在合的库拉莫托振荡器网络中对同步和网络重组产生神经调节效应
Sinan Aktay1, Leonard M Sander2, Michal Zochowski1,2
1Biophysics Program, <a href="https://ror.org/00jmfr291">University of Michigan, Ann Arbor</a>, Michigan 48105, USA.
Physical review. E
|November 20, 2024
概括
神经调节改变了大脑网络的动态. 乙胆水平和神经可塑性的变化可以导致稳定的同步状态,如splay状态,影响信号处理.
科学领域:
- 计算神经科学是一种神经科学.
- 神经动力学是一种神经动力学.
- 系统神经科学 系统神经科学
背景情况:
- 神经调节过程显著影响神经信号处理和网络组织.
- 乙胆 (ACh) 水平可以改变神经元的相应曲线,将动态从1型转变为2型.
- 活动依赖的可塑性是神经网络适应的一个关键机制.
研究的目的:
- 调查相应反应曲线的变化是如何形成的 (类型1与类型1对比). 类型2) 和神经可塑性影响网络重组.
- 模拟不同乙胆水平对合振荡器网络的影响.
- 探索不同网络条件下的同步状态的出现,如splay状态.
主要方法:
- 利用合的不相同的Kuramoto振荡器来模拟神经网络.
- 多种参数来表示相应曲线形状 (类型1和类型2) 和连接矩阵对称性的变化.
- 基于相锁的内置活动依赖的可塑性规则.
主要成果:
- 没有可塑性的1型网络显示出异步动态,但不对称的连接引发了稳定的splay状态.
- 类型2网络同步不管连接对称性,建立一个强大的频率相关系.
- 在Type 1网络中,活动依赖的可塑性自然产生了扩散状态,与同步Type 2网络中的结构频率映射不同.
结论:
- 阶段响应曲线的形状和网络连接性极大地影响了新兴动态.
- 在1型网络中,分离状态是一个强大的结果,特别是在可塑性方面.
- 这些发现表明,扩散状态可能是大脑网络重组中的常见现象.
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