在神经模型中,代谢能量是潜在的吸引力
Richard B Buxton1, Eric C Wong1,2
1Department of Radiology, University of California, San Diego, California, United States.
Journal of neurophysiology
|December 6, 2023
概括
这项研究将神经人口模型与细胞能量成本联系起来,估计大脑ATP的使用. 它将神经吸引器与现实的生物能量学要求挂起来,以了解大脑功能.
科学领域:
- 计算神经科学是一种计算神经科学.
- 神经能量学是一种神经能量学.
- 系统神经科学 系统神经科学
背景情况:
- 神经人口建模,包括神经吸引物,有助于理解大脑功能.
- 神经活动生物能成本 (ATP/s/神经元) 的细胞水平估计提供了生理基础.
- 对于清醒的休息大脑ATP使用的经验参考是哺乳动物的2 × 10^9 ATP/s-神经元.
研究的目的:
- 提出一个建模框架,将抽象的神经人口模型变量与细胞生物能量成本联系起来.
- 将神经群体模型,特别是神经吸引器,固定在合理的生物能源要求上.
主要方法:
- 在威尔逊-考恩 (WC) 模型中应用了一个能量框架,用于相互作用的刺激性 (E) 和抑制性 (I) 神经群体.
- 分析了稳定状态,极限周期和持续活动的吸引力.
- 用每秒每神经元消耗的ATP来量化能量成本.
主要成果:
- 极限周期的能源成本与发射速度比振荡频率更相关.
- 通过反复激发进行自我持续的发射会导致更高的能源成本.
- 一个三节点的WC网络表现出持久的"开关"行为与适度的ATP使用.
结论:
- 拟议的框架将神经人口建模和细胞生物能学联系起来.
- 它提供了一种在生理能量约束中的抽象神经模型接地方法.
- 这种方法将神经吸引器固定在现实的生物能量需求上,从而促进对大脑功能的理解.
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