工作记忆中的动态编码的计算基础
Jake P Stroud1, John Duncan2, Máté Lengyel3
1Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.
Trends in cognitive sciences
|April 5, 2024
概括
工作记忆的维护可能依赖于动态的神经编码,而不仅仅是稳定的活动. 任务优化模型自然地显示了这些动态,这表明动态编码是认知功能的关键.
科学领域:
- 认知神经科学 认知神经科学
- 计算神经科学是一种神经科学.
背景情况:
- 工作记忆 (WM) 对认知至关重要.
- 传统上,WM维护与稳定的神经活动模式有关.
研究的目的:
- 研究工作记忆中稳定与动态神经编码的作用.
- 解释为什么任务优化模型表现出动态编码,与经典模型不同.
主要方法:
- 神经数据的分析.
- 检查经典和任务优化的神经网络模型.
主要成果:
- 在WM维护期间的神经活动在稳定之前显示动态变化.
- 任务优化模型自然会显示动态编码,提供理论解释.
- 经典模型本身并没有显示动态编码.
结论:
- 动态编码是工作内存维护的一个基本计算特征.
- 修订WM的理解,以纳入动态神经过程是必要的.
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