ISSN 0439-755X
CN 11-1911/B

心理学报 ›› 2022, Vol. 54 ›› Issue (11): 1340-1353.doi: 10.3724/SP.J.1041.2022.01340

• 研究报告 • 上一篇    下一篇


冯霞1, 冯成志2()   

  1. 1南通大学教育科学学院, 江苏 南通 226019
    2苏州大学心理系, 江苏 苏州 215123
  • 收稿日期:2021-07-21 出版日期:2022-11-25 发布日期:2022-09-08
  • 通讯作者: 冯成志
  • 基金资助:

The effect of cognitive flexibility on probabilistic category learning

FENG Xia1, FENG Chengzhi2()   

  1. 1School of Education Science, Nantong University, Nantong 226019, China
    2Department of Psychology, School of Education, Soochow University, Suzhou 215123, China
  • Received:2021-07-21 Online:2022-11-25 Published:2022-09-08
  • Contact: FENG Chengzhi


本研究采用“数字-字母转换任务”区分高低认知灵活性者, 构建概率配对模式相同但形式不同的两个概率类别学习任务, 借助ERP技术探讨认知灵活性对概率类别学习任务的作用特点与机制。结果发现, 本研究的两个任务中, 高认知灵活性组的规则习得水平均优于低认知灵活性组, 认知灵活性能促进概率类别的学习。同时, 对不同学习阶段的ERPs分析结果显示, 高认知灵活性者在概率类别学习中的优势源于反馈加工过程。

关键词: 认知灵活性, 概率, 规则学习, 反馈相关负波(FRN), P300


Cognitive flexibility is related to one’s level of cognitive ability and creativity, and is an important feature of intelligence. With regard to probabilistic cue learning, whether the level of cognitive flexibility has an impact on the learning process in young adults remains to be studied. We addressed these questions by taking advantage of the event-related potentials (ERP) technique in two rule tasks with the same probability properties, which aimed to see how learners' cognitive flexibility promotes the dynamic process of probabilistic category learning, and its underlying neural mechanisms.

We chose the “number-letter task” as the effective tool to assess learners’ cognitive flexibility level based on previous research and pilot testing. The participants were ranked according to their switch cost. The first 27% (smaller switch cost) were assigned to the high flexibility group, and the last 27% were assigned to the low group. All participants completed the picture selection task and the coin search task in the EEG environment on two occasions with a two week interval in between. The two tasks had the same probability pairs (0-1/3, 0-2/3, 1/3-2/3, 1-1/3), yet were different in form. Leaning curves for different groups, accuracy, latency, and ERPs at different learning stages were recorded and analyzed for each task.

Behavioral results showed that in these two tasks, learners with high flexibility had a higher rule acquisition rate, although the high and low groups did not show any difference in rule acquisition speed. Learners' cognitive flexibility had cross-task advantages in probabilistic cue rule learning. For the ERP results, in the picture selection task there was a marginally significant difference between the two groups in the amplitude of the P300 component under the condition of preacquisiton-high - probability-reward. The advantage of high flexibility in rule learning was mainly due to the higher efficiency of feedback learning. In the coin search task, there was a significant difference between high and low flexibility groups in the amplitude of the FRN component under the conditions of preacquisiton- expectation and the conditions of postacquisition -unexpectation. Furthermore, only the low flexibility group showed a significant difference between the high and low probability conditions in the amplitude of the P300 component.

In conclusion, the study suggests that learners with high cognitive flexibility have a cross-task advantage in probabilistic category learning, which is mainly due to more efficient feedback learning.

Key words: cognitive flexibility, probability, rule learning, feedback-related negativity (FRN), P300


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