LREN, Department of clinical neurosciences - CHUV, University Lausanne, Switzerland.
Max-Planck Institute for Human Brain and Cognitive Sciences, Leipzig, German; Department of Gerontopsychiatry, Psychosomatic Medicine, and Psychotherapy, Pfalzklinikum, Klingenmünster, Germany; Institute of Psychology, Goethe-University, Frankfurt am Main, Germany.
Neuroimage. 2021 Apr 1;229:117735. doi: 10.1016/j.neuroimage.2021.117735. Epub 2021 Jan 14.
There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force.
Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content.
The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections.
We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.
关于皮质和皮质下脑区在力调制中的作用，目前仍存在争议。在全脑研究方法中，我们旨在研究抓握力的解剖学基础，同时承认个体间连接模式的差异。我们测试了大脑病变图在单侧运动缺陷患者中的作用，是否可以为健康对照组的全脑结构连接分析提供信息，以揭示抓握力的网络基础。
我们使用磁共振成像（MRI）和慢性中风患者（n=55）和健康对照组（n=67）的全脑基于体素形态学方法，确定了灰质和白质中与抓握力强度显著相关的脑区。所得的统计参数图（SPM）为大规模社区居住队列（n=977）的全脑结构协方差分析提供了种子区域，该队列包括体积估计之外，对髓鞘、铁和组织含水量敏感的参数图。
SPM 显示了上肢运动表现、基底节、后岛和皮质脊髓束之间存在双侧对称的相关性簇。用 SPM 获得的种子区域进行的协方差分析表明，大脑体积和组织特性存在广泛的解剖模式，包括皮质、皮质下运动网络节点和感觉运动区投射。
我们将协方差结果解释为涉及抓握力的大脑网络的生物学特征。从慢性中风患者中获得的基于数据驱动的种子区域定义显示了不同组织特性估计下皮质下运动网络内的重叠结构协方差模式。这些累积证据为我们的发现提供了表面有效性及其生物学合理性。
