Assessing brain-muscle connectivity in human locomotion through mobile brain/body imaging: opportunities, pitfalls and future directions
- 1Department of Health Sciences and Technology, ETH Zurich, Switzerland
Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography is capable to non-invasively measure cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artefactual from cerebral sources of activity. This step marked a new opportunity for the investigation of the brains’ role while moving, and was tagged mobile brain/body imaging. This methodology involves simultaneous mobile recording of brain activity with several other body behavioral variables (e.g. muscle activity and kinematics), through wireless recording wearable devices/sensors. Notably, several mobile brain/body imaging studies using EEG-EMG approaches recently showed that the brain is functionally connected to the muscles and active throughout the whole gait cycle and, thus, rejecting the long-lasting idea of a solely spinal-driven bipedalism. However, mobile brain/body imaging and brain/muscle connectivity assessments during human locomotion are still in their fledgling state of investigation. Mobile brain/body imaging approaches hint towards promising opportunities, however, there are some remaining pitfalls that need to be resolved before considering their routine clinical use. This article discusses several of these pitfalls and proposes research to address them. Examples relate to the validity, reliability and reproducibility of this method in ecologically valid scenarios and in different populations. Furthermore, whether brain/muscle connectivity within the mobile brain/body imaging framework represents a potential biomarker in neuromuscular syndromes where gait disturbances are evident (e.g. age-related sarcopenia) remains to be determined.
Keywords: Mobile brain/body imaging (MoBI), independent component analysis (ICA), corticomuscular coherence (CMC), corticokinematic coherence (CKC), functional connectivity, neural drive, Central drive, neuronal synchronization, oscillatory synchronization, Neuronal communication, communication-through-coherence, Walking, Gait, human locomotion, human movement, Electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), Magnetoencephalography (MEG), Central pattern generators (CPG)
Received: 02 Aug 2017;
Accepted: 01 Feb 2018.
Edited by:Parashkev Nachev, University College London, United Kingdom
Reviewed by:Mitsunori Ogihara, University of Miami, United States
Niall Twomey, University of Bristol, United Kingdom
Copyright: © 2018 Gennaro and De Bruin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mr. Federico Gennaro, ETH Zurich, Department of Health Sciences and Technology, Zurich, Switzerland, firstname.lastname@example.org