Adult; Brain/blood supply/physiopathology; Brain Mapping; Choice Behavior/physiology; Communication; Consciousness/physiology; Female; Humans; Magnetic Resonance Imaging/methods; Male; Neuropsychological Tests; Online Systems; Oxygen/blood; Signal Processing, Computer-Assisted; Statistics as Topic; User-Computer Interface; Young Adult
Abstract :
[en] The term 'locked-in'syndrome (LIS) describes a medical condition in which persons concerned are severely paralyzed and at the same time fully conscious and awake. The resulting anarthria makes it impossible for these patients to naturally communicate, which results in diagnostic as well as serious practical and ethical problems. Therefore, developing alternative, muscle-independent communication means is of prime importance. Such communication means can be realized via brain-computer interfaces (BCIs) circumventing the muscular system by using brain signals associated with preserved cognitive, sensory, and emotional brain functions. Primarily, BCIs based on electrophysiological measures have been developed and applied with remarkable success. Recently, also blood flow-based neuroimaging methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), have been explored in this context. After reviewing recent literature on the development of especially hemodynamically based BCIs, we introduce a highly reliable and easy-to-apply communication procedure that enables untrained participants to motor-independently and relatively effortlessly answer multiple-choice questions based on intentionally generated single-trial fMRI signals that can be decoded online. Our technique takes advantage of the participants' capability to voluntarily influence certain spatio-temporal aspects of the blood oxygenation level-dependent (BOLD) signal: source location (by using different mental tasks), signal onset and offset. We show that healthy participants are capable of hemodynamically encoding at least four distinct information units on a single-trial level without extensive pretraining and with little effort. Moreover, real-time data analysis based on simple multi-filter correlations allows for automated answer decoding with a high accuracy (94.9%) demonstrating the robustness of the presented method. Following our 'proof of concept', the next step will involve clinical trials with LIS patients, undertaken in close collaboration with their relatives and caretakers in order to elaborate individually tailored communication protocols. As our procedure can be easily transferred to MRI-equipped clinical sites, it may constitute a simple and effective possibility for online detection of residual consciousness and for LIS patients to communicate basic thoughts and needs in case no other alternative communication means are available (yet)--especially in the acute phase of the LIS. Future research may focus on further increasing the efficiency and accuracy of fMRI-based BCIs by implementing sophisticated data analysis methods (e.g., multivariate and independent component analysis) and neurofeedback training techniques. Finally, the presented BCI approach could be transferred to portable fNIRS systems as only this would enable hemodynamically based communication in daily life situations.
Allison B.Z., Wolpaw E.W., and Wolpaw J.R. Brain-computer interface systems: Progress and prospects. Expert Review of Medical Devices 4 (2007) 463-474
Bagarinao E., Nakai T., and Tanaka Y. Real-time functional MRI: Development and emerging applications. Magnetic Resonance in Medical Sciences 5 (2006) 157-165
Bauer G., Gerstenbrand F., and Rumpl E. Varieties of the locked-in syndrome. Journal of Neurology 221 (1979) 77-91
Birbaumer N., and Cohen L.G. Brain-computer interfaces: Communication and restoration of movement in paralysis. The Journal of Physiology 579 (2007) 621-636
Birbaumer N., Ghanayim N., Hinterberger T., Iversen I., Kotchoubey B., Kubler A., et al. A spelling device for the paralysed. Nature 398 (1999) 297-298
Birbaumer N., Murguialday A.R., and Cohen L. Brain-computer interface in paralysis. Current Opinion in Neurology 21 (2008) 634-638
Birbaumer, N., Weiskopf, N., Weber, C., Kubler, A., Goebel, R., Caria, A., et al. (2006). An fMRI-Brain-computer-interface for the conditioning of the fear circuit in psychopaths. 12th Annual Meeting of the Organization for Human Brain Mapping. Florence, Italy.
