Ahn Woo Young, Dai Junyi, Vassileva Jasmin, Busemeyer Jerome R, Stout Julie C
Department of Psychiatry, Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychology, The Ohio State University, Columbus, OH, USA.
Centre for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany.
Prog Brain Res. 2016;224:53-65. doi: 10.1016/bs.pbr.2015.07.032. Epub 2015 Nov 4.
Decision-making tasks that have good ecological validity, such as simulated gambling tasks, are complex, and performance on these tasks represents a synthesis of several different underlying psychological processes, such as learning from experience, and motivational processes such as sensitivity to reward and punishment. Cognitive models can be used to break down performance on these tasks into constituent processes, which can then be assessed and studied in relation to clinical characteristics and neuroimaging outcomes. Whether it will be possible to improve treatment success by targeting these constituent processes more directly remains unexplored. We review the development and testing of the Expectancy-Valence and Prospect-Valence Learning models from the past 10 years or so using simulated gambling tasks, in particular the Iowa and Soochow Gambling Tasks. We highlight the issues of model generalizability and parameter consistency, and we describe findings obtained from these models in clinical populations including substance use disorders. We then suggest future directions for this research that will help to bring its utility to broader research and clinical applications.
具有良好生态效度的决策任务，如模拟赌博任务，是复杂的，这些任务上的表现代表了几种不同潜在心理过程的综合，如从经验中学习，以及对奖励和惩罚敏感等动机过程。认知模型可用于将这些任务上的表现分解为组成过程，然后可以根据临床特征和神经影像学结果对这些过程进行评估和研究。是否有可能通过更直接地针对这些组成过程来提高治疗成功率仍未得到探索。我们回顾了过去10年左右使用模拟赌博任务，特别是爱荷华州和苏州赌博任务对预期-效价和前景-效价学习模型的开发和测试。我们强调了模型可推广性和参数一致性的问题，并描述了从这些模型在包括物质使用障碍在内的临床人群中获得的发现。然后，我们提出了这项研究的未来方向，这将有助于将其效用应用于更广泛的研究和临床应用。
