神经退行性疾病的扰动疗法:可兴奋网络的吸引器如何帮助
Mariia Popova1, Claus C Hilgetag1, Marc-Thorsten Hütt2
1Institute of Computational Neuroscience, Hamburg Center of Neuroscience, <a href="https://ror.org/01zgy1s35">University Medical Center Hamburg-Eppendorf</a>, Hamburg University, Hamburg, Germany.
Physical review. E
|December 18, 2024
概括
网络拓显著影响可激发动态. 微小的网络变化可以大大改变系统行为,为帕金森病和等神经系统疾病提供新的治疗策略.
科学领域:
- 计算神经科学是一种计算神经科学.
- 复杂的系统复杂的系统.
- 图形理论是指图形的理论.
背景情况:
- 刺激的动态是神经功能的基础.
- 网络拓,包括反循环,塑造系统行为.
- 了解吸引力动态对于建模大脑功能至关重要.
研究的目的:
- 调查网络拓如何影响可刺激动态中的吸引子.
- 确定拓变化改变动态模式的机制.
- 探索神经疾病模型中的应用.
主要方法:
- 在已签名的定向图上建模可激发动态.
- 系统的数值实验来分析网络拓效应.
- 调查由于边缘增加/移除而引起的吸引器空间的变化.
主要成果:
- 网络拓,通过反循环,决定了吸引子的出现和消失.
- 特定的拓操作可以诱导或破坏网络吸引器.
- 确定了剧烈的动态模式转变的决定因素.
结论:
- 提出一种系统方法,通过拓变化改变系统动态.
- 拓操纵为扰动疗法提供了一个框架.
- 对帕金森病和的深度大脑刺激有潜在的应用.
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