ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2018, Vol. 50 ›› Issue (12): 1449-1459.doi: 10.3724/SP.J.1041.2018.01449

• Reports of Empirical Studies • Previous Articles    

To switch or not to switch?Cognitive and neural mechanisms of card switching behavior

SUN Yachen1#,ZHANG Hanqi2,3#,LI Yonghui4,XUE Gui2(),HE Qinghua1,4()   

  1. 1 Faculty of Psychology, Key Lab of Cognition and Personality, Chongqing Collaborative Innovation Center for Brain Science, Southwest University, Chongqing 400715, China
    2 Faculty of Psychology, National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
    3 School of Psychology and Cognitive Sciences, Peking University, Beijing 100871, China
    4 Institute of Psychology, Key Laboratory of Mental Health, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2017-10-24 Published:2018-12-25 Online:2018-10-30


Decision making is a common, frequent and important task. It is not uniform though; there are individual differences in decision making processes. One notable differences between decision makers is in repeated binary choice situations. Specifically, when facing repeated binary choices, some people keep choosing the same option while others often switch. Previous research used a random card guessing task to explore the underlying mechanism of such differences in choice strategy. In this task, participants are asked to match a computer-generated “random” choice of a black or red card. The computer does not follow a random choice pattern; it follows a canonical random sequence generated by a Bernoulli process characterized by an equal numbers of black and red choices, switch of color on half of the trials, and streak length following an exponential distribution. In theory, participants should guess cards randomly. Nevertheless, they switch significantly less often than the computer does. In other words, participants present some change resistance and have an increased likelihood to select the same card; this likelihood varies among participants. One notable gap in this research stream pertains to the underlying cognitive and neural mechanism of such card switching behaviors. We partially address this gap in this study.

Three hundred and fifty healthy Chinese college students (194 females, mean age = 19.97 years) were recruited for this study. All of them completed the Card Guessing Task, the Temperament and Character Inventory-Revised (TCI-R), and the Wisconsin Card Sorting Test (WCST). One session of high-resolution magnetic resonance anatomical image was also acquired for each individual using a 3T MRI scanner. First, subjects’ frequency of switching, persistence error on the WCST as an index for cognitive flexibility, and persistence dimension score on TCI-R were calculated. Next, the correlation between gray matter volume (GMV) and frequency of switching was tested with both univariate and multivariate voxel-based morphometry (VBM). In addition, the mediation roles of trait persistence and cognitive flexibility in the GMV and switching frequency were tested.

Results suggested that the mean frequency of card switching in our sample was 43%, which was significantly lower than 50% (p < 0.001). Importantly, the number varied from 0% to 80%, suggesting large between-individual differences. Correlation analysis showed that both trait persistence and cognitive flexibility negatively correlated with card switching frequency. Univariate VBM analysis showed that (1) the GMV in the Frontal Pole (FP), Posterior Cingulate Gyrus (PCC), Putamen and the left Insular Cortex positively correlated with the card switching frequency, and (2) the GMV in the Medial Temporal Lobe and right Insular Cortex negatively correlated with card switching frequency. Multivariate VBM analysis suggested that the GMV of Posterior Cingulate Gyrus (PCC), Middle Frontal Gyrus (MFG), Insular Cortex, and Frontal Pole could significantly predict individuals’ frequency of card switching. Last, mediation analysis revealed that both trait persistence and cognitive flexibility mediate the relationship between GMV of the implicated regions and card switching frequency.

Overall, this study examined individual differences in card switching frequency and the cognitive and neural mechanisms that underlie them. Understanding the reason why some people persist in choosing the same option, while others frequently change their choices is important, and can serve as a basis for understating complex decision making situations that follow a repeated binary choice pattern.

Key words: card switching frequency, the card guessing task, persistence, cognitive flexibility, decision making, voxel-based morphometry, repeated binary-choice

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