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How does the Reward Prediction Error (RPE) support neurofeedback training in IFEN Race?
IFEN Race is a neurofeedback racing game that utilizes the Reward Prediction Error (RPE), the brain's key reinforcement learning signal. The player's brainwave criteria are displayed in real time, and meeting them immediately leads to smoother forward movement, diamond collection, and safer driving—while deviating from the target state visibly degrades performance. In "stop-and-go" mode, the game pauses when the criteria are not met and resumes as soon as they are. This creates clear positive and negative RPE updates, helping users implicitly discover the self-regulatory state that keeps the car moving. Progress tracking via a leaderboard (duration, total score, date) supports long-term motivation, while customizations (vehicle appearance, background color, music) maintain engagement across repeated sessions.
Neurofeedback is understood as a self-regulation process based on reinforcement learning, in which self-regulation is acquired through contingent feedback.
Motivation, the salience of the reinforcer, and sustained engagement are considered important moderators of learning success. Since the subjective motivational value of feedback can vary between individuals and decrease with repeated exposure, the adaptive design of feedback environments is discussed as an approach to maintain effective reinforcement.
Against this background, offering multiple feedback or game options can be understood as a theoretically sound strategy to support engagement, reduce habituation effects, and maintain the reinforcing value of feedback across training sessions, thereby potentially promoting the stability of learning and the transfer of effects (Schwartz & Andrasik, 2016; Enriquez-Geppert et al., 2017; Lubianiker et al., 2022; Sitaram et al., 2024).
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