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Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Published on: September 1, 2023

Shutting Down Sensorimotor Interferences after Stroke: A Proof-of-Principle SMR Neurofeedback Study.

Johanna L Reichert¹, Silvia E Kober¹, Daniela Schweiger²

¹Institute of Psychology, University of GrazGraz, Austria; BioTechMed GrazGraz, Austria.

Frontiers in Human Neuroscience

|July 30, 2016

Summary

Sensorimotor rhythm (SMR) neurofeedback training improved cognitive function and brain activity in a stroke patient and healthy elderly individuals. This neurofeedback approach shows promise for cognitive rehabilitation after stroke.

Keywords:

aging memory neurofeedback sensorimotor rhythm stroke

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Area of Science:

Neuroscience
Cognitive Rehabilitation
Brain-Computer Interfaces

Background:

Neurofeedback training aims to improve self-regulation of brain activity for cognitive, emotional, and physiological functions.
While promising for cognitive rehabilitation in neurological diseases like stroke, research on neurofeedback's feasibility and efficiency is limited.

Purpose of the Study:

To investigate the behavioral and electrophysiological effects of sensorimotor rhythm (SMR) neurofeedback in a stroke patient.
To compare the effects in a stroke patient with a healthy elderly control group.

Main Methods:

A 74-year-old stroke patient (UG20) and 10 healthy elderly controls underwent 10 sessions of SMR neurofeedback.
Behavioral and electrophysiological (multichannel EEG, event-related potentials - ERPs, coherence) assessments were conducted before and after training during non-verbal and verbal learning tasks.

Main Results:

Both UG20 and controls successfully regulated SMR activity.
UG20 showed improved performance in a non-verbal learning task, increased P3 amplitude, and decreased central-parietal coherence post-training.
Healthy controls also exhibited behavioral improvements and trends towards similar electrophysiological changes.

Conclusions:

SMR neurofeedback is feasible and effective in a stroke patient and healthy elderly individuals.
The training may reduce sensorimotor interferences, benefiting semantic encoding and retrieval processes.