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| The Computational Models and Neural Mechanisms of the Speed-Accuracy Trade-Off |
| Ming Qian-guo1 Kang Yin-shi2 Xiu Xi-wang3 |
| 1. Behavioral Science Institute, Radboud University, Nijmegen, 6525GD, Netherlands; 2. School of Psychology，South China Normal University，Guangzhou 510631，China; 3. School of education, Handan University, Handan, 056005, China |
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Abstract The speed-accuracy trade-off is a common phenomenon in decision-making and action control, where humans and animals often need to balance between ensuring accuracy and speeding up their response. Computational modeling has become a cornerstone in research dedicated to elucidating this phenomenon. This article offers a comprehensive review of quintessential sequential sampling models, including the drift-diffusion model and urgency signal models, which have been instrumental in interpreting the speed-accuracy trade-off. Furthermore, we encapsulate findings from neural imaging studies that delve into this trade-off. Future research should focus on examining the influence of contextual factors on decision strategies in speed-accuracy trade-off, investigating their relationship with personality traits and other cognitive functions, and refining the link between neural mechanisms and computational models of the speed-accuracy trade-off.
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Published: 13 September 2023
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| Cite this article: |
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Ming Qian-guo,Kang Yin-shi,Xiu Xi-wang. The Computational Models and Neural Mechanisms of the Speed-Accuracy Trade-Off[J]. 应用心理学, 2024, 30(5): 457-469.
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| URL: |
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http://www.appliedpsy.cn/EN/Y2024/V30/I5/457 |
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