Hand movement direction decoded from MEG and EEG

Stephan Waldert, Hubert Preissl, Evariste Demandt, Christoph Braun, Niels Birbaumer, Ad Aertsen, Carsten Mehring

Research output: Contribution to journalArticle

275 Citations (Scopus)

Abstract

Brain activity can be used as a control signal for brain-machine interfaces (BMIs). A powerful and widely acknowledged BMI approach, so far only applied in invasive recording techniques, uses neuronal signals related to limb movements for equivalent, multidimensional control of an external effector. Here, we investigated whether this approach is also applicable for noninvasive recording techniques. To this end, we recorded whole-head MEG during center-out movements with the hand and found significant power modulation of MEG activity between rest and movement in three frequency bands: an increase for ≤7 Hz (low-frequency band) and 62-87 Hz (high-γ band) and a decrease for 10-30 Hz (β band) during movement. Movement directions could be inferred on a single-trial basis from the low-pass filtered MEG activity as well as from power modulations in the low-frequency band, but not from the β and high-γ bands. Using sensors above the motor area, we obtained a surprisingly high decoding accuracy of 67% on average across subjects. Decoding accuracy started to rise significantly above chance level before movement onset. Based on simultaneous MEG and EEG recordings, we show that the inference of movement direction works equally well for both recording techniques. In summary, our results show that neuronal activity associated with different movements of the same effector can be distinguished by means of noninvasive recordings and might, thus, be used to drive a noninvasive BMI.

Original languageEnglish
Pages (from-to)1000-1008
Number of pages9
JournalJournal of Neuroscience
Volume28
Issue number4
DOIs
Publication statusPublished - Jan 23 2008

Fingerprint

Brain-Computer Interfaces
Electroencephalography
Hand
Motor Cortex
Extremities
Head
Brain
Direction compound

Keywords

  • BMI
  • Decoding
  • EEG
  • Hand movement
  • MEG
  • Motor cortex

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Waldert, S., Preissl, H., Demandt, E., Braun, C., Birbaumer, N., Aertsen, A., & Mehring, C. (2008). Hand movement direction decoded from MEG and EEG. Journal of Neuroscience, 28(4), 1000-1008. https://doi.org/10.1523/JNEUROSCI.5171-07.2008

Hand movement direction decoded from MEG and EEG. / Waldert, Stephan; Preissl, Hubert; Demandt, Evariste; Braun, Christoph; Birbaumer, Niels; Aertsen, Ad; Mehring, Carsten.

In: Journal of Neuroscience, Vol. 28, No. 4, 23.01.2008, p. 1000-1008.

Research output: Contribution to journalArticle

Waldert, S, Preissl, H, Demandt, E, Braun, C, Birbaumer, N, Aertsen, A & Mehring, C 2008, 'Hand movement direction decoded from MEG and EEG', Journal of Neuroscience, vol. 28, no. 4, pp. 1000-1008. https://doi.org/10.1523/JNEUROSCI.5171-07.2008
Waldert S, Preissl H, Demandt E, Braun C, Birbaumer N, Aertsen A et al. Hand movement direction decoded from MEG and EEG. Journal of Neuroscience. 2008 Jan 23;28(4):1000-1008. https://doi.org/10.1523/JNEUROSCI.5171-07.2008
Waldert, Stephan ; Preissl, Hubert ; Demandt, Evariste ; Braun, Christoph ; Birbaumer, Niels ; Aertsen, Ad ; Mehring, Carsten. / Hand movement direction decoded from MEG and EEG. In: Journal of Neuroscience. 2008 ; Vol. 28, No. 4. pp. 1000-1008.
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