推断心灵从感知决策中漫步的推断.
1Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA. cathyz@wustl.edu.
Communications psychology
|February 19, 2026
概括
研究人员开发了一个计算模型来追踪任务期间的思维流浪 (MW). 这种方法测量了注意力逐试验的转移,而不会打断参与者,为认知状态提供了新的见解.
科学领域:
- 认知心理学 认知心理学
- 神经科学是一个神经科学.
- 计算建模 计算建模
背景情况:
- 保持专注的注意力对于目标实现至关重要,但注意力往往由于心灵漫游 (MW) 而失效.
- 传统的方法,如思维探测,是不常见的和破坏性的,而其他技术则假设固定的任务/非任务时间分割.
- 需要持续的,非侵入性的方法来测量认知任务期间的MW.
研究的目的:
- 开发和验证一个计算框架,以逐个试验的基础上推断思维漂泊.
- 评估使用计算建模来追踪注意状态的时间变化是否可行.
- 在不依赖破坏性思维探测的情况下,提供对MW动态的更细致的理解.
主要方法:
- 使用随机点运动任务与操纵的证据和重复的响应偏差.
- 一个隐藏的马尔科夫模型与通用线性模型 (GLM-HMM) 被安装到参与者的性能数据中.
- 偶尔会使用思维探测来验证模型对内部状态的分类.
主要成果:
- 非任务试验的特点是更高的准确性和更短的反应时间,这表明刺激处理减少,对响应偏差的依赖增加.
- 两种状态的GLM-HMM成功地预测了在非任务期间的较低反应时间.
- 该模型显示,在任务的过程中,思想流浪的增加与自我报告的焦点水平相关.
结论:
- 计算建模,特别是GLM-HMM,可以有效地测量注意力状态的试验对试验变化.
- 这种方法可以在不中断认知任务的情况下,持续评估心灵漂泊.
- 这些发现为研究注意力和认知控制的动态开辟了新的途径.
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