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A Neural System for Error Detection and Compensation
Analysis of the human event-related brain potentials (ERPs) accompanying errors provides evidence for a neural process whose activity is specifically associated with monitoring and compensating for erroneous behavior.
Is the P300 component a manifestation of context updating?
Abstract To understand the endogenous components of the event-related brain potential (ERP), we must use data about the components' antecedent conditions to form hypotheses about the
Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria.
New guidelines for recording ERPs are presented and criteria for publishing the results are presented, which allow different studies to be compared readily.
Brain-computer interface technology: a review of the first international meeting.
The first international meeting devoted to brain-computer interface research and development is summarized, which focuses on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users.
The mental prosthesis: assessing the speed of a P300-based brain-computer interface.
The data indicate that a P300-based BCI is feasible and practical, however, these conclusions are based on tests using healthy individuals, which indicates that an off line version of the system can communicate at the rate of 7.8 characters a minute and achieve 80% accuracy.
The truth will out: interrogative polygraphy ("lie detection") with event-related brain potentials.
The feasibility of using Event Related Brain Potentials (ERPs) in Interrogative Polygraphy ("Lie Detection") was tested by examining the effectiveness of the Guilty Knowledge Test designed by Farwell
Presidential address, 1980. Surprise!...Surprise?
  • E. Donchin
  • Economics
  • 1 September 1981
The effect of stimulus sequence on the waveform of the cortical event-related potential.
The waveform of the cortical event-related potential is extremely sensitive to variations in the sequence of stimuli preceding the eliciting event and a quantitative model was developed relating the waveform changes to changes in event expectancy.