EEG error-related potentials encode magnitude of errors and individual perceptual thresholds
Fumiaki Iwane1,2,3, Aleksander Sobolewski4,5, Ricardo Chavarriaga5,6
1Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Iscience
|August 28, 2023
Summary
Error-related potentials (ErrPs), brain signals linked to performance monitoring, can predict individual error detection thresholds. This research advances understanding of brain-computer interfaces and learning.
Area of Science:
- Neuroscience
- Cognitive Science
- Human-Computer Interaction
Background:
- Error-related potentials (ErrPs) are key electroencephalogram (EEG) markers for performance monitoring and behavioral adaptation.
- The extent to which ErrPs encode information beyond simple error detection remains largely unexplored.
Purpose of the Study:
- To investigate if ErrPs contain information about the magnitude of errors.
- To develop and validate a brain-computer interface (BCI) for real-time ErrP detection and feedback.
- To explore the relationship between ErrP characteristics and error magnitude.
Main Methods:
- An experiment involving 16 participants over three sessions, using a cursor reaching task with visual rotations of varying magnitudes.
- Development of a BCI system to detect ErrPs and provide real-time feedback.
- Analysis of EEG data, focusing on ErrP characteristics and theta-gamma oscillatory coupling.
Main Results:
- Individualized ErrP-BCI decoders demonstrated robust transferability across sessions and scalability with error magnitude.
- A non-linear relationship was found between ErrP-BCI output and error magnitude, predicting individual perceptual thresholds for error detection.
- Theta-gamma oscillatory coupling correlated with the magnitude of the necessary behavioral adjustment.
Conclusions:
- ErrPs encode more detailed information about performance errors than previously understood, including magnitude.
- BCIs can effectively decode ErrPs in real-time, offering a new tool for studying performance monitoring.
- Findings suggest incorporating continuous interaction tasks and comprehensive ErrP analysis to refine theories of performance monitoring.
