Mental imagery for brain-computer interface control and communication in non-responsive individuals

[en] Background: People who survive severe brain damage may eventually develop a prolonged consciousness disorder. Others can regain full consciousness but remain unable to speak or move because of the severity of the lesions, as for those with locked-in syndrome (LIS). Brain-computer interface techniques can be useful to disentangle these states by detecting neurophysiological correlates of conscious processing of information to enable communication with these individuals after the diagnosis. Objective: The goal of our study was to evaluate with a user-centered design approach the usability of a mental imagery task to detect signs of voluntary information processing and enabling communication in a group of severely disabled individuals. Methods: Five individuals with LIS participated in the study. Participants were instructed to imagine hand, arm or feet movements during electroencephalography (EEG) to detect patterns of event-related synchronization/desynchronization associated with each task. After the user-centered design, usability was evaluated (i.e., efficiency, effectiveness and satisfaction). Results: Two participants achieved significant levels of accuracy in 2 different tasks. The associated workload and levels of satisfaction perceived by the users were moderate and were mainly related to the time demand of the task. Conclusion: Results showed lack of effectiveness of the task to detect voluntary brain activity and thus detect consciousness or communicate with non-responsive individuals. The application must be modified to be sufficiently satisfying for the intended end-users and suggestions are made in this regard. © 2019 Elsevier Masson SAS

Research center :

CHU de Liège-Centre du Cerveau² - ULiège

Disciplines :

Neurosciences & behavior

Author, co-author :

Lugo, Zulay R.; GIGA Consciousness, Coma Science Group, University of Liège, Belgium, Department of Psychology I, University of Würzburg, Germany, French Association of Locked-In Syndrome (ALIS), Boulogne-Billancourt, 92100, France

Pokorny, C.; Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, Graz, Austria

Pellas, F.; French Association of Locked-In Syndrome (ALIS), Boulogne-Billancourt, 92100, France, Coma Arousal Unit, PMR Department, Nîmes University Hospital, Nîmes, France

Noirhomme, Quentin ; Université de Liège - ULiège > GIGA CRC In vivo Imaging

Laureys, Steven ; Université de Liège - ULiège > GIGA Consciousness-Coma Science Group

Müller-Putz, G.; Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, Graz, Austria

Kübler, A.; Department of Psychology I, University of Würzburg, Germany

Language :

English

Title :

Mental imagery for brain-computer interface control and communication in non-responsive individuals

Publication date :

2020

Journal title :

Annals of Physical and Rehabilitation Medicine

ISSN :

1877-0657

eISSN :

1877-0665

Publisher :

Elsevier Masson SAS

Volume :

Issue :

Pages :

21-27

Peer reviewed :

Peer Reviewed verified by ORBi

European Projects :

FP7 - 247919 - DECODER - Deployment of Brain-Computer Interfaces for the Detection of Consciousness in Non-Responsive Patients

Funders :

ALIS - Association du Locked-In Syndrome [FR]
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
UE - Union Européenne [BE]
FEDER - Fonds Européen de Développement Régional [BE]
Fonds Léon Fredericq [BE]
JSMF - James S McDonnell Foundation [US-MO] [US-MO]
MSF - Mind Science Foundation [US-TX] [US-TX]
CE - Commission Européenne [BE]

Available on ORBi :

