To Err is Human: Learning from Error Potentials in Brain-Computer Interfaces
Several studies describe evoked EEG potentials elicited when a subject is aware of an erroneous decision either taken by him or by an external interface. This paper studies Error-related potentials (ErrP) elicited when a human user monitors an external system upon which he has no control whatsoever. In addition, the possibility of using the ErrPs as a learning signals to infer the user’s intended strategy is also addressed. Experimental results show that single-trial recognition of correct and error trials can be achieved, allowing the fast learning of the user’s strategy. These results may constitute the basis of a new kind of human-computer interaction where the former provides monitoring signals that can be used to modify the performance of the latter.
KeywordsTarget Location Reinforcement Learning Erroneous Decision Information Transfer Rate Speed Response Task
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