title: Measuring human locomotor control using EMG and EEG: Current knowledge, limitations and future considerations.
abstract: Electrical signals encoding different forms of information can be observed at multiple levels of the human nervous system. Typically, these signals have been recorded in a rather isolated fashion with little overlap between the static recordings of electroencephalography (EEG) commonly used in neuroscience and the typical surface electromyography (EMG) recordings used in biomechanics. However, within the last decade, there has been an emerging need to link the electrical activation patterns of brain areas during movement to the behavior of the musculoskeletal system. This review discusses some of the most recent studies using the EEG and/or EMG to study the neural control of movement and human locomotion as well as studies quantifying the connectivity between brain and muscles. The focus is on rhythmic locomotor-type activities; however, results are discussed within the framework of initial work that has been done in upper and lower limbs during static and dynamic contractions. Limitations and current challenges as well as the possibility and functional interpretation of studying the connectivity between the cortex and skeletal muscles using a measure of coherence are discussed. The manuscript is geared toward scientists interested in the application of EEG in the field of locomotion, sports and exercise.
authors.affiliation: a Human Performance Laboratory, Faculty of Kinesiology , University of Calgary , Calgary , Canada.
authors.forename: Hendrik
authors.initials: H
authors.lastname: Enders
authors.affiliation: a Human Performance Laboratory, Faculty of Kinesiology , University of Calgary , Calgary , Canada.
authors.forename: Benno M
authors.initials: BM
authors.lastname: Nigg
mesh_terms: D002540:Cerebral Cortex / Q000502:physiology*; D004569:Electroencephalography; D004576:Electromyography; D006801:Humans; D009068:Movement / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*
keywords: Electromyography; brain; electroencephalography; locomotion; movement; muscle