EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

Fumiaki Iwane; Aleksander Sobolewski; Ricardo Chavarriaga; José Del R Millán

doi:10.1016/j.isci.2023.107524

EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

iScience. 2023 Aug 2;26(9):107524. doi: 10.1016/j.isci.2023.107524. eCollection 2023 Sep 15.

Authors

Fumiaki Iwane^{1

2

3}, Aleksander Sobolewski^{4

5}, Ricardo Chavarriaga^{5

6}, José Del R Millán^{1

2

5

7}

Affiliations

¹ Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
² Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.
³ Learning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
⁴ Wyss Center for Bio and Neuroengineering, Campus Biotech, 1202 Genève, Switzerland.
⁵ École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland.
⁶ Centre for Artificial Intelligence, Zurich University of Applied Sciences (ZHAW), 8401 Winterthur, Switzerland.
⁷ Mulva Clinic for the Neurosciences, The University of Texas at Austin, Austin, TX 78712, USA.

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.

Keywords: Cognitive neuroscience; Neuroscience.