在随机模块化网络中混乱动态的层次结构
Łukasz Kuśmierz1, Ulises Pereira-Obilinovic1, Zhixin Lu1
1Allen Institute, Seattle, Washington, USA.
Physical review letters
|April 25, 2025
概括
我们探索了神经群体动态,发现混沌可以通过添加噪音或模块化来减少. 跨层次层次的平衡驱使系统走向混乱的边缘.
科学领域:
- 计算神经科学是一种计算神经科学.
- 复杂系统理论 复杂系统理论
背景情况:
- 神经群体动态对于大脑功能至关重要.
- 了解连接和混乱动态之间的关系是一个持续的挑战.
研究的目的:
- 研究随机连接的神经群体的相位图和动态.
- 探索连接结构如何影响混乱行为.
- 检查层次连接对系统稳定性的影响.
主要方法:
- 为随机连接的神经群体开发模型.
- 动态平均场理论的应用.
- 进行数值模拟来分析系统动态.
主要成果:
- 丰富的相位图的识别,具有明显的高和低维的混乱相位.
- 交叉区域的特征与特定的Lyapunov和维度值.
- 证明噪音或模块化可以减轻神经网络中的混乱.
- 观察到等级连接驱动系统朝着混乱的边缘.
结论:
- 连接结构在塑造神经群体动态方面发挥着至关重要的作用.
- 混乱的边缘可能是复杂的神经系统的关键操作模式.
- 可以利用模块化和噪声来控制神经网络中的混乱动态.
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