从有效的潜在变量中获得神经关键性.
Mia C Morrell1, Ilya Nemenman2, Audrey Sederberg3
1Department of Physics, New York University, New York, United States.
eLife
|March 12, 2024
概括
大脑活动可能会表现出雪崩关键性,这是神经系统中观察到的关键状态. 这项研究表明,将神经活动与多个潜在变量合,自然会导致这种关键行为,而无需微调.
科学领域:
- 计算神经科学是一种神经科学.
- 复杂系统科学 复杂系统科学
- 动态系统理论 动态系统理论
背景情况:
- 神经活动中的功率定律分布表明大脑可能处于关键状态.
- 雪崩的关键性,一种特定的关键性的表现,已经在各种神经系统中观察到.
- 最近的发现将老鼠神经群体中的功率规律与多个潜在动态变量的合联系起来.
研究的目的:
- 确定潜伏动态变量诱导雪崩关键性的条件.
- 调查是否类似的机制是神经系统中雪崩关键性的基础.
- 探索潜变量与关键大脑动态之间的关系.
主要方法:
- 神经群体的数学建模与潜在的动态变量相结合.
- 对关键行为和参数空间探索的分析.
- 根据信息内容,识别雪崩动态的不同模式.
主要成果:
- 潜在的动态变量确实可以导致雪崩的关键性.
- 与多个潜在变量相连,与单个变量相比,扩大了关键行为的参数范围.
- 在不需要微调模型参数的情况下观察到雪崩的关键性.
- 确定了两个不同的关键雪崩制度,在信息传输方面有所不同.
结论:
- 神经系统中的雪崩关键性可能来自于神经活动是由几个潜在的动态变量驱动的.
- 这些动态变量可以从观察到的人口活动中推断出来.
- 这些发现为大脑中的雪崩关键性提供了一种机械解释.
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