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Updated: Jun 30, 2025

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
Published on: October 20, 2022
Exploration of the influence of the quantification method and reference scheme on feedback-related negativity and
Johannes Rodrigues1, Saskia Müller1, Marko Paelecke1
1Julius-Maximilians-Universität Würzburg, Germany.
Abstract:
Various approaches have been taken over the years to quantify event-related potential (ERP) responses and these approaches may vary in their utility connecting empirical research and scientific claims. In this work we compared different quantification methods as well as the influence of three reference methods (linked mastoids, average reference, and current source density) on the resulting ERP amplitude. We use the experimental effects and effect sizes (Cohen's d) to evaluate the different methodological variants and we calculate intraclass correlation coefficients (ICC). In addition, the bootstrapped standard error of the means (SME, Luck et al., 2021), which was recently suggested as a quality criterion for ERP research, is used for this purpose. Our example for an ERP is the feedback-related negativity (FRN) to feedback about trustee behavior in a trust game with participants in the trustor position. We found that the quantification methods concerning the FRN influenced the absolute value of condition effects in the experimental paradigm. Yet, the patterns of effects were detected by all chosen methods, except for the 'individual difference wave'-based peak window approach. In addition, our findings stress the importance of checking the reference electrodes concerning effects of the experimental conditions. Furthermore, interactions of topographical distribution and reference choice should be considered. Finally, we were able to show that the SME is lower for more datapoints that are given in the quantification period of the FRN, and higher for more negative FRN amplitudes. These biases may lead to divergence of SME and effect size detection. Therefore, if the SME was used to compare different processing choices one should consider controlling for these important aspects of the data and possibly include other quality criteria like effect sizes.
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