title: Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review.
abstract: Recent research has reached a consensus on the feasibility of motor imagery brain-computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most MI-BCI systems rely on temporal, spectral, and spatial features of single channels to distinguish different MI patterns. However, no successful communication has been established for a completely locked-in subject. To provide more useful and informative features, it has been recommended to take into account the relationships among electroencephalographic (EEG) sensor/source signals in the form of brain connectivity as an efficient tool of neuroscience. In this review, we briefly report the challenges and limitations of conventional MI-BCIs. Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI-BCI performance. An extensive literature on EEG-based MI brain connectivity analysis of healthy subjects is reviewed. We subsequently discuss the brain connectomes during left and right hand, feet, and tongue MI movements. Moreover, key components involved in brain connectivity analysis that considerably affect the results are explained. Finally, possible technical shortcomings that may have influenced the results in previous research are addressed and suggestions are provided.
authors.affiliation: Center for Biomedical Engineering and Faculty of Bioscience and Medical Engineering, Universiti Teknologi Malaysia, Skudai, 81310 Johor Bahru, Malaysia hamedi.mahyar@gmail.com.
authors.forename: Mahyar
authors.initials: M
authors.lastname: Hamedi
authors.affiliation: Center for Biomedical Engineering, Universiti Teknologi Malaysia, Skudai, 81310 Johor Bahru, Malaysia hussain@fke.utm.my.
authors.forename: Sh-Hussain
authors.initials: ShH
authors.lastname: Salleh
authors.affiliation: Center for Biomedical Engineering, Universiti Teknologi Malaysia, Skudai, 81310 Johor Bahru, Malaysia alias@mail.fkm.utm.my.
authors.forename: Alias Mohd
authors.initials: AM
authors.lastname: Noor
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D062207:Brain-Computer Interfaces / Q000639:trends; D004569:Electroencephalography / Q000379:methods* / Q000639:trends; D006801:Humans; D019018:Imagery, Psychotherapy / Q000379:methods / Q000639:trends; D007092:Imagination / Q000502:physiology*; D009048:Motor Skills / Q000502:physiology; D009415:Nerve Net / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*