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全脑计算建模揭示了帕金森病中微观大脑动态的破坏

Wenqian Zhao¹, Xueao Li², Jing Wang²

¹School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China; Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou 450000, China.

Computer methods and programs in biomedicine

|September 27, 2025

概括

帕金森病 (PD) 导致动态大脑异常,可以通过放松平均场动态建模 (rMFM) 检测到. 这些微观变化与网络变化有关,并且可能会在结构损伤之前发生,为早期诊断提供潜在的生物标志物.

科学领域:

神经科学是一个神经科学.
计算生物学计算生物学
医疗成像医学成像

背景情况:

帕金森病 (PD) 影响大脑的神经动力学,影响运动和非运动功能.
当前的神经成像方法 (rsfMRI,DTI,sMRI) 在检测微妙的,特定区域的动态变化方面存在局限性.
了解这些动态变化对于诊断和管理PD至关重要.

研究的目的:

应用放松平均场动态建模 (rMFM) 来识别PD中的微尺度动态异常.
为了将这些动态变化与大脑网络拓学和临床特征相关联.
探索rMFM在发现PD特定生物标志物的潜力.

主要方法:

利用rMFM,一个生物物理知情的计算框架,集成多模式MRI数据.
在rMFM中优化区域反复连接强度 (w) 和皮质下输入 (I).
进行了图形理论分析和相关性分析,以链接模型参数,网络指标和临床变量.

主要成果:

确定了PD患者的区域反复连接强度 (w) 和皮质下输入 (I) 的显著变化,特别是在叶区域.
观察到大脑网络拓学的相应变化.
发现证据表明功能障碍可能会在早期PD发生结构变化之前.

结论:

介绍了rMFM作为一种创新的方法,用于模拟使用多模式MRI的局部大脑动态.
突出了与大规模网络变化相关的PD中明显的微观动态异常.
建立了rMFM作为了解PD病理生理学和识别潜在生物标志物的有希望的工具.

关键词:

纤维通道学纤维通道学纤维通道学图形理论分析图形理论分析这就是为什么MRI是MRI.帕金森病是帕金森氏症的一种疾病.放松平均场动态建模放松平均场动态建模休息状态的功能性MRI.全脑计算建模全脑计算建模

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