fMRI as a molecular imaging procedure for the functional reorganization of motor systems in chronic stroke
Asimina Lazaridou, Loukas G. Astrakas, Dionyssios Mintzopoulos, AZADEH KHANCHICEH, Aneesh B. Singhal, Michael A. Moskowitz, Bruce R. Rosen, A. Aria Tzika
- 发表年份
- 2013
- 引用次数
- 30
- 访问权限
- 开放获取
摘要
Previous brain imaging studies suggest that stroke alters functional connectivity in motor execution networks. Moreover, current understanding of brain plasticity has led to new approaches in stroke rehabilitation. Recent studies showed a significant role of effective coupling of neuronal activity in the SMA (supplementary motor area) and M1 (primary motor cortex) network for motor outcome in patients after stroke. After a subcortical stroke, functional magnetic resonance imaging (fMRI) during movement reveals cortical reorganization that is associated with the recovery of function. The aim of the present study was to explore connectivity alterations within the motor-related areas combining motor fMRI with a novel MR-compatible hand-induced robotic device (MR_CHIROD) training. Patients completed training at home and underwent serial MR evaluation at baseline and after 8 weeks of training. Training at home consisted of squeezing a gel exercise ball with the paretic hand at ~75% of maximum strength for 1 h/day, 3 days/week. The fMRI analysis revealed alterations in M1, SMA, PMC (premotor cortex) and Cer (cerebellum) in both stroke patients and healthy controls after the training. Findings of the present study suggest that enhancement of SMA activity could benefit M1 dysfunction in stroke survivors. These results also indicate that connectivity alterations between motor areas might assist the counterbalance of a functionally abnormal M1 in chronic stroke survivors and possibly other patients with motor dysfunction.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992