Park Harhim, Yang Jaeyeong, Vassileva Jasmin, Ahn Woo-Young
Department of Psychology, Seoul National University, Seoul, Korea.
Department of Psychiatry, Virginia Commonwealth University, Virginia, United States of America.
J Math Psychol. 2021 Jun;102. doi: 10.1016/j.jmp.2021.102532. Epub 2021 Apr 21.
The Balloon Analogue Risk Task (BART) is a popular task used to measure risk-taking behavior. To identify cognitive processes associated with choice behavior on the BART, a few computational models have been proposed. However, the extant models either fail to capture choice patterns on the BART or show poor parameter recovery performance. Here, we propose a novel computational model, the exponential-weight mean-variance (EWMV) model, which addresses the limitations of existing models. By using multiple model comparison methods, including post hoc model fits criterion and parameter recovery, we showed that the EWMV model outperforms the existing models. In addition, we applied the EWMV model to BART data from healthy controls and substance-using populations (patients with past opiate and stimulant dependence). The results suggest that (1) the EWMV model addresses the limitations of existing models and (2) heroin-dependent individuals show reduced risk preference than other groups, which may have significant clinical implications.
气球模拟风险任务（BART）是一种用于测量冒险行为的常用任务。为了识别与BART上的选择行为相关的认知过程，已经提出了一些计算模型。然而，现有的模型要么无法捕捉BART上的选择模式，要么表现出较差的参数恢复性能。在这里，我们提出了一种新的计算模型，即指数加权均值 - 方差（EWMV）模型，它解决了现有模型的局限性。通过使用多种模型比较方法，包括事后模型拟合标准和参数恢复，我们表明EWMV模型优于现有模型。此外，我们将EWMV模型应用于来自健康对照组和物质使用人群（过去有阿片类药物和兴奋剂依赖的患者）的BART数据。结果表明：（1）EWMV模型解决了现有模型的局限性；（2）海洛因依赖个体比其他组表现出更低的风险偏好，这可能具有重要的临床意义。
