Matthias Witte and Ferran Galán contributed equally to this work.
Concurrent stable and unstable cortical correlates of human wrist movements
Version of Record online: 22 JAN 2014
Copyright © 2014 Wiley Periodicals, Inc.
Human Brain Mapping
Volume 35, Issue 8, pages 3867–3879, August 2014
How to Cite
Witte, M., Galán, F., Waldert, S., Braun, C. and Mehring, C. (2014), Concurrent stable and unstable cortical correlates of human wrist movements. Hum. Brain Mapp., 35: 3867–3879. doi: 10.1002/hbm.22443
- Issue online: 8 JUL 2014
- Version of Record online: 22 JAN 2014
- Manuscript Accepted: 25 NOV 2013
- Manuscript Revised: 6 NOV 2013
- Manuscript Received: 8 FEB 2013
- German Federal Ministry of Education and Research (BMBF). Grant Number: 01GQ0761/2 (to Bernstein cooperation Tübingen-Freiburg) and BMBF grant 01GQ0831 (to Bernstein Focus Neurotechnology Freiburg-Tübingen) Deutsche Forschungsgemeinschaft; DFG EXC 307 (to Werner Reichardt Centre for Integrative Neuroscience (CIN) at the University of Tuebingen)
- brain-machine interface;
- movement decoding;
Cortical activity has been shown to correlate with different parameters of movement. However, the dynamic properties of cortico-motor mappings still remain unexplored in humans. Here, we show that during the repetition of simple stereotyped wrist movements both stable and unstable correlates simultaneously emerge in human sensorimotor cortex. Using visual feedback of wrist movement target inferred online from MEG, we assessed the dynamics of the tuning properties of two neuronal signals: the MEG signal below 1.6 Hz and within the 4 to 6 Hz range. We found that both components are modulated by wrist movement allowing for closed-loop inference of movement targets. Interestingly, while tuning of 4 to 6 Hz signals remained stable over time leading to stable inference of movement target using a static classifier, the tuning of cortical signals below 1.6 Hz significantly changed resulting in steadily decreasing inference accuracy. Our findings demonstrate that non-invasive neuronal population signals in human sensorimotor cortex can reflect a stable correlate of voluntary movements. Hence, we provide first evidence for a stable control signal in non-invasive human brain-machine interface research. However, as not all neuronal signals initially tuned to movement were stable across days, a careful selection of features for real-life applications seems to be mandatory. Hum Brain Mapp 35:3867–3879, 2014. © 2014 Wiley Periodicals, Inc.