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Acta Psychologica Sinica    2018, Vol. 50 Issue (12) : 1449-1459     DOI: 10.3724/SP.J.1041.2018.01449
Reports of Empirical Studies |
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 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
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Abstract  

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.

Keywords card switching frequency      the card guessing task      persistence      cognitive flexibility      decision making      voxel-based morphometry      repeated binary-choice     
ZTFLH:  B849: C91  
  B845  
Issue Date: 30 October 2018
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SUN Yachen
ZHANG Hanqi
LI Yonghui
XUE Gui
HE Qinghua
Cite this article:   
SUN Yachen,ZHANG Hanqi,LI Yonghui, et al. To switch or not to switch?Cognitive and neural mechanisms of card switching behavior[J]. Acta Psychologica Sinica, 2018, 50(12): 1449-1459.
URL:  
http://journal.psych.ac.cn/xlxb/EN/10.3724/SP.J.1041.2018.01449     OR     http://journal.psych.ac.cn/xlxb/EN/Y2018/V50/I12/1449
  
  
认知机制 平均数 ± 标准差 与换牌频率的相关
坚持性 116.81 ± 16.61 r (249) = -0.23, p <.001
认知灵活性 4.99 ± 2.16 r (249) = -0.20, p <.001
  
脑区 左/右半球 体素数量 p MNI坐标x MNI坐标y MNI坐标z
后扣带回 1788 0.01 6 -44 22
后扣带回 0.03 -14 -48 34
楔前叶 0.02 -10 -64 26
楔前叶 0.02 10 -58 26
额中回 1522 0.01 -34 24 32
脑岛 0.04 -36 8 2
壳核 0.02 -28 -2 -8
额中回 792 0.01 46 10 50
额极 116 0.03 -34 40 2
  
  
脑区 大脑半球 体素数量 p MNI坐标x MNI坐标y MNI坐标z
颞上回 1541 0.05 66 -16 6
脑岛 0.04 34 -26 12
颞叶 998 0.01 60 12 -26
内侧颞叶 379 0.02 18 -10 -22
颞叶 280 0.02 -56 16 30
  
  
脑区 大脑半球 体素数量 预测准确性 MNI坐标x MNI坐标y MNI坐标z
额中回 222 0.18 -38 22 32
额中回 128 0.16 48 8 48
脑岛 75 0.16 30 -26 20
额极 18 0.16 16 50 46
后扣带回 10 0.15 -2 -44 24
  
  
  
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