适应式指数整合和火模型,具有碎形扩展
Diogo L M Souza1, Enrique C Gabrick1,2,3, Paulo R Protachevicz4
1Graduate Program in Science, State University of Ponta Grossa, 84030-900 Ponta Grossa, PR, Brazil.
Chaos (Woodbury, N.Y.)
|February 11, 2024
概括
这项研究引入了使用碎形衍生物的适应指数整合和火 (Adex) 神经元模型的碎形扩展. 研究结果显示,碎形顺序对神经元发射模式和适应机制产生影响.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 数学生物学 数学生物学
背景情况:
- 数学模型对于理解神经元电生理学至关重要.
- 适应指数整合与火 (Adex) 模型是模拟神经元行为的广泛使用的工具.
- 标准的Adex模型使用的是整数顺序的衍生值.
研究的目的:
- 提出并研究Adex神经元模型的碎形延伸.
- 探索碎形导数对神经元发射模式和平均频率的影响.
- 为了确定分形导数是否提供更现实的神经元表示.
主要方法:
- 在阿德克斯模型中用分数导数取代整数顺序的导数.
- 分析了使用等级和不同级别的碎形导数的效果.
- 检查了尖峰间隔和平均发射频率的变化.
主要成果:
- 碎形导数的顺序显著影响神经元发射模式.
- 分数顺序影响神经元的尖峰间隔和平均发射频率.
- 发射模式依赖于神经元参数和碎形操作员命令.
结论:
- 阿德克斯模型的碎形扩展为神经元建模提供了一个通用的框架.
- 碎形衍生物为描述神经元电生理学提供了细微的方法.
- 低于单位的碎形顺序增强了适应机制对尖峰射击模式的影响.
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