方法避免强化学习作为一种与焦虑相关的避免的翻译和计算模型
Yumeya Yamamori1, Oliver J Robinson1,2, Jonathan P Roiser1
1Institute of Cognitive Neuroscience, University College London, London, United Kingdom.
eLife
|November 14, 2023
概括
焦虑导致人们避免潜在的惩罚,即使这意味着更少的奖励. 一个新的强化学习任务有助于测量这种跨物种的回避行为,以更好地治疗焦虑.
科学领域:
- 认知神经科学 认知神经科学
- 计算精神病学是一种计算精神病学.
- 行为经济学是一种行为经济学.
背景情况:
- 避免是焦虑障碍的一个关键症状,但在人类和动物之间持续测量它是具有挑战性的.
- 现有的研究避免的方法缺乏翻译有效性,阻碍了理论进步和治疗开发.
研究的目的:
- 开发和验证一种新的转化测量焦虑相关的避免使用一种方法-避免强化学习任务.
- 通过计算建模来研究潜在的回避行为及其与主观焦虑的关系的认知机制.
主要方法:
- 为在线研究 (n=372) 中的人类参与者适应非人类动物强化学习范式.
- 采用计算建模来分析方法回避行为和奖励/惩罚灵敏度的个体差异.
- 在独立样本中重复发现 (n=627) 和评估测量可靠性 (n=57).
主要成果:
- 具有较高任务诱导焦虑的个体表现出避免惩罚相关的选择,即使以减少整体奖励为代价.
- 计算模型表明,相对于奖励,对惩罚的高度敏感性解释了这种回避行为.
- 开发的任务表现出对绩效指标的相当至卓越的可靠性.
结论:
- 方法避免强化学习任务为研究与焦虑相关的避免提供了一个有前途的翻译和计算模型.
- 这种范式可以弥合人类和非人类动物研究之间的差距.
- 未来的研究应该探索这个任务在患者群体中的临床实用性和预测有效性.
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