Hannanu Fabrice F, Goundous Issa, Detante Olivier, Naegele Bernadette, Jaillard Assia
AGEIS, EA 7407, Université Grenoble Alpes, Grenoble, France.
Stroke Unit, Neurologie, Centre Hospitalier Universitaire Grenoble Alpes (CHUGA), Grenoble, France.
Cortex. 2020 Aug;129:80-98. doi: 10.1016/j.cortex.2020.03.024. Epub 2020 Apr 17.
Motor hand deficits impact autonomy in everyday life, and neuroplasticity processes of motor recovery can be explored using functional MRI (fMRI). However, few studies have used fMRI to explore the mechanisms underlying hand recovery following stroke. Based on the dual visuomotor model positing that two segregated dorsomedial and dorsolateral cerebral networks control reach and grasp movements, we explored the relationship between motor task-related activity in the sensorimotor network and hand recovery following stroke. Behavioral recovery was explored with a handgrip force task assessing simple grasp, and a visuomotor reaching and precise grasping task, the Purdue Pegboard Test (PPT). We used a passive wrist flexion-extension task to measure fMRI activity in 36 sensorimotor brain areas. Behavioral and fMRI measurements were performed in 27 patients (53.2 ± 9.5 years) 1-month following stroke, and then 6-month and 24-month later. The effects of sensorimotor activity on hand recovery were analyzed using correlations and linear mixed models (LMMs). PPT and handgrip force correlated with fMRI activity measures in the sensorimotor and parietal areas. PPT recovery was modeled by fMRI measures in the ipsilesional primary motor cortex (MI-4p), superior parietal lobule (SPL-7M) and parietal operculum OP1, and lesion side. Handgrip force was modeled by ipsilesional MI-4a, OP1, and contralesional inferior parietal lobule (IPL-PFt). Moreover, the relationship between fMRI activity and hand recovery was time-dependent, occurring in the early recovery period in SPL-BA-7M, and later in MI. These results suggest that areas of both dorsolateral and dorsomedial networks participate to visuomotor reach and grasp tasks (PPT), while dorsolateral network areas may control recovery of simple grasp (handgrip force), suggesting that the type of movement modulates network recruitment. We also found functional dissociations between MI-4p related to PPT that required independent finger movements and MI-4a related to simple grasp without independent finger movements. These findings need to be replicated in further studies.
手部运动功能障碍会影响日常生活中的自主性，利用功能磁共振成像（fMRI）可以探究运动恢复的神经可塑性过程。然而，很少有研究使用fMRI来探究中风后手功能恢复的潜在机制。基于双视觉运动模型，即两个分离的背内侧和背外侧脑网络控制伸展和抓握运动，我们探究了感觉运动网络中与运动任务相关的活动与中风后手功能恢复之间的关系。通过握力任务评估简单抓握，并使用视觉运动伸展和精确抓握任务——普渡钉板测试（PPT）来探究行为恢复情况。我们使用被动腕屈伸任务来测量36个感觉运动脑区的fMRI活动。在27例患者（53.2±9.5岁）中风后1个月、6个月和24个月时进行行为和fMRI测量。使用相关性分析和线性混合模型（LMMs）分析感觉运动活动对手功能恢复的影响。PPT和握力与感觉运动区和顶叶区的fMRI活动测量值相关。PPT恢复情况可通过患侧初级运动皮层（MI-4p）、顶上小叶（SPL-7M）、顶叶岛盖OP1以及病变侧的fMRI测量值进行建模。握力可通过患侧MI-4a、OP1以及对侧下顶叶（IPL-PFt）进行建模。此外，fMRI活动与手功能恢复之间的关系具有时间依赖性，在SPL-BA-7M的早期恢复阶段出现，而在MI中则出现在后期。这些结果表明，背外侧和背内侧网络区域均参与视觉运动伸展和抓握任务（PPT），而背外侧网络区域可能控制简单抓握（握力）的恢复，这表明运动类型会调节网络募集。我们还发现，与需要独立手指运动的PPT相关的MI-4p和与无独立手指运动的简单抓握相关的MI-4a之间存在功能分离。这些发现需要在进一步的研究中进行重复验证。
