大脑和中央模式生成器之间的合关系基于一个分数顺序扩展的后沼泽-模型
Qiang Lu1, Haomiao Wang2, Wenxuan Lu3
1College of Medical Information Engineering, Shandong First Medical University & Shandong Academy of Medical Sciences, 271000 Taian, Shandong, China.
Journal of integrative neuroscience
|May 30, 2024
概括
中央模式发生器 (CPG) 与中枢神经系统 (CNS) 结合,在不同状态中呈现频率滑动,调节大脑功能. 增加对中枢神经系统的外部输入减少了同步,并触发了不规则的触发,为运动机制提供了洞察力.
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.
- 系统神经科学 系统神经科学
背景情况:
- 中枢神经系统 (CNS) 呈现出不同的状态 (次临界,临界,超临界),影响信息处理.
- 中央模式生成器 (CPG) 对于运动至关重要,它们与中枢神经系统的相互作用需要进一步研究.
研究的目的:
- 调查CNS和CPG模型之间的合.
- 了解神经网络振荡如何响应周期性刺激.
主要方法:
- 开发了一个分数顺序的CPG模型,使用时间延迟的扩展的Hindmarsh-Rose模型.
- 建立了一个中枢神经系统模型,具有循环激发抑制神经网络.
- 探索了CNS和CPG模型之间的合动态.
主要成果:
- 在合的中枢神经系统中观察到频率滑动,在亚临界,临界和超临界状态之间,特别是在马波段.
- 证明频率滑动在多个时空尺度上调节大脑功能.
- 发现,对中枢神经系统的外部输入增加会降低连贯性,诱导神经元随机性,降低同步性,并导致不规则的触发.
结论:
- CPG和CNS模型的合提供了对大脑功能频率调节的见解.
- 由强大的外部输入诱导的神经元随机性在调节神经网络同步和发射模式方面发挥着作用.
- 这些发现为控制机动系统的机制提供了新的视角.
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