ArticleiScience2023
EEG error-related potentials encode magnitude of errors and individual perceptual thresholds.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Error-related potentials detection to enhance human-robot collaboration: a mini review.Frontiers in neuroergonomics · 2026Review
- Error-related potentials during multitasking involving sensorimotor control: an ERP and offline decoding study for brain-computer interface.Frontiers in human neuroscience · 2025Article
- AI reshaping life sciences: intelligent transformation, application challenges, and future convergence in neuroscience, biology, and medicine.Frontiers in digital health · 2025Review
- Electroencephalography signatures of motor error and stimulus-driven attention in electrical muscle stimulation-induced wrist movements under motor imagery.Frontiers in human neuroscience · 2025Article
- Neural interfaces: Bridging the brain to the world beyond healthcare.Exploration (Beijing, China) · 2024Article
- Article
- Yes or no? A study of ErrPs in the "guess what I am thinking" paradigm with stimuli of different visual content.Frontiers in psychology · 2024Article
- Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. We report an experiment with sixteen participants over three sessions in which occasional visual rotations of varying magnitude occurred during a cursor reaching task. We designed a brain-computer interface (BCI) to detect ErrPs that provided real-time feedback. The individual ErrP-BCI decoders exhibited good transfer across sessions and scalability over the magnitude of errors. A non-linear relationship between the ErrP-BCI output and the magnitude of errors predicts individual perceptual thresholds to detect errors. We also reveal theta-gamma oscillatory coupling that co-varied with the magnitude of the required adjustment. Our findings open new avenues to probe and extend current theories of performance monitoring by incorporating continuous human interaction tasks and analysis of the ErrP complex rather than individual peaks.
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