Tiancheng Yang
Chenghan Xie
Xuehe Wang- 1School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China
- 2College of Engineering, Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong, China
A Correction on
Forgetting phenomena in the Iowa Gambling Task: a new computational model among diverse participants
by Yang, T., Xie, C., and Wang, X. (2025). Front. Psychol. 16:1510151. doi: 10.3389/fpsyg.2025.1510151
In the published article, there was an error. Two sentences in section 5.1. Extension of EEF model with loss aversion, Paragraphs 4 and 5, used outdated statistical values.
Corrections have been made to 5.1 Extension of EEF model with loss aversion, Paragraphs 4 and 5. These paragraphs previously stated:
“Figure 7 shows the comparison of SED and FI, and we can find that although the EEFLA model performed slightly worse than the EEF model (the SED of EEFLA is 1.598, with a difference of 0.106 from the original data, while the SED of EEF has a difference of only 0.008 from the original data; the FI of EEFLA is 4.02, with a difference of 2.22 from the original data, while the FI of EEF has a difference of 2.07), it still outperformed the other models. This indicates that the EEFLA model is still capable of effectively simulating human decision-making behaviors.
However, it can be seen from Figure 8 that the performance of the EEFLA model is not outstanding in terms of parameter recovery and fixed-effects statistical model analysis. The average correlation coefficient for EEFLA's parameter recovery is 0.77155 (range: 0.60 – 0.93), which is lower than the EEF model's 0.8299 (range: 0.64 – 0.96). Additionally, the EEFLA model did not perform well in the previously mentioned fixed-effects statistical model analysis.”
The corrected paragraphs appear below:
“Figure 7 shows the comparison of SED and FI, and we can find that although the EEFLA model performed slightly worse than the EEF model (the SED of EEFLA is 1.598, with a difference of 0.049 from the original data, while the SED of EEF has a difference of only 0.008 from the original data; the FI of EEFLA is 4.02, with a difference of 2.22 from the original data, while the FI of EEF has a difference of 2.11), it still outperformed most of the other models. This indicates that the EEFLA model is still capable of effectively simulating human decision-making behaviors.
However, it can be seen from Figure 8 that the performance of the EEFLA model is not outstanding in terms of parameter recovery and fixed-effects statistical model analysis. The composite correlation coefficient for EEFLA's parameter recovery is 0.785 (range: 0.58–0.93), which is lower than the EEF model's 0.849 (range: 0.69–0.96). Additionally, the EEFLA model did not perform well in the previously mentioned fixed-effects statistical model analysis.”
The original article has been updated.
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Keywords: Forgetting Phenomena, Iowa Gambling Task, Exploitation and Exploration with Forgetting model, Sequential Exploration Decay, Forgetting Interval
Citation: Yang T, Xie C and Wang X (2025) Correction: Forgetting phenomena in the Iowa Gambling Task: a new computational model among diverse participants. Front. Psychol. 16:1642513. doi: 10.3389/fpsyg.2025.1642513
Received: 06 June 2025; Accepted: 17 June 2025;
Published: 03 July 2025.
Edited and reviewed by: Lidia Ghosh, RCC Institute of Information Technology, India
Copyright © 2025 Yang, Xie and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Xuehe Wang, d2FuZ3h1ZWhlQG1haWwuc3lzdS5lZHUuY24=
†These authors share first authorship