在不确定性下的食遵循边际价值定理与环境表示的贝叶斯更新
James Webb1,2, Paul Steffan1, Benjamin Y Hayden3
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
bioRxiv : the preprint server for biology
|April 8, 2024
概括
在不确定的环境中,小鼠的食行为与修改的边际值定理 (MVT) 相一致. 他们学习并适应不断变化的奖励率,在波动的情况下展示了复杂的决策.
科学领域:
- 行为生态学 行为生态学
- 神经科学是一个神经科学.
- 计算生物学 计算生物学
背景情况:
- 食理论,特别是边际值定理 (MVT),解释了可预测环境中的最佳补丁离开策略.
- 自然环境通常是随机的,需要采集者适应不确定性,这是标准MVT的局限性.
- 了解动物在不稳定条件下的决策对于行为生态学和神经科学至关重要.
研究的目的:
- 在确定性和随机的食条件下研究小鼠留的决策.
- 开发一种新的行为任务和计算框架来研究食策略.
- 为了确定小鼠的食行为是否符合MVT或更简单的启发式策略.
主要方法:
- 为固定头部和自由移动的小鼠开发了一个新的行为任务.
- 操纵了补丁之间旅行时间和补丁内奖励耗尽率的确定性和随机性.
- 利用计算框架分析补丁停留时间,并将其与理论模型进行比较.
主要成果:
- 鼠标表现出与MVT一致的补丁停留时间,而不是简单的启发式策略.
- 行为最好通过修改后的MVT来解释,该MVT包含贝叶斯估计器和动态预先更新环境表示.
- 鼠标展示了同时在多个时间尺度上学习和利用任务结构的能力.
结论:
- 小鼠可以通过动态更新它们的内部奖励可用性模型,在不稳定的环境中有效地寻找食物.
- 这些发现支持了修改后的MVT,该MVT考虑了在不确定的条件下学习和适应.
- 这项研究为使用系统神经科学方法调查不确定性下寻找食物的神经基础提供了基础.
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