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Does Real-Time Feedback Affect Sensorimotor EEG Patterns in Routine Motor Imagery Practice?

Anatoly N Vasilyev^1,2, Yury O Nuzhdin¹, Alexander Y Kaplan^1,3

¹Department of Human and Animal Physiology, Faculty of Biology, M.V. Lomonosov Moscow State University, 119234 Moscow, Russia.

|September 28, 2021

Summary

Motor imagery training using brain-computer interfaces (BCIs) did not significantly enhance brain responses compared to open-loop practice. Well-practiced individuals may benefit from simpler, at-home motor imagery (MI) training without real-time feedback.

Keywords:

EEG rhythm brain-computer interface desynchronization generalized eigendecomposition linear mixed effects motor imagery neurorehabilitation open loop sensorimotor vividness

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Published on: August 24, 2017

Area of Science:

Neuroscience
Rehabilitation Medicine
Brain-Computer Interfaces

Background:

Motor imagery (MI) activates similar neural circuits as actual movement, making it valuable for training and neurorehabilitation.
Electroencephalogram (EEG)-based event-related desynchronization (ERD) of sensorimotor rhythms can mark brain activity during MI.
Brain-computer interfaces (BCIs) can provide real-time feedback on brain activity during MI, but their effectiveness compared to open-loop training is unclear.

Purpose of the Study:

To investigate whether BCI-enabled real-time feedback enhances brain responses during motor imagery compared to open-loop training.
To determine the stability of brain activation patterns during motor imagery over time and across different feedback conditions.

Main Methods:

Seven healthy volunteers with prior motor imagery experience underwent six EEG sessions over 4.5 months.
Participants performed kinesthetic imagery of arm and finger movements.
Real-time EEG feedback (closed-loop) was provided in the first and last sessions; other sessions used no feedback (open-loop).
Spatiotemporal and amplitude features of ERD patterns were analyzed using linear mixed-effects modeling.

Main Results:

Spatial sources of ERD were highly stable across sessions for most participants (ρ > 0.94).
Only one subject showed a statistically significant difference in activation patterns between feedback conditions (p = 0.009).
Real-time visual feedback via BCI did not significantly increase ERD strength.

Conclusions:

BCI-enabled feedback did not significantly enhance brain responses during motor imagery in this study.
Well-habituated individuals may achieve motor imagery benefits using simplified, open-loop training methods.
At-home self-practice with simplified setups could be a viable option for motor imagery training.