Bruno M., Bernheim J.L., Schnakers C., and Laureys S. Locked-in: Don't judge a book by its cover. Journal of Neurology, Neurosurgery, and Psychiatry 79 (2008) 2
Buch E., Weber C., Cohen L.G., Braun C., Dimyan M.A., Ard T., et al. Think to move: A neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke 39 (2008) 910-917
Coyle S., Ward T., Markham C., and McDarby G. On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces. Physiological Measurement 25 (2004) 815-822
Dahmen, B., Sorger, B., Sinke, C. B. A., & Goebel, R. (2008). When the brain takes BOLD 'steps': Controlling differential brain activation levels via real-time fMRI-based neurofeedback training. 14th Annual Meeting of the Organization for Human Brain Mapping (Vol. 41, p. 43). Melbourne: Elsevier.
deCharms R.C. Reading and controlling human brain activation using real-time functional magnetic resonance imaging. Trends in Cognitive Sciences 11 (2007) 473-481
deCharms R.C., Maeda F., Glover G.H., Ludlow D., Pauly J.M., Soneji D., et al. Control over brain activation and pain learned by using real-time functional MRI. Proceedings of the National Academy of Sciences of the United States of America 102 (2005) 18626-18631
Eskandari P., and Erfanian A. Improving the performance of brain-computer interface through meditation practicing. Conference of the IEEE Engineering in Medicine and Biology Society (2008) 662-665
Esposito F., Seifritz E., Formisano E., Morrone R., Scarabino T., Tedeschi G., et al. Real-time independent component analysis of fMRI time-series. Neuroimage 20 (2003) 2209-2224
Felton E.A., Wilson J.A., Williams J.C., and Garell P.C. Electrocorticographically controlled brain-computer interfaces using motor and sensory imagery in patients with temporary subdural electrode implants. Report of four cases. Journal of Neurosurgery 106 (2007) 495-500
Friston K.J., Fletcher P., Josephs O., Holmes A., Rugg M.D., and Turner R. Event-related fMRI: Characterizing differential responses. Neuroimage 7 (1998) 30-40
Goebel, R., Sorger, B., Birbaumer, N., & Weiskopf, N. (2005). Learning to play BOLD Brain Pong: From individual neurofeedback training to brain-brain interactions. 11th Annual Meeting of the Organization for Human Brain Mapping. Toronto.
Goebel, R., Sorger, B., Kaiser, J., Birbaumer, N., & Weiskopf, N. (2004). BOLD brain pong: Self regulation of local brain activity during synchronously scanned, interacting subjects. 34th Annual Meeting of the Society for Neuroscience. San Diego.
Gosseries O., Demertzi A., Noirhomme Q., Tshibanda J., Boly M., de Beeck M.O., et al. Functional neuroimaging (fMRI, PET and MEG): What do we measure?. Revue Medicale de Liege 63 (2008) 231-237
Handwerker D.A., Ollinger J.M., and D'Esposito M. Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses. Neuroimage 21 (2004) 1639-1651
Hochberg L.R., Serruya M.D., Friehs G.M., Mukand J.A., Saleh M., Caplan A.H., et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442 (2006) 164-171
Hwang H.J., Kwon K., and Im C.H. Neurofeedback-based motor imagery training for brain-computer interface (BCI). Journal of Neuroscience Methods 179 (2009) 150-156
Irani F., Platek S.M., Bunce S., Ruocco A.C., and Chute D. Functional near infrared spectroscopy (fNIRS): An emerging neuroimaging technology with important applications for the study of brain disorders. The Clinical Neuropsychologist 21 (2007) 9-37
Iversen I.H., Ghanayim N., Kubler A., Neumann N., Birbaumer N., and Kaiser J. A brain-computer interface tool to assess cognitive functions in completely paralyzed patients with amyotrophic lateral sclerosis. The Clinical Neuropsychologist 119 (2008) 2214-2223
Karim A.A., Hinterberger T., Richter J., Mellinger J., Neumann N., Flor H., et al. Neural internet: Web surfing with brain potentials for the completely paralyzed. Neurorehabilitation and Neural Repair 20 (2006) 508-515
Kubler A., Furdea A., Halder S., Hammer E.M., Nijboer F., and Kotchoubey B. A brain-computer interface controlled auditory event-related potential (p300) spelling system for locked-in patients. Annals of the New York Academy of Sciences 1157 (2009) 90-100
Kubler A., Kotchoubey B., Hinterberger T., Ghanayim N., Perelmouter J., Schauer M., et al. The thought translation device: A neurophysiological approach to communication in total motor paralysis. Experimental Brain Research 124 (1999) 223-232
