EEG Analyses of visual cue effects on executed movements

Patrick Suwandjieff, Gernot R. Müller-Putz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: In electroencephalographic (EEG) or electrocorticographic (ECoG) experiments, visual cues are commonly used for timing synchronization but may inadvertently induce neural activity and cognitive processing, posing challenges when decoding self-initiated tasks. New method: To address this concern, we introduced four new visual cues (Fade, Rotation, Reference, and Star) and investigated their impact on brain signals. Our objective was to identify a cue that minimizes its influence on brain activity, facilitating cue-effect free classifier training for asynchronous applications, particularly aiding individuals with severe paralysis. Results: 22 able-bodied, right-handed participants aged 18–30 performed hand movements upon presentation of the visual cues. Analysis of time-variability between movement onset and cue-aligned data, grand average MRCP, and classification outcomes revealed significant differences among cues. Rotation and Reference cue exhibited favorable results in minimizing temporal variability, maintaining MRCP patterns, and achieving comparable accuracy to self-paced signals in classification. Comparison with existing methods: Our study contrasts with traditional cue-based paradigms by introducing novel visual cues designed to mitigate unintended neural activity. We demonstrate the effectiveness of Rotation and Reference cue in eliciting consistent and accurate MRCPs during motor tasks, surpassing previous methods in achieving precise timing and high discriminability for classifier training. Conclusions: Precision in cue timing is crucial for training classifiers, where both Rotation and Reference cue demonstrate minimal variability and high discriminability, highlighting their potential for accurate classifications in online scenarios. These findings offer promising avenues for refining brain-computer interface systems, particularly for individuals with motor impairments, by enabling more reliable and intuitive control mechanisms.

Original languageEnglish
Article number110241
JournalJournal of Neuroscience Methods
Volume410
DOIs
Publication statusPublished - Oct 2024

Keywords

  • Brain-computer interface (BCI)
  • Cue-based
  • Electroencephalogram (EEG)
  • Movement-related cortical potential (MRCP)
  • Self-paced
  • Visual cue
  • Visual evoked potentials (VEPs)

ASJC Scopus subject areas

  • General Neuroscience

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