噪音诱导的两个神经元图案的同步与不对称的噪音和不均的合
Gurpreet Jagdev1, Na Yu1,2
1Department of Mathematics, Toronto Metropolitan University, Toronto, ON, Canada.
Frontiers in computational neuroscience
|March 11, 2024
概括
不对称的噪声可以同步合的神经振荡器,特别是在刺激值附近. 最佳同步发生在最大化的合差异和单向连接中的特定噪声模式下.
科学领域:
- 计算神经科学是一种计算神经科学.
- 系统神经科学 系统神经科学
- 理论神经科学理论神经科学
背景情况:
- 同步动态对于认知功能至关重要.
- 之前的研究集中在神经振荡器中统一的噪音和合.
- 现实世界的神经系统在噪音和合方面表现出异质性.
研究的目的:
- 研究与异质噪声和合相结合的刺激神经元中的噪声诱导同步.
- 探索非对称噪声和合如何影响同步.
- 了解网络图案在神经元动态中的作用.
主要方法:
- 利用Hopf分叉 (HB) 的正常形式来建模可刺激的神经元.
- 模拟结合的神经元与独立变化的噪声强度和合强度.
- 分析了非对称噪声和合对同步的影响.
主要成果:
- 不对称的噪音可以诱导结合激发神经元的同步.
- 当系统接近激发值 (HB) 时,同步会增加.
- 不均的合和噪声不对称性促进相位同步,在最大的合差异处具有最佳状态.
- 与双向连接相比,单向连接显示了增强的相位同步.
结论:
- 噪音和合的异质性显著影响神经同步.
- 不对称的噪声和合是相内同步的关键驱动因素.
- 研究结果强调了网络结构和噪声在神经元通信中的重要性.
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