禁食的尼古丁依赖个体的增强决策:使用分层漂移扩散建模的计算分析
Kathryn Biernacki1, Elena Molokotos2, Chungmin Han1
1National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD21224, United States.
Drug and alcohol dependence
|July 22, 2023
概括
计算机建模显示,成功戒烟50分钟的个体在基于奖励的决策过程中,与没有戒烟的人相比,在基于奖励的决策过程中,证据积累速度更快. 这突出了决策过程作为戒烟治疗的关键目标.
科学领域:
- 神经科学是一个神经科学.
- 行为经济学是一种行为经济学.
- 成研究 研究成研究
背景情况:
- 个人决策和奖励敏感性的差异影响吸烟禁欲.
- 像等级漂移扩散模型 (HDDM) 这样的计算模型可以区分奖励响应与决策组件.
研究的目的:
- 利用HDDM来识别影响非寻求治疗的吸烟者吸烟戒断的决策和奖励相关参数.
- 调查选择行为参数如何与延迟戒烟的能力有关.
主要方法:
- 80名成年吸烟者完成了概率奖励任务 (PRT) 和复发模拟任务 (RAT).
- 根据RAT完成情况,参与者被分为两组:在一夜戒烟后吸烟前等待0分钟 (n=36) 和50分钟 (n=44).
- 应用了HDDM来从PRT数据中分析决策参数.
主要成果:
- 两组之间没有发现PRT信号检测指标 (响应偏差,可歧视性) 的显著差异.
- 在HDDM分析中,与0分钟服务员相比,50分钟服务员的漂移率 (证据积累) 更快.
结论:
- 成功戒烟50分钟的吸烟者在基于奖励的决策过程中表现出增强的证据积累.
- 决策机制,特别是证据积累过程,对于戒烟至关重要,并代表潜在的治疗目标.
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