威胁的知识偏差在焦虑时的感知决策:来自信号检测理论和漂移扩散建模的证据
Sekine Ozturk1, Xian Zhang1, Shannon Glasgow1
1Department of Psychology, Stony Brook University, Stony Brook, New York.
Biological psychiatry global open science
|February 1, 2024
概括
了解焦虑中的威胁偏见至关重要. 不确定的威胁线索增强了大多数人的决策,但损害了焦虑个人的决策,突出了焦虑.
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.
- 计算精神病学是一种计算精神病学.
背景情况:
- 威胁偏见与焦虑的发展和维持有关.
- 这些偏差的操作化和量化仍然有限.
- 威胁知识和不确定性对这些偏见的影响尚不清楚.
研究的目的:
- 调查先前对威胁的了解及其不确定性如何影响威胁偏见.
- 通过计算建模来量化这些偏差.
- 检查这些偏见在焦虑中的表现.
主要方法:
- 参与者 (n=55) 执行了一个使用 prestimulus 线索的歧视任务.
- 关于威胁概率的不确定性有所不同.
- 使用信号检测理论和层次漂移扩散建模.
主要成果:
- 与中性线索相比,高不确定性威胁线索改善了歧视.
- 在高不确定性威胁信号之后,焦虑与更严重的歧视相关.
- 计算机建模揭示了威胁线索,改变了决策的起点,提高了证据积累的效率,焦虑影响了起点,而不是效率.
结论:
- 了解不确定的威胁可以改善感知决策.
- 然而,在焦虑症患者中,这种改善受损.
- 计算建模阐明了这些与焦虑相关的偏见背后的机制.
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