Kubler A., and Neumann N. Brain-computer interfaces - The key for the conscious brain locked into a paralyzed body. Progress in Brain Research 150 (2005) 513-525
LaConte S.M., Peltier S.J., and Hu X.P. Real-time fMRI using brain-state classification. Human Brain Mapping 28 (2007) 1033-1044
Laureys S., Owen A.M., and Schiff N.D. Brain function in coma, vegetative state, and related disorders. Lancet Neurology 3 (2004) 537-546
Laureys S., Pellas F., Van Eeckhout P., Ghorbel S., Schnakers C., Perrin F., et al. The locked-in syndrome: What is it like to be conscious but paralyzed and voiceless?. Progress in Brain Research 150 (2005) 495-511
Lebedev M.A., and Nicolelis M.A. Brain-machine interfaces: Past, present and future. Trends in Neurosciences 29 (2006) 536-546
Lee J.H., Marzelli M., Jolesz F.A., and Yoo S.S. Automated classification of fMRI data employing trial-based imagery tasks. Medical Image Analysis 13 (2009) 392-404
Lee J.H., Ryu J., Jolesz F.A., Cho Z.H., and Yoo S.S. Brain-machine interface via real-time fMRI: Preliminary study on thought-controlled robotic arm. Neuroscience Letters 450 (2009) 1-6
Leon-Carrion J., van Eeckhout P., and Dominguez-Morales Mdel R. The locked-in syndrome: A syndrome looking for a therapy. Brain Injury 16 (2002) 555-569
Leuthardt E.C., Miller K.J., Schalk G., Rao R.P., and Ojemann J.G. Electrocorticography-based brain computer interface - The Seattle experience. IEEE Transactions on Neural Systems and Rehabilitation Engineering 14 (2006) 194-198
Luu S., and Chau T. Decoding subjective preference from single-trial near-infrared spectroscopy signals. Journal of Neural Engineering 6 (2009) 016003
Majerus S., Gill-Thwaites H., Andrews K., and Laureys S. Behavioral evaluation of consciousness in severe brain damage. Progress in Brain Research 150 (2005) 397-413
Menon R.S., and Kim S.G. Spatial and temporal limits in cognitive neuroimaging with fMRI. Trends in Cognitive Sciences 3 (1999) 207-216
Monti, M. M., Coleman, M. R., & Owen, A. M. (2008). 'Brain Reading' with real-time fMRI: Communication via detection of brain states in the absence of motor response. 14th Annual Meeting of the Organization for Human Brain Mapping, (Vol. 1, p. 133). Melbourne: Elsevier.
Naito M., Michioka Y., Ozawa K., Ito Y., Kiguchi M., and Kanazawa T. A communication means for totally locked-in ALS patients based on changes in cerebral blood volume measured with near-infrared light. IEICE Transactions on Information and Systems E90-D (2007) 1028-1037
Nijboer F., Sellers E.W., Mellinger J., Jordan M.A., Matuz T., Furdea A., et al. A P300-based brain-computer interface for people with amyotrophic lateral sclerosis. Journal of Clinical Neurophysiology 119 (2008) 1909-1916
Ogawa S., Lee T.M., Kay A.R., and Tank D.W. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences of the United States of America 87 (1990) 9868-9872
Oldfield R.C. The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia 9 (1971) 97-113
Owen A.M., Coleman M.R., Boly M., Davis M.H., Laureys S., and Pickard J.D. Detecting awareness in the vegetative state. Science 313 (2006) 1402
Pfurtscheller G., Guger C., Muller G., Krausz G., and Neuper C. Brain oscillations control hand orthosis in a tetraplegic. Neuroscience Letters 292 (2000) 211-214
Plum F., and Posner J.B. The Diagnosis of stupor and coma: Edited book title (1966), Davis, F.A, Philadelphia, PA
Ramsey N.F., van de Heuvel M.P., Kho K.H., and Leijten F.S. Towards human BCI applications based on cognitive brain systems: An investigation of neural signals recorded from the dorsolateral prefrontal cortex. IEEE Transactions on Neural Systems and Rehabilitation Engineering 14 (2006) 214-217
Rota G., Sitaram R., Veit R., Erb M., Weiskopf N., Dogil G., et al. Self-regulation of regional cortical activity using real-time fMRI: The right inferior frontal gyrus and linguistic processing. Human Brain Mappings 30 (2009) 1605-1614
Scharnowski, F., Weiskopf, N., Mathiak, K., Zopf, R., Studer, P., Bock, S. W., et al. (2004). Self-regulation of the BOLD signal of supplementary motor area (SMA) and parahippocampal place area (PPA): fMRI-neurofeedback and its behavioural consequences. 10th Annual Meeting of the Organization for Human Brain Mapping. Budapest, Hungary.
