What cognitive processes drive response biases? A diffusion model analysis
What cognitive processes drive response biases? A diffusion model analysis
复制标题
哪些认知过程会导致反应偏差？
DOI：
10.1017/s1930297500002680
复制
发表时间：
2011
影响因子：
2.5
通讯作者：
R. Ratcliff
中科院分区：
文献类型：
--
作者：
F. Leite;R. Ratcliff
我们使用扩散模型来检验反应偏向操作对反应时间(RT)和准确性的影响，这些数据是在两个包含两个选择的决策任务的实验中收集的。我们要求18名受试者对10×10网格中的星号数量做出“低”或“高”的反应，这是基于实验者决定的决定截止点。在该模型中，证据不断积累，直到达到“低”或“高”的决策标准，这反过来又会引发反应。我们在四个实验条件下进行了两个实验。在条件1和条件2中，低判断和高判断之间的决定界限固定为50。在条件1中，我们操纵了低刺激和高刺激呈现的频率。在条件2中，我们使用了模仿频率操纵的回报结构。我们发现，操纵刺激频率对反应时和准确度的影响比操纵回报结构更大。在模型中，我们发现操纵刺激频率比操纵回报结构在证据积累过程的起点上产生了更大的变化。在条件3和条件4中，我们将决策界限设为40、50或60(实验1)和45或55(实验2)。在条件3中，低刺激和高刺激的数量相等，而在条件4中，低刺激和高刺激的比例不同。模型分析表明，起点的变化解释了刺激比例变化产生的偏差，而证据偏差解释了决策截止点的变化。
We used a diffusion model to examine the effects of response-bias manipulations on response time (RT) and accuracy data collected in two experiments involving a two-choice decision making task. We asked 18 subjects to respond “low” or “high” to the number of asterisks in a 10×10 grid, based on an experimenter-determined decision cutoff. In the model, evidence is accumulated until either a “low” or “high” decision criterion is reached, and this, in turn, initiates a response. We performed two experiments with four experimental conditions. In conditions 1 and 2, the decision cutoff between low and high judgments was fixed at 50. In condition 1, we manipulated the frequency with which low- and high-stimuli were presented. In condition 2, we used payoff structures that mimicked the frequency manipulation. We found that manipulating stimulus frequency resulted in a larger effect on RT and accuracy than did manipulating payoff structure. In the model, we found that manipulating stimulus frequency produced greater changes in the starting point of the evidence accumulation process than did manipulating payoff structure. In conditions 3 and 4, we set the decision cutoff at 40, 50, or 60 (Experiment 1) and at 45 or 55 (Experiment 2). In condition 3, there was an equal number of low- and high-stimuli, whereas in condition 4 there were unequal proportions of low- and high-stimuli. The model analyses showed that starting-point changes accounted for biases produced by changes in stimulus proportions, whereas evidence biases accounted for changes in the decision cutoff.