Sensorimotor Modulation Assessment and Brain-Computer Interface Training in Disorders of Consciousness

Coyle, Damien; Stow, Jacqueline; McCreadie, Karl; McElligott, Jacinta; Carroll, Áine

doi:10.1016/j.apmr.2014.08.024

Cited by 54 publications

(50 citation statements)

References 21 publications

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“…This underlines the importance of the sensorimotor cortex as part of the SMR's neural substrate (Matsumoto et al, 2010). Recently, it was shown that even individuals in minimally conscious state may have the capacity to regulate SMR-ERD (Coyle et al, 2015) and use this ability for communication. Another tDCS study evidenced a causal link between M1 function and the successful acquisition of abstract skills such as control over SMR-ERD (Soekadar et al, 2015b).…”

Section: Identification Of Biomarkers For Bmi Motor Rehabilitationmentioning

confidence: 98%

Brain–machine interfaces for rehabilitation of poststroke hemiplegia

Ushiba

Soekadar²

2016

Progress in Brain Research

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Section: Identification Of Biomarkers For Bmi Motor Rehabilitationmentioning

confidence: 98%

Brain–machine interfaces for rehabilitation of poststroke hemiplegia

Ushiba

Soekadar²

2016

Progress in Brain Research

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“…To date, 34 VS and other non-responsive patients with a disorder of consciousness (DOC) have demonstrated covert command following (CF) in motor imagery (MI) tasks with EEG (Cruse et al, 2011 , 2012a ; Gibson et al, 2014 ; Horki et al, 2014 ; Coyle et al, 2015 ), or fMRI (Owen et al, 2006 ; Monti et al, 2010 ; Bardin et al, 2011 ; Fernández-Espejo and Owen, 2013 ; Forgacs et al, 2014 ; Gibson et al, 2014 ). Subsequent studies have used selective visual or auditory attention (Schnakers et al, 2008 ; Lulé et al, 2013 ; Naci and Owen, 2013 ; Monti et al, 2014 ; Pan et al, 2014 ), as well as attempted movements (Bekinschtein et al, 2011 ; Cruse et al, 2012b ; Horki et al, 2014 ) to reveal covert awareness in 34 more patients.…”

Section: Introductionmentioning

confidence: 99%

The dissociation between command following and communication in disorders of consciousness: an fMRI study in healthy subjects

Osborne

Owen

Fernández‐Espejo

2015

Front. Hum. Neurosci.

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Neuroimaging studies have identified a subgroup of patients with a Disorder of Consciousness (DOC) who, while being behaviorally non-responsive, are nevertheless able to follow commands by modulating their brain activity in motor imagery (MI) tasks. These techniques have even allowed for binary communication in a small number of DOC patients. However, the majority of patients who can follow commands are unable to use their responses to communicate. A similar dissociation between present command following (CF) and absent communication abilities has been reported in overt behavioral assessments. However, the neural correlates of this dissociation in both overt and covert modalities are unknown. Here, we used functional magnetic resonance imaging (fMRI) to explore the neural mechanisms underlying CF and selection of responses for binary communication using either executed or imagined movements. Fifteen healthy participants executed or imagined two different types of arm movements that were either pre-determined by the experimenters (CF) or decided by them (action selection, AS). Action selection involved greater activity in high-level associative areas in frontal and parietal regions than CF. Additionally, motor execution (ME), as compared to MI, activated contralateral motor cortex, while the opposite contrast revealed activation in the ipsilateral sensorimotor cortex and the left inferior frontal gyrus. Importantly, there was no interaction between the task (CF/AS) and modality (MI/ME). Our results suggest that the neural processes involved in following a motor command or selecting between two motor actions are not dependent on how the response is expressed (via ME/MI). They also suggest a potential neural basis for the distinction in cognitive abilities seen in DOC patients.

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“…For these patients that have been erroneously diagnosed with DoC, BCI can be used to diagnose their consciousness even in the absence of any behavioural response. To do so, these patients may be asked to control a given BCI, such as a motor-imagery BCI [122], or a P300-based BCI [123]. If the patient manages to control the BCI, i.e., if the patients' EEG signals can be discriminated according to the instructions, it means the patient can cognitively respond (by performing motor imagery tasks or by attending stimulus) and therefore that he/she is conscious.…”

Section: Bci and Disorder Of Consciousnessmentioning

confidence: 99%

Electroencephalography (EEG)‐Based Brain–Computer Interfaces

Lotte

Bougrain

Clerc

2015

Wiley Encyclopedia of Electrical and Electronics Engineering

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Brain-Computer Interfaces (BCI) are systems that can translate the brain activity patterns of a user into messages or commands for an interactive application. The brain activity which is processed by the BCI systems is usually measured using Electroencephalography (EEG). In this article, we aim at providing an accessible and up-to-date overview of EEG-based BCI, with a main focus on its engineering aspects. We notably introduce some basic neuroscience background, and explain how to design an EEG-based BCI, in particular reviewing which signal processing, machine learning, software and hardware tools to use. We present Brain Computer Interface applications, highlight some limitations of current systems and suggest some perspectives for the field.

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Sensorimotor Modulation Assessment and Brain-Computer Interface Training in Disorders of Consciousness

Cited by 54 publications

References 21 publications

Brain–machine interfaces for rehabilitation of poststroke hemiplegia

Brain–machine interfaces for rehabilitation of poststroke hemiplegia

The dissociation between command following and communication in disorders of consciousness: an fMRI study in healthy subjects

Electroencephalography (EEG)‐Based Brain–Computer Interfaces

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