Scherer R., Graimann B., Huggins J.E., Levine S.P., and Pfurtscheller G. Frequency component selection for an ECoG-based brain-computer interface. Biomedizinische Technik (Berlin) 48 (2003) 31-36
Schnakers C., Majerus S., Goldman S., Boly M., Van Eeckhout P., Gay S., et al. Cognitive function in the locked-in syndrome. Journal of Neurology 255 (2008) 323-330
Schwartz A.B., Cui X.T., Weber D.J., and Moran D.W. Brain-controlled interfaces: Movement restoration with neural prosthetics. Neuron 52 (2006) 205-220
Sitaram R., Caria A., Veit R., Gaber T., Rota G., Kuebler A., et al. FMRI brain-computer interface: A tool for neuroscientific research and treatment. Computational Intelligence and Neuroscience (2007) 25487
Sitaram R., Zhang H., Guan C., Thulasidas M., Hoshi Y., Ishikawa A., et al. Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface. Neuroimage 34 (2007) 1416-1427
Sorger, B., Bareither, I., Weiskopf, N., Rodriguez, E. F., Birbaumer, N., & Goebel, R. (2004). Voluntary modulation of regional brain activity to different target levels based on real-time fMRI neurofeedback. 34th Annual Meeting of the Society for Neuroscience. San Diego.
Sorger, B., Dahmen, B., Reithler, J., & Goebel, R. (2007). BOLD communication: When the brain speaks for itself. 13th Annual Meeting of the Organization for Human Brain Mapping (Vol. 36, p. 37). Chicago: Elsevier.
Talairach G., and Tournoux P. Co-planar stereotaxic atlas of the human brain (1988), Thieme, New York
Vanzetta I. Hemodynamic responses in cortex investigated with optical imaging methods. Implications for functional brain mapping. Journal of Physiology (Paris) 100 (2006) 201-211
Villringer A., and Chance B. Non-invasive optical spectroscopy and imaging of human brain function. Trends in Neurosciences 20 (1997) 435-442
Weiskopf N., Klose U., Birbaumer N., and Mathiak K. Single-shot compensation of image distortions and BOLD contrast optimization using multi-echo EPI for real-time fMRI. Neuroimage 24 (2005) 1068-1079
Weiskopf N., Mathiak K., Bock S.W., Scharnowski F., Veit R., Grodd W., et al. Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI). IEEE Transactions on Bio-Medical Engineering 51 (2004) 966-970
Weiskopf N., Scharnowski F., Veit R., Goebel R., Birbaumer N., and Mathiak K. Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). Journal of Physiology (Paris) 98 (2004) 357-373
Weiskopf N., Sitaram R., Josephs O., Veit R., Scharnowski F., Goebel R., et al. Real-time functional magnetic resonance imaging: methods and applications. Magnetic Resonance Imaging 25 (2007) 989-1003
Weiskopf N., Veit R., Erb M., Mathiak K., Grodd W., Goebel R., et al. Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): Methodology and exemplary data. Neuroimage 19 (2003) 577-586
Wijesekera L.C., and Leigh P.N. Amyotrophic lateral sclerosis. Orphanet Journal of Rare Diseases 4 (2009) 3
Yoo S.S., Fairneny T., Chen N.K., Choo S.E., Panych L.P., and Park H. Brain-computer interface using fMRI: Spatial navigation by thoughts. Neuroreport 15 (2004) 1591-1595