Mu and Beta Rhythm Topographies During Motor Imagery and Actual Movements

• Published in: Brain topography Vol. 12; no. 3; pp. 177 - 186
• Main Authors: McFarland, Dennis J., Miner, Laurie A., Vaughan, Theresa M., Wolpaw, Jonathan R.
• Format: Journal Article
• Language: English
• Published: United States Springer Nature B.V 01.03.2000
• Subjects: Adolescent; Adult; Beta Rhythm; Brain Mapping; Female; Functional Laterality - physiology; Humans; Imagination - physiology; Male; Mental Processes - physiology; Middle Aged; Motor Cortex - physiology; Movement - physiology; Somatosensory Cortex - physiology
• ISSN: 0896-0267; 1573-6792
• DOI: 10.1023/A:1023437823106

People can learn to control the 8-12 Hz mu rhythm and/or the 18-25 Hz beta rhythm in the EEG recorded over sensorimotor cortex and use it to control a cursor on a video screen. Subjects often report using motor imagery to control cursor movement, particularly early in training. We compared in untrained subjects the EEG topographies associated with actual hand movement to those associated with imagined hand movement. Sixty-four EEG channels were recorded while each of 33 adults moved left- or right-hand or imagined doing so. Frequency-specific differences between movement or imagery and rest, and between right- and left-hand movement or imagery, were evaluated by scalp topographies of voltage and r spectra, and principal component analysis. Both movement and imagery were associated with mu and beta rhythm desynchronization. The mu topographies showed bilateral foci of desynchronization over sensorimotor cortices, while the beta topographies showed peak desynchronization over the vertex. Both mu and beta rhythm left/right differences showed bilateral central foci that were stronger on the right side. The independence of mu and beta rhythms was demonstrated by differences for movement and imagery for the subjects as a group and by principal components analysis. The results indicated that the effects of imagery were not simply an attenuated version of the effects of movement. They supply evidence that motor imagery could play an important role in EEG-based communication, and suggest that mu and beta rhythms might provide independent control signals.