BACKGROUND: Motor improvement post-stroke may happen even if resting state functional connectivity between the ipsilesional and contralesional components of the sensorimotor network is not fully recovered. Therefore, we investigated which extra-motor networks might support upper limb motor gains in response to treatment post-stroke. METHODS: Both resting state functional connectivity and upper limb capacity were measured prior to and after an 8-week intervention of task-specific training in 29 human participants [59.24 ± (SD) 10.40 yrs., 12 females and 17 males] with chronic stroke. The sensorimotor and five extra-motor networks were defined: default mode, frontoparietal, cingulo-opercular, dorsal attention network, and salience networks. The Network Level Analysis toolbox was used to identify network pairs whose connectivities were enriched in connectome-behavior relationships. RESULTS: Mean upper limb capacity score increased 5.45 ± (SD) 5.55 following treatment. Baseline connectivity of some motor but mostly extra-motor network interactions of cingulo-opercular and default-mode networks were predictive of upper limb capacity following treatment. Also, changes in connectivity for extra-motor interactions of salience with default mode, cingulo-opercular, and dorsal attention networks were correlated with gains in upper limb capacity. CONCLUSIONS: These connectome-behavior patterns suggest larger involvement of cingulo-opercular networks in prediction of treatment response and of salience networks in maintenance of improved skilled behavior. These results support our hypothesis that cognitive networks may contribute to recovery of motor performance after stroke and provide additional insights into the neural correlates of intensive training.
The Role of Extra-motor Networks in Upper Limb Motor Performance Post-stroke.
中风后上肢运动功能中运动外网络的作用
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作者:Mattos Daniela J S, Rutlin Jerrel, Hong Xin, Zinn Kristina, Shimony Joshua S, Carter Alexandre R
| 期刊: | Neuroscience | 影响因子: | 2.800 |
| 时间: | 2023 | 起止号: | 2023 Mar 15; 514:1-13 |
| doi: | 10.1016/j.neuroscience.2023.01.033 | ||
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