CORRECTION article

Front. Psychol., 03 July 2025

Sec. Decision Neuroscience

Volume 16 - 2025 | https://doi.org/10.3389/fpsyg.2025.1642513

Correction: Forgetting phenomena in the Iowa Gambling Task: a new computational model among diverse participants

  • 1. School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China

  • 2. College of Engineering, Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong, China

Article metrics

View details

805

Views

205

Downloads

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 Extension of EEF model with loss aversion, Paragraphs 4 and 5, used outdated statistical values.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.

Statements

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

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

Volume

16 - 2025

Edited and reviewed by

Lidia Ghosh, RCC Institute of Information Technology, India

Updates

Copyright

*Correspondence: Xuehe Wang

†These authors share first authorship

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics