A Paradigm to Enhance Motor Imagery Using Rubber Hand Illusion Induced by Visuo-Tactile Stimulus

Enhancing motor imagery (MI) results in amplified event-related desynchronization (ERD) and is important for MI-based rehabilitation and brain–computer interface (BCI) applications. Many attempts to enhance the MI by providing a visual guidance have been reported. We believe that the rubber hand illusion (RHI), which induces body ownership over an external object, can provide better guidance to enhance MI; thus, an RHI-based paradigm with motorized moving rubber hand was proposed. To validate the proposed MI enhancing paradigm, we conducted an experimental comparison among paradigms with 20 healthy subjects. The peak amplitude and arrival times of ERD were compared at contralateral and ipsilateral electroencephalogram channels. We found significantly amplified ERD caused by the proposed paradigm, which is similar to the ERD caused by motor execution. In addition, the arrival time suggests that the proposed paradigm is applicable for BCI. In conclusion, the proposed paradigm can significantly enhance the MI with better characteristics for use with BCI.

[1]  H. Ehrsson,et al.  Moving a Rubber Hand that Feels Like Your Own: A Dissociation of Ownership and Agency , 2012, Front. Hum. Neurosci..

[2]  F. L. D. Silva,et al.  Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.

[3]  Robert Teasell,et al.  Plasticity and Reorganization of the Brain Post Stroke , 2005, Topics in stroke rehabilitation.

[4]  G. Pfurtscheller,et al.  EEG-based discrimination between imagination of right and left hand movement. , 1997, Electroencephalography and clinical neurophysiology.

[5]  Ning Jiang,et al.  Peripheral Electrical Stimulation Triggered by Self-Paced Detection of Motor Intention Enhances Motor Evoked Potentials , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[6]  R. Lane,et al.  Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration , 2009, Neuroscience & Biobehavioral Reviews.

[7]  G. Pfurtscheller,et al.  Synchronization of intrinsic 0.1‐Hz blood‐oxygen‐level‐dependent oscillations in amygdala and prefrontal cortex in subjects with increased state anxiety , 2018, The European journal of neuroscience.

[8]  J Strackee,et al.  Hemodynamic fluctuations and baroreflex sensitivity in humans: a beat-to-beat model. , 1987, The American journal of physiology.

[9]  Axel Cleeremans,et al.  New frontiers in the rubber hand experiment: when a robotic hand becomes one’s own , 2014, Behavior Research Methods.

[10]  M. Hallett,et al.  Prediction of human voluntary movement before it occurs , 2011, Clinical Neurophysiology.

[11]  Andrej Stancák,et al.  Cortical oscillatory changes occurring during somatosensory and thermal stimulation. , 2006, Progress in brain research.

[12]  Henk J. Stam,et al.  Randomized Controlled Trial Motor Recovery and Cortical Reorganization After Mirror Therapy in Chronic Stroke Patients : A Phase II , 2011 .

[13]  J. Wolpaw,et al.  Activity-dependent spinal cord plasticity in health and disease. , 2001, Annual review of neuroscience.

[14]  T. Jones,et al.  Motor Skills Training Enhances Lesion-Induced Structural Plasticity in the Motor Cortex of Adult Rats , 1999, The Journal of Neuroscience.

[15]  Jin-Chern Chiou,et al.  A Comparison of Independent Event-Related Desynchronization Responses in Motor-Related Brain Areas to Movement Execution, Movement Imagery, and Movement Observation , 2016, PloS one.

[16]  Bettina Forster,et al.  An ERP Investigation on Visuotactile Interactions in Peripersonal and Extrapersonal Space: Evidence for the Spatial Rule , 2009, Journal of Cognitive Neuroscience.

[17]  J. Ushiba,et al.  Ipsilateral EEG mu rhythm reflects the excitability of uncrossed pathways projecting to shoulder muscles , 2017, Journal of NeuroEngineering and Rehabilitation.

[18]  Theresa A. Jones,et al.  Experience-Dependent Structural Plasticity in Cortex Heterotopic to Focal Sensorimotor Cortical Damage , 2000, Experimental Neurology.

[19]  Zoran Nenadic,et al.  Brain-controlled functional electrical stimulation therapy for gait rehabilitation after stroke: a safety study , 2015, Journal of NeuroEngineering and Rehabilitation.

[20]  Jonghyun Kim,et al.  A Novel Movement Intention Detection Method for Neurorehabilitation Brain-Computer Interface System , 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[21]  J. Baron,et al.  Motor Imagery: A Backdoor to the Motor System After Stroke? , 2006, Stroke.

[22]  Zhizeng Luo,et al.  Improving motor imagery practice with synchronous action observation in stroke patients , 2016, Topics in stroke rehabilitation.

[23]  M. Jüptner,et al.  Arm Training Induced Brain Plasticity in Stroke Studied with Serial Positron Emission Tomography , 2001, NeuroImage.

[24]  Jeremy D. Thorne,et al.  Embodied neurofeedback with an anthropomorphic robotic hand , 2016, Scientific Reports.

[25]  Antonio Frisoli,et al.  Hand and Arm Ownership Illusion through Virtual Reality Physical Interaction and Vibrotactile Stimulations , 2010, EuroHaptics.

[26]  G. Pfurtscheller,et al.  How many people are able to operate an EEG-based brain-computer interface (BCI)? , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[27]  Clemens Brunner,et al.  Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks , 2006, NeuroImage.

[28]  Tele Tan,et al.  3D visualization of movements can amplify motor cortex activation during subsequent motor imagery , 2015, Front. Hum. Neurosci..

[29]  Jonathan D. Cohen,et al.  Rubber hands ‘feel’ touch that eyes see , 1998, Nature.

[30]  G. Pfurtscheller,et al.  ERD/ERS patterns reflecting sensorimotor activation and deactivation. , 2006, Progress in brain research.

[31]  S. Small,et al.  The mirror neuron system and treatment of stroke. , 2012, Developmental psychobiology.

[32]  Olaf Blanke,et al.  Virtual reality improves embodiment and neuropathic pain caused by spinal cord injury , 2017, Neurology.

[33]  Jonghyun Kim,et al.  Motor imagery enhancement paradigm using moving rubber hand illusion system , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[34]  Josef Parvizi,et al.  Resting oscillations and cross-frequency coupling in the human posteromedial cortex , 2012, NeuroImage.

[35]  K.-R. Muller,et al.  The Berlin brain-computer interface: EEG-based communication without subject training , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[36]  M. Slater,et al.  Multisensory Stimulation Can Induce an Illusion of Larger Belly Size in Immersive Virtual Reality , 2011, PloS one.

[37]  Ruimin Wang,et al.  Classification of Four-Class Motor Imagery Employing Single-Channel Electroencephalography , 2014, PloS one.

[38]  G. Pfurtscheller,et al.  Coupling between Intrinsic Prefrontal HbO2 and Central EEG Beta Power Oscillations in the Resting Brain , 2012, PloS one.

[39]  F. L. D. Silva,et al.  Event-Related Desynchronization , 1999 .

[40]  P. Haggard,et al.  Having a body versus moving your body: How agency structures body-ownership , 2006, Consciousness and Cognition.

[41]  H. C. Dijkerman,et al.  A Virtual Reality Full Body Illusion Improves Body Image Disturbance in Anorexia Nervosa , 2016, PloS one.

[42]  C. Winstein,et al.  The Mirror Neuron System: A Neural Substrate for Methods in Stroke Rehabilitation , 2010, Neurorehabilitation and neural repair.

[43]  Nathan Evans,et al.  Shared electrophysiology mechanisms of body ownership and motor imagery , 2013, NeuroImage.

[44]  Kup-Sze Choi,et al.  Improving the discrimination of hand motor imagery via virtual reality based visual guidance , 2016, Comput. Methods Programs Biomed..

[45]  J. Wolpaw,et al.  Brain–computer interfaces in neurological rehabilitation , 2008, The Lancet Neurology.

[46]  G. Pfurtscheller,et al.  Motor imagery activates primary sensorimotor area in humans , 1997, Neuroscience Letters.

[47]  C. Richards,et al.  Potential role of mental practice using motor imagery in neurologic rehabilitation. , 2001, Archives of physical medicine and rehabilitation.

[48]  Janis J. Daly,et al.  Construction of Efficacious Gait and Upper Limb Functional Interventions Based on Brain Plasticity Evidence and Model-Based Measures For Stroke Patients , 2007, TheScientificWorldJournal.

[49]  S. Small,et al.  Action observation has a positive impact on rehabilitation of motor deficits after stroke , 2007, NeuroImage.

[50]  Cecilia Heyes,et al.  Visuotactile learning and body representation: An erp study with rubber hands and rubber objects , 2008 .

[51]  E. Noé,et al.  Body schema plasticity after stroke: Subjective and neurophysiological correlates of the rubber hand illusion , 2017, Neuropsychologia.

[52]  Christa Neuper,et al.  Autocalibration and Recurrent Adaptation: Towards a Plug and Play Online ERD-BCI , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[53]  J. Palva,et al.  Infraslow oscillations modulate excitability and interictal epileptic activity in the human cortex during sleep. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[54]  R. Dickstein,et al.  Motor Imagery in Physical Therapist Practice , 2007, Physical Therapy.

[55]  N. Birbaumer,et al.  ERD-Based Online Brain–Machine Interfaces (BMI) in the Context of Neurorehabilitation: Optimizing BMI Learning and Performance , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.