Lee Michael D, Mistry Percy K, Menon Vinod
Department of Cognitive Sciences, University of California Irvine, Irvine, CA 92697, USA.
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, USA, CA 94305.
Comput Brain Behav. 2022 Sep;5(3):261-278. doi: 10.1007/s42113-022-00138-1. Epub 2022 Jun 7.
The -back task is a widely used behavioral task for measuring working memory and the ability to inhibit interfering information. We develop a novel model of the commonly used 2-back task using the cognitive psychometric framework provided by Multinomial Processing Trees. Our model involves three parameters: a memory parameter, corresponding to how well an individual encodes and updates sequence information about presented stimuli; a decision parameter corresponding to how well participants execute choices based on information stored in memory; and a base-rate parameter corresponding to bias for responding "yes" or "no". We test the parameter recovery properties of the model using existing 2-back experimental designs, and demonstrate the application of the model to two previous data sets: one from social psychology involving faces corresponding to different races (Stelter and Degner, 109:777-798, 2018), and one from cognitive neuroscience involving more than 1000 participants from the Human Connectome Project (Van Essen et al., 80:62-79, 2013). We demonstrate that the model can be used to infer interpretable individual-level parameters. We develop a hierarchical extension of the model to test differences between stimulus conditions, comparing faces of different races, and comparing face to non-face stimuli. We also develop a multivariate regression extension to examine the relationship between the model parameters and individual performance on standardized cognitive measures including the List Sorting and Flanker tasks. We conclude by discussing how our model can be used to dissociate underlying cognitive processes such as encoding failures, inhibition failures, and binding failures.
2-back任务是一种广泛用于测量工作记忆和抑制干扰信息能力的行为任务。我们使用多项式处理树提供的认知心理测量框架,开发了一种常用2-back任务的新型模型。我们的模型涉及三个参数:一个记忆参数,对应个体对呈现刺激的序列信息进行编码和更新的能力;一个决策参数,对应参与者根据记忆中存储的信息执行选择的能力;以及一个基础比率参数,对应回答“是”或“否”的偏差。我们使用现有的2-back实验设计测试模型的参数恢复特性,并展示该模型在两个先前数据集上的应用:一个来自社会心理学,涉及对应不同种族的面孔(Stelter和Degner,109:777-798,2018),另一个来自认知神经科学,涉及人类连接体项目的1000多名参与者(Van Essen等人,80:62-79,2013)。我们证明该模型可用于推断可解释的个体水平参数。我们开发了该模型的层次扩展,以测试刺激条件之间的差异,比较不同种族的面孔,以及比较面孔与非面孔刺激。我们还开发了多元回归扩展,以检查模型参数与标准化认知测量(包括列表排序和侧翼任务)上的个体表现之间的关系。我们通过讨论我们的模型如何用于区分潜在的认知过程,如编码失败、抑制失败和绑定失败来得出结论。