since 10 July 2020

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Bibliography

Giacino, J.T., Katz, D.I., Schiff, N.D., Whyte, J., Ashman, E.J., Ashwal, S., et al. Comprehensive systematic review update summary: disorders of consciousness: report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology: the American Congress of Rehabilitation Medicine: and the National Institute on Disability, Independent Living, and Rehabilitation Research. Arch Phys Med Rehabil 99 (2018), 1710–1719.
American Congress of Rehabilitation Medecine, Recommendation for use of uniform nomenclature pertinent to patients with severe alterations of consciousness. Arch Phys Med Rehabil 76 (1995), 205–209.
Bauer, G., Gerstenbrand, F., Rumpl, E., Varieties of the locked-in syndrome. J Neurol 221 (1979), 77–91.
Rohaut, B., Raimondo, F., Galanaud, D., Valente, M., Sitt, J.D., Naccache, L., Probing consciousness in a sensory-disconnected paralyzed patient. Brain Inj 31 (2017), 1398–1403.
Schnakers, C., Perrin, F., Schabus, M., Hustinx, R., Majerus, S., Moonen, G., et al. Detecting consciousness in a total locked-in syndrome: an active event-related paradigm. Neurocase 15 (2009), 271–277.
Schiff, N.D., Cognitive motor dissociation following severe brain injuries. JAMA Neurol 72 (2015), 1413–1415.
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M., Brain-computer interfaces for communication and control. Clin Neurophysiol 113 (2002), 767–791.
Owen, A.M., Coleman, M.R., Boly, M., Davis, M.H., Laureys, S., Pickard, J.D., Detecting awareness in the vegetative state. Science, 313, 2006, 1402.
Monti, M.M., Vanhaudenhuyse, A., Coleman, M.R., Boly, M., Pickard, J.D., Tshibanda, L., et al. Willful modulation of brain activity in disorders of consciousness. N Engl J Med 362 (2010), 579–589.
Goldfine, A.M., Victor, J.D., Conte, M.M., Bardin, J.C., Schiff, N.D., Determination of awareness in patients with severe brain injury using EEG power spectral analysis. Clin Neurophysiol 122 (2011), 2157–2168.
Cruse, D., Chennu, S., Chatelle, C., Bekinschtein, T.A., Fernandez-Espejo, D., Pickard, J.D., et al. Bedside detection of awareness in the vegetative state: a cohort study. Lancet 378 (2011), 2088–2094.
Pfurtscheller, G., Solis-Escalante, T., Could the beta rebound in the EEG be suitable to realize a “brain switch”?. Clin Neurophysiol 120 (2009), 24–29.
Kübler, A., Holz, E.M., Riccio, A., Zickler, C., Kaufmann, T., Kleih, S.C., et al. The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications. PLoS One, 9, 2014, e112392.
Kleih, S.C., Nijboer, F., Halder, S., Kübler, A., Motivation modulates the P300 amplitude during brain-computer interface use. Clin Neurophysiol 121 (2010), 1023–1031.
Müller-Putz, G.R., Zimmermann, D., Graimann, B., Nestinger, K., Korisek, G., Pfurtscheller, G., Event-related beta EEG-changes during passive and attempted foot movements in paraplegic patients. Brain Res 1137 (2007), 84–91.
Enghoff, S., Moving ICA and time-frequency analysis in event-related EEH studies of selective attention. 1999, Technical University Denmark.
Makeig, S., Bell, J.A., Jung, T.-P., Sejnowski, T.J., Independent component analysis of electroencephalographic data. Adv Neural Inf Process Syst 8 (1996), 145–151.
McMenamin, B.W., Shackman, A.J., Maxwell, J.S., Bachhuber, D.R.W., Koppenhaver, A.M., Greischar, L.L., et al. Validation of ICA-based myogenic artifact correction for scalp and source-localized EEG. Neuroimage 49 (2010), 2416–2432.
Fisher, R.A., The use of multiple measurements in taxonomic problems. Ann Eugen 7 (1936), 179–188.
Davison, A.C., Hinkley, D.V., Bootstrap methods and their application. 1997, Cambridge University Press.
Müller-Putz, G.R., Scherer, R., Brunner, C., Leeb, R., Pfurtscheller, G., Better than random? A closer look on BCI results. Int J Bioelectromagnetism 10 (2008), 52–55.
Hart, Sandra, G., NASA-task load index (NASA-TLX): 20 years later. Hum Factors Ergon Soc Annu Meting 50 (2006), 904–908.
Moroney, W., Biers, D.W., Eggemeier, F.T., Mitchell, J.A., A comparison of two scoring procedures with the NASA task load index in a simulated flight task. Proc IEEE 2 (1992), 2734–2740.
Byers, C.J., Traditional and raw Task Load Index (TLX) correlations: are paired comparisons necessary?. Advances in Industrial and Ergonomics Safety 1: Taylor and Francis, 1989, 481–485.
Demers, L., Weiss-lambrou, R., Ska, B., The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0): an overview and recent progress. Technol Disabil 14 (2002), 101–105.
Bernheim, J.L., How to get serious answers to the serious question: “How have you been?”: subjective quality of life (QOL) as an individual experiential emergent construct. Bioethics 13 (1999), 272–287.
Houdayer, E., Labyt, E., Cassim, F., Bourriez, J.L., Derambure, P., Relationship between event-related beta synchronization and afferent inputs: analysis of finger movement and peripheral nerve stimulations. Clin Neurophysiol 117 (2006), 628–636.
Li, S., Spasticity motor recovery, and neural plasticity after stroke. Front Neurol, 8, 2017, 120.
Muller-Putz, G.R., Pokorny, C., Klobassa, D.S., Horki, P., A single-switch BCI based on passive and imagined movements: toward restoring communication in minimally conscious patients. Int J Neural Syst, 23, 2013 [1250037].
Ward, N.S., Brown, M.M., Thompson, A.J., Frackowiak, R.S.J., Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain 126 (2003), 2476–2496.
Curley, W.H., Forgacs, P.B., Voss, H.U., Conte, M.M., Schiff, N.D., Characterization of EEG signals revealing covert cognition in the injured brain. Brain 141 (2018), 1404–1421.
Conson, M., Sacco, S., Sara, M., Pistoia, F., Grossi, D., Trojano, L., Selective motor imagery defect in patients with locked-in syndrome. Neuropsychologia 46 (2008), 2622–2628.
Horki, P., Bauernfeind, G., Schippinger, W., Pichler, G., Müller-Putz, G.R., Evaluation of induced and evoked changes in EEG during selective attention to verbal stimuli. J Neurosci Methods 270 (2016), 165–176.
Guger, C., Edlinger, G., Harkam, W., Niedermayer, I., Pfurtscheller, G., How many people are able to operate an EEG-based brain-computer interface (BCI)?. IEEE Trans Neural Syst Rehabil Eng 11 (2003), 145–147.
Friedrich, E.V.C., Scherer, R., Neuper, C., The effect of distinct mental strategies on classification performance for brain-computer interfaces. Int J Psychophysiol 84 (2012), 86–94.
Noirhomme, Q., Brecheisen, R., Lesenfants, D., Antonopoulos, G., Laureys, S., “Look at my classifier's result”: disentangling unresponsive from (minimally) conscious patients. Neuroimage 145 (2017), 288–303.
Kubler, A., Nijboer, F., Mellinger, J., Vaughan, T.M., Pawelzik, H., Schalk, G., et al. Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology 64 (2005), 1775–1777.
Blankertz, B., Sannelli, C., Halder, S., Hammer, E.M., Kubler, A., Muller, K.R., et al. Neurophysiological predictor of SMR-based BCI performance. Neuroimage 51 (2010), 1303–1309.
Ke, Y., Wang, P., Chen, Y., Gu, B., Qi, H., Zhou, P., et al. Training and testing ERP-BCIs under different mental workload conditions. J Neural Eng, 13, 2015 [016007].
Horki, P., Bauernfeind, G., Klobassa, D.S., Pokorny, C., Pichler, G., Schippinger, W., et al. Detection of mental imagery and attempted movements in patients with disorders of consciousness using EEG. Front Hum Neurosci, 8, 2014, 1009.