通过能量平衡战略在分数级神经网络中的同步
Zhao Yao1, Kehui Sun1, Shaobo He2
1School of Physics, Central South University, Changsha, 410083 China.
Cognitive neurodynamics
|November 18, 2024
概括
单个神经元的差异是使用小数式微积分来建模的,揭示了能量平衡如何驱动神经网络中的信息交换和同步. 这种异质性是集体神经元行为和信息传输的关键.
科学领域:
- 神经科学是一个神经科学.
- 复杂的系统复杂的系统.
- 数学生物学 数学生物学
背景情况:
- 个体神经元的差异对于理解复杂的神经网络行为至关重要.
- 分数式微积分提供了一个框架来建模这些个别变化.
- 菲茨休-纳古莫 (FHN) 模型是研究神经动力学的基本工具.
研究的目的:
- 为了研究神经元中的个体差异如何使用分数顺序框架影响网络行为.
- 探索能量平衡策略在中介神经元间通信中的作用.
- 分析异质神经网络中同步和信息传输的出现.
主要方法:
- 使用一个分数顺序的菲茨休-纳古莫 (FHN) 神经电路模型.
- 实施能量平衡策略来控制神经元之间的突触通信.
- 连接两个神经元和一个链式神经网络来观察同步现象.
- 分析不同神经元序列的网络中目标波的发展.
主要成果:
- 能量失衡的神经元成功交换信息,而平衡的神经元阻断了突触传输.
- 结合的神经元实现了相位同步和相位锁定,表明了协调的尖端.
- 由分数顺序引入的异质性导致了目标波的形成和扩散.
- 接近1的同步因子在整个网络中显示出一致的发射模式.
结论:
- 通过分数顺序建模的神经元中的个体差异对于集体行为和信息处理至关重要.
- 能量平衡策略有效调节神经元间的通信,导致同步.
- 分数顺序建模提供了关于网络异质性如何驱动目标波等复杂的新兴现象的见解.
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