高阶网络中神经元同步的模式
Soumen Majhi1, Samali Ghosh2, Palash Kumar Pal2
1Physics Department, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy.
Physics of life reviews
|January 3, 2025
概括
神经网络同步,由双向和高阶相互作用驱动,塑造大脑功能和功能障碍. 了解这些复杂的动态,包括嵌合体状态,是神经学研究的关键.
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.
- 复杂的系统复杂的系统.
背景情况:
- 神经元同步对于认知和运动控制至关重要.
- 传统上对双向神经元相互作用的关注正在扩大,包括更高阶相互作用.
- 复杂的同步模式,如奇默状态,在神经网络中观察到,并与神经系统疾病相关联.
研究的目的:
- 审查如何双向和高阶相互作用影响神经网络中的同步模式.
- 提供有关驱动神经元同步的连接机制的全面概述.
- 突出神经系统中同步状态的重要性.
主要方法:
- 审查关于神经元同步现有的文献.
- 探索各种连接机制 (例如,时间相互作用,时间延迟合,自适应通信).
- 关键神经元模型的分析 (欣德马什-罗斯,霍奇金-哈克斯利,谢尔曼,菲茨休-纳古莫).
主要成果:
- 双向和高阶相互作用都会产生复杂的同步时空模式.
- 奇梅拉状态,以同步和非同步活动的共存为特征,从这些相互作用中产生.
- 网络结构和神经元动态显著影响同步模式的出现和稳定性.
结论:
- 了解不同的同步模式对于神经学研究至关重要.
- 高级互动在塑造网络动态方面发挥着重要作用.
- 对神经元同步的进一步研究可以为神经系统疾病的治疗提供信息.
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