人类感知决策的多个井框架
Joseph Fluegemann1, Jiaqi Huang2, Morgan Lena Rosendahl1,3
1Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA.
Entropy (Basel, Switzerland)
|February 27, 2026
概括
这项研究介绍了决策的量子认知模型,将认知控制与感知任务联系起来. 该模型成功地预测了人类的选择和反应时间,为耶克斯-多德森定律提供了新的见解.
科学领域:
- 认知科学 认知科学
- 量子物理学 量子物理学 是一种量子物理学.
- 决策神经科学 决策神经科学
背景情况:
- 人类决策涉及复杂的认知过程.
- 了解认知控制和兴奋的作用至关重要.
- 现有的模型可能无法完全捕捉这些影响.
研究的目的:
- 提出一种新的量子认知模型,将认知控制整合到感知决策中.
- 量化建模认知兴奋对任务执行的影响,特别是解决耶克斯-多德森定律.
- 为理解主观概率和证据积累提供一个框架.
主要方法:
- 开发了一种使用多个平方井潜力的量子认知模型.
- 每个井代表一个决策结果,深度编码信号强度和宽度编码域普遍性.
- 使用点运动两替代强制选择 (2AFC) 任务验证了该模型,并将其应用于Yerkes-Dodson定律.
主要成果:
- 该模型成功地复制了2AFC任务的关键经验发现,包括运动连贯性和漂移率之间的相关性.
- 该模型捕获了任务准确性和认知唤醒之间的反转U形关系,这是Yerkes-Dodson定律的特征.
- 两种兴奋模型方法的比较 (自身能量与动能) 产生了不同的预测.
结论:
- 这项工作提出了第一个关于唤起对人类感知决策影响的定量模型.
- 量子认知模型为理解在不同认知控制和兴奋水平下的决策提供了一个强大的框架.
- 这项研究为精确定义耶克斯-多德森定律的功能形式奠定了基础.
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