基于突触的适应神经网络的集体行为,具有记忆效应和随机性
Vinoth Seralan1, D Chandrasekhar2, Sarasu Pakiriswamy3
1Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, 600069 India.
Cognitive neurodynamics
|December 23, 2024
概括
这项研究揭示了具有磁流的适应性突触神经元如何表现出全球多稳定性. 网络拓和随机性影响集体神经元行为和同步动态.
科学领域:
- 计算神经科学是一种神经科学.
- 复杂系统动力学 复杂系统动力学
- 网络科学 网络科学
背景情况:
- 适应性突触神经元模型对于理解大脑功能至关重要.
- 小世界网络的特点是局部集群和短路径长度,在生物系统中很普遍.
- 电磁流和记忆性突触引入了复杂的动力学和合机制.
研究的目的:
- 为了研究一个具有磁流的单个适应性突触神经元模型的全球多稳定性.
- 为了分析两个结合的神经元的动态和同步与一个memristive突触.
- 探索不同参数的小世界网络中神经元的集体行为.
主要方法:
- 使用分叉图,相图和吸引力分析盆地的数值模拟.
- 通过最大的利亚普诺夫指数和平均平均误差对结合神经元动态的分析.
- 将常规网络重建为小世界网络,并控制重新布线的概率.
主要成果:
- 在单个神经元模型中,由于可切换的平衡状态,证明了全球多稳定性.
- 在结合的神经元中观察同步动态.
- 在受到邻里连接,合强度和重新连接概率影响的小世界网络中识别集体行为.
结论:
- 具有磁流的适应性突触神经元模型表现出复杂的动态和全球多稳定性.
- 小世界网络拓学显著影响集体神经元行为和同步.
- 这项研究为复杂神经网络的新兴特性提供了洞察力.
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