从混乱到一致性:高阶突触相关联对神经动力学的影响
Nimrod Sherf1,2, Xaq Pitkow2,3,4,5,6, Krešimir Josić1,7
1Department of Mathematics, University of Houston, Houston, Texas, USA.
ArXiv
|September 15, 2025
概括
突触连接中的高阶循环相关性显著影响神经元网络动态. 强烈的相关性抑制混乱活动,促进大脑中稳定,节奏的模式.
科学领域:
- 计算神经科学是一种计算神经科学.
- 网络科学 网络科学
- 系统生物学 系统生物学
背景情况:
- 循环神经网络 (RNN) 模型阐明了生物神经网络的动态,特别是皮质活动模式.
- 现有的研究主要检查随机或简单的网络连接,忽视复杂的结构.
- 实验数据表明,高阶连接会影响时间活动,但缺乏理论框架.
研究的目的:
- 研究突触连接中第三阶和更高阶循环相关性对神经网络动态的影响.
- 发展理论理解,将复杂的网络结构与新兴动态联系起来.
- 探索特定的连接模式如何影响混乱和稳定活动之间的过渡.
主要方法:
- 对RNN模型的分析,在突触连接中具有不同顺序的循环相关性.
- 检查网络结构,连接矩阵的固有值谱和新兴动态之间的关系.
- 研究从混乱到固定或振荡活动的相位过渡.
主要成果:
- 突触连接中的第三阶和更高阶循环相关性显著改变神经元动态.
- 强大的周期性相关性抑制混乱的动态,有利于振荡或固定活动状态.
- 从混沌到稳定动态的相位过渡与自值支中的尖端形成有关.
- 网络活动的维度与底层网络结构有明显的联系.
结论:
- 高阶循环相关性是神经元网络动态的关键决定因素,超越了简单的连接模型.
- 强烈的循环相关性的存在可以稳定神经活动,防止混乱状态.
- 自身价值分析为理解结构动态关系和预测活动转变提供了理论基础.
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