在中风后手指灵活性恢复过程中,大脑皮层与皮层下部之间的相互作用是一个 ANN 模型。

Ashraf Kadry, Deborah Solomonow-Avnon, Sumner Lee Norman, Jing Xu, Firas Mawase
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引用次数: 0

摘要

目的:手指的灵活性,尤其是手指的单独活动能力,对人类的运动至关重要,而脑损伤导致的手指灵活性中断会严重影响生活质量。了解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分离中的作用:来自初级运动皮层和前运动区的皮质脊髓束(CST),以及来自脑干的皮质下网状脊髓束(RST)。我们的目的是研究在这些区域发生病变后,皮质-脊髓网络如何重组以帮助手指灵活性的恢复:为了从生物学角度为这一问题提供一个潜在的合理答案,我们开发了一个人工神经网络(ANN)来模拟前运动规划层、具有兴奋和抑制皮质脊髓输出的皮质层以及控制手指运动的网状脊髓输出之间的相互作用。对 ANN 进行了训练,以模拟正常的手指分离和力量。然后对皮质脊髓(CS)区、网状脊髓(RS)区或两者进行模拟中风,并分析手指灵活性的恢复情况:主要结果:在完好的模型中,方差网络显示指令手指和非指令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。中风后模拟显示,CS和RS区域的病变导致非指令手指的非预期力量增加,指令手指的力量立即减弱,在早期恢复过程中控制力得到改善,神经可塑性增强。仅 CS 区的病变就会严重影响个体化,而 RS 区的病变会影响力量,但对个体化的影响较小。该模型还预测了中风严重程度对手指个性化的影响,突出了CS和RS病变的综合效应:该模型深入揭示了皮层和皮层下区域在手指个性化中的交互作用。意义:该模型深入揭示了皮层和皮层下区域在手指个体化中的交互作用,表明恢复机制涉及这些网络的重组,可为神经康复策略提供参考。
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An ANN models cortical-subcortical interaction during post-stroke recovery of finger dexterity.

Objective: 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 tract (CST) from the primary motor cortex and premotor areas, and the subcortical reticulospinal tract (RST) from the brainstem. We aimed to investigate how the cortical-reticular network reorganizes to aid recovery of finger dexterity following lesions in these areas.

Approach: 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 corticospinal outputs, and reticulospinal outputs controlling finger movements. The ANN was trained to simulate normal finger individuation and strength. A simulated stroke was then applied to the corticospinal (CS) area, reticulospinal (RS) area, or both, and the recovery of finger dexterity was analyzed.

Main results: 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.

Significance: 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.

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