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Updated: Mar 18, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
Published on: March 10, 2011
Oscillatory profiles of positive, negative and neutral feedback stimuli during adaptive decision making
Peng Li1, Travis E Baker2, Chris Warren3
1Brain Function and Psychological Science Research Center, Shenzhen University, Shenzhen, China.
Abstract:
The electrophysiological response to positive and negative feedback during reinforcement learning has been well documented over the past two decades, yet, little is known about the neural response to uninformative events that often follow our actions. To address this issue, we recorded the electroencephalograph (EEG) during a time-estimation task using both informative (positive and negative) and uninformative (neutral) feedback. In the time-frequency domain, uninformative feedback elicited significantly less induced beta-gamma activity than informative feedback. This result suggests that beta-gamma activity is particularly sensitive to feedback that can guide behavioral adjustments, consistent with other work. In contrast, neither theta nor delta activity were sensitive to the difference between negative and neutral feedback, though both frequencies discriminated between positive, and non-positive (neutral or negative) feedback. Interestingly, in the time domain, we observed a linear relationship in the amplitude of the feedback-related negativity (neutral>negative>positive), a component of the event-related brain potential thought to index a specific kind of reinforcement learning signal called a reward prediction error. Taken together, these results suggest that the reinforcement learning system treats neutral feedback as a special case, providing valuable information about the electrophysiological measures used to index the cognitive function of frontal midline cortex.
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