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Computational and Mathematical Methods in Medicine
Volume 2012, Article ID 451938, 10 pages
Research Article

Enhancing the Signal of Corticomuscular Coherence

1Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands
2MEG-Center, University of Tübingen, Otfried-Müller-Straße 47, 72076 Tübingen, Germany
3Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38100 Trento, Italy
4Department of Cognitive and Educational Sciences (DiSCoF), University of Trento, Via delle Regole 101, 38100 Trento, Italy

Received 18 November 2011; Revised 7 February 2012; Accepted 20 February 2012

Academic Editor: Mingzhou Ding

Copyright © 2012 Cristiano Micheli and Christoph Braun. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The availability of multichannel neuroimaging techniques, such as MEG and EEG, provides us with detailed topographical information of the recorded magnetic and electric signals and therefore gives us a good overview on the concomitant signals generated in the brain. To assess the location and the temporal dynamics of neuronal sources with noninvasive recordings, reconstruction tools such as beamformers have been shown to be useful. In the current study, we are in particular interested in cortical motor control involved in the isometric contraction of finger muscles. To this end we are measuring the interaction between the dynamics of brain signals and the electrical activity of hand muscles. We were interested to find out whether in addition to the well-known correlated activity between contralateral primary motor cortex and the hand muscles, additional functional connections can be demonstrated. We adopted coherence as a functional index and propose a so-called nulling beamformer method which is computationally efficient and addresses the localization of multiple correlated sources. In simulations of cortico-motor coherence, the proposed method was able to correctly localize secondary sources. The application of the approach on real electromyographic and magnetoencephalographic data collected during an isometric contraction and rest revealed an additional activity in the hemisphere ipsilateral to the hand involved in the task.