Kadry Ashraf, Solomonow-Avnon Deborah, Norman Sumner L, Xu Jing, Mawase Firas
Faculty of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel.
Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States of America.
J Neural Eng. 2024 Nov 15;21(6). doi: 10.1088/1741-2552/ad8961.
Finger dexterity, and finger individuation in particular, is crucial for human movement, and disruptions due to brain injury can significantly impact quality of life. Understanding the neurological mechanisms responsible for recovery is vital for effective neurorehabilitation. This study explores the role of two key pathways in finger individuation: the corticospinal (CS) tract from the primary motor cortex and premotor areas, and the subcortical reticulospinal (RS) tract from the brainstem. We aimed to investigate how the cortical-reticular network reorganizes to aid recovery of finger dexterity following lesions in these areas.To provide a potential biologically plausible answer to this question, we developed an artificial neural network (ANN) to model the interaction between a premotor planning layer, a cortical layer with excitatory and inhibitory CS outputs, and RS outputs controlling finger movements. The ANN was trained to simulate normal finger individuation and strength. A simulated stroke was then applied to the CS area, RS area, or both, and the recovery of finger dexterity was analyzed.In the intact model, the ANN demonstrated a near-linear relationship between the forces of instructed and uninstructed fingers, resembling human individuation patterns. Post-stroke simulations revealed that lesions in both CS and RS regions led to increased unintended force in uninstructed fingers, immediate weakening of instructed fingers, improved control during early recovery, and increased neural plasticity. Lesions in the CS region alone significantly impaired individuation, while RS lesions affected strength and to a lesser extent, individuation. The model also predicted the impact of stroke severity on finger individuation, highlighting the combined effects of CS and RS lesions.This model provides insights into the interactive role of cortical and subcortical regions in finger individuation. It suggests that recovery mechanisms involve reorganization of these networks, which may inform neurorehabilitation strategies.
手指灵活性，尤其是手指的个体化控制，对于人类活动至关重要，脑损伤导致的功能障碍会显著影响生活质量。了解负责恢复的神经机制对于有效的神经康复至关重要。本研究探讨了两条关键通路在手指个体化控制中的作用：一条是从初级运动皮层和运动前区发出的皮质脊髓（CS）束，另一条是从脑干发出的皮质下网状脊髓（RS）束。我们旨在研究在这些区域发生损伤后，皮质-网状网络如何重组以帮助恢复手指灵活性。为了给这个问题提供一个潜在的生物学上合理的答案，我们开发了一个人工神经网络（ANN），以模拟运动前规划层、具有兴奋性和抑制性CS输出的皮质层以及控制手指运动的RS输出之间的相互作用。该ANN经过训练以模拟正常的手指个体化控制和力量表现。然后对CS区域、RS区域或两者同时施加模拟中风，并分析手指灵活性的恢复情况。在完整模型中，ANN显示出受指令控制手指和未受指令控制手指的力量之间存在近乎线性的关系，类似于人类的个体化模式。中风后的模拟结果表明，CS和RS区域的损伤都会导致未受指令控制手指的意外力量增加、受指令控制手指立即变弱、早期恢复过程中的控制改善以及神经可塑性增加。仅CS区域的损伤会显著损害个体化控制，而RS损伤则会影响力量，对个体化控制的影响较小。该模型还预测了中风严重程度对手指个体化控制的影响，突出了CS和RS损伤的综合作用。这个模型为皮质和皮质下区域在手指个体化控制中的相互作用提供了见解。它表明恢复机制涉及这些网络的重组，这可能为神经康复策略提供参考。
