Groupe d'Imagerie Neurofonctionnelle du DEVeloppement - GINDEV, UMR 6232 (CI-NAPS), CNRS & CEA, Universities of Paris Descartes and Caen, France.
Brain Cogn. 2010 Apr;72(3):378-84. doi: 10.1016/j.bandc.2009.11.004. Epub 2009 Dec 16.
Intuitive predictions and judgments under conditions of uncertainty are often mediated by judgment heuristics that sometimes lead to biases. Using the classical conjunction bias example, the present study examines the relationship between receptivity to metacognitive executive training and emotion-based learning ability indexed by Iowa Gambling Task (IGT) performance. After completing a computerised version of the IGT, participants were trained to avoid conjunction bias on a frequency judgment task derived from the works of Tversky and Kahneman. Pre- and post-test performances were assessed via another probability judgment task. Results clearly showed that participants who produced a biased answer despite the experimental training (individual patterns of the biased --> biased type) mainly had less emotion-based learning ability in IGT. Better emotion-based learning ability was observed in participants whose response pattern was biased --> logical. These findings argue in favour of the capacity of the human mind/brain to overcome reasoning bias when trained under executive programming conditions and as a function of emotional warning sensitivity.
在不确定条件下的直观预测和判断往往受到判断启发式的影响,这些启发式有时会导致偏差。本研究以经典的合取偏差为例,考察了对元认知执行训练的接受程度与以爱荷华赌博任务 (IGT) 表现为指标的情绪学习能力之间的关系。在完成 IGT 的计算机化版本后,参与者被训练在源自特沃斯基和卡尼曼的工作的频率判断任务中避免合取偏差。通过另一个概率判断任务评估前后测表现。结果清楚地表明,尽管进行了实验训练,但仍给出有偏差答案的参与者(有偏差的个体模式-->有偏差的类型)在 IGT 中的情绪学习能力主要较差。在反应模式为有偏差-->逻辑的参与者中观察到更好的情绪学习能力。这些发现支持了人类大脑/思维在执行编程条件下克服推理偏差的能力,并且是情绪预警敏感性的函数。