噪音记忆在不断变化的环境中产生价值
Jorge Ramírez-Ruiz1, R Becket Ebitz1
1Département de Neurosciences, Faculté de Médecine, Université de Montréal, Montréal, QC, Canada.
Adaptive behavior
|November 10, 2025
概括
情节性记忆中的记忆错误可以增强顺序性决策. 不完美的记忆程序 (IMP) 和损失代理 (LIMP) 接近基于价值的决策,表明记忆的不完美可以改善,而不是损害认知功能.
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.
- 行为经济学是一种行为经济学.
背景情况:
- 在连续的决策过程中,情节性记忆的作用受到争论.
- 标准模型整合了奖励,与记忆回忆不同.
- 之前的工作引入了不完善的记忆程序 (IMP),用于基于记忆的决策.
研究的目的:
- 开发生物可信的IMP的近似方法,称为失效剂 (LIMPs).
- 研究记忆不完美如何影响循序渐进的基于价值的决策.
- 探索记忆错误是否可以提高决策性能.
主要方法:
- 开发了具有1位奖励内存和概率编码失败的损失代理 (LIMPs).
- 在经典决策任务中评估IMP和LIMP.
- 分析了奖励和遗漏的差异编码概率的影响.
主要成果:
- LIMP和IMP的性能与完美的记忆剂相比或更好.
- 这些代理产生了类似于基于价值的计算的决策模式.
- 调整编码概率允许在匹配/最大化和灵活性/稳定性方面进行权衡.
结论:
- 情节性代理可以使用现实的记忆噪声来近似基于价值的代理.
- 记忆错误可能有助于提高决策的性能.
- 记忆缺陷为'价值'的行为相关性提供了另一种解释.
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