Dear all,
I need your expertise on this matter. I have an article under review and I got some comments that I need your help with:
In my research, I investigated the FRN (200_300ms post_feedback window) and P3 (300_500 ms post feedback window) components in EEG data . Additionally, I explored the reward prediction error (RPE). Our experimental design consists of three expectancy conditions and two valence feedback (positive, and negative) (3*2 conditions).
Our reviewer pointed out that "The FRN and P3 are defined as mean amplitudes in specific time windows. In this context it is confusing that also latencies of the maximal negativity and positivity were analysed, as these do not necessarily correspond to the respective components. "
The reviewer questioned the rationale behind our RPE analysis. While we based it on the ERP difference between positive and negative feedback, they suggested that single-trial-based modeling of the RPE might be more appropriate. How can we justify our approach and align it better with RPE theory?
What should I do and how should I approach to resolve this.
would greatly appreciate any insights or suggestions from fellow researchers in the field of cognitive neuroscience. Thank you!
All the best
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