初级运动皮质电路的多尺度模型在体内预测了特定于细胞类型的行为状态依赖的动态
Salvador Dura-Bernal1, Samuel A Neymotin2, Benjamin A Suter3
1Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Cell reports
|June 10, 2023
概括
我们创建了一个详细的小鼠运动皮质模型,以了解在多个尺度上的大脑功能. 这种多尺度模型准确地预测了不同行为和操纵过程中的神经活动.
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:
- 了解大脑皮层需要整合分子,细胞,电路和行为数据.
- 现有的模型往往缺乏捕捉复杂皮层动态所需的多尺度细节.
研究的目的:
- 开发一个全面的,多尺度,生物物理细节模型的小鼠初级运动皮质 (M1).
- 将包括神经元类型,连接性和突触位置在内的各种实验数据集成到统一的计算框架中.
- 在各种行为状态和实验条件下调查细胞类型特定和多尺度的动力学,这些动力学是M1功能的基础.
主要方法:
- 构建了一个大规模的小鼠M1模型,包含超过1万个神经元和3000万个突触.
- 使用关于神经元类型,密度,分布,形态,生物物理和连接性在亚层分辨率上的实验数据的受约束模型参数.
- 包括来自胸膜和皮质区域的远程输入,以及诺拉德仁基输入.
主要成果:
- 该模型准确地预测了in vivo层和细胞类型特定的神经反应 (发射速率和局部场势).
- 模型的预测与在安静的清醒,运动和实验性操纵期间观察到的活动模式保持一致 (甲状腺体不活化,上腺素阻塞).
- 分析揭示了低维人群潜伏动态,并为观察到的神经活动产生了机制性假设.
结论:
- 开发的定量理论框架有效地整合和解释实验M1数据.
- 该模型提供了对细胞类型特定的多尺度动态的洞察,这些动态在不同的行为和实验环境中控制着M1的功能.
- 这种方法通过弥合生物组织的多个尺度来促进对皮质功能的更深入的理解.
相关概念视频
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