
Material and method |
A total of 34 chronic stroke patients with subcortical lesions were randomly assigned to the conventional rehabilitation therapy (CRT) group and the MIT group. Before and after the 4-week treatment, motor function of each patient was blindly assessed with Fugl–Meyer assessment Scale (FM-UL) and resting-state fMRI was administered. Functional connectivity (FC) analyses of the ipsilesional primary motor cortex (M1), measurements of the lateralization index (LI) and graph-theory based analysis were also performed in both group to investigate the altered whole-brain networks after treatment.
Results |
Both groups showed significant improvement in FM-UL scores and the change in MIT group was significantly greater than that of the CRT group. Similar changes patterns of FC were seen between the MIT and CRT group: increased FC of the ipsilesional M1 with the contralesional precentral gyrus and decreased FC within ipsilesional hemisphere were found in both group. Additional increased FC of contralesional SMA and postcentral gyrus and restored LI were observed in MIT group. Moreover, a significant positive correlation between increase of clustering coefficient and improvement of FM-UL score were identified in MIT group as well (P<0.05).
Conclusion |
Our results indicate that the impact of MIT on the plasticity of brain networks was measurable on resting-state fMRI, and widely recruitment of the brain areas, restoring symmetry of the FC reflected by LI and increased clustering coefficients after treatment on a broader level of brain network analysis might be related to the neural mechanisms of motor recovery in stroke patients after MIT.
Le texte complet de cet article est disponible en PDF.Keywords : Motor imagery training, Resting-state brain networks, Neural mechanisms
Plan
Vol 61 - N° S
P. e20 - juillet 2018 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.