Simultaneous Neural Control of Simple Reaching and Grasping With the Modular Prosthetic Limb Using Intracranial EEG

Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the subject made reaching and grasping movements to identify task-selective electrodes. Independent, online control of reaching and grasping was then achieved using high gamma activity from a small subset of electrodes with a model trained on short blocks of reaching and grasping with no further adaptation. Classification accuracy did not decline (p <; 0.05, one-way ANOVA) over three blocks of testing in either subject. Mean classification accuracy during independently executed overt reach and grasp movements for (Subject 1, Subject 2) were (0.85, 0.81) and (0.80, 0.96), respectively, and during simultaneous execution they were (0.83, 0.88) and (0.58, 0.88), respectively. Our models leveraged knowledge of the subject's individual functional neuroanatomy for reaching and grasping movements, allowing rapid acquisition of control in a time-sensitive clinical setting. We demonstrate the potential feasibility of verifying functionally meaningful iEEG-based control of the MPL prior to chronic implantation, during which additional capabilities of the MPL might be exploited with further training.

[1]  Matthew P. Para,et al.  Control System Architecture for the Modular Prosthetic Limb , 2011 .

[2]  Gerwin Schalk,et al.  Electrocorticographic (ECoG) correlates of human arm movements , 2012, Experimental Brain Research.

[3]  D J McFarland,et al.  An EEG-based brain-computer interface for cursor control. , 1991, Electroencephalography and clinical neurophysiology.

[4]  Gerwin Schalk,et al.  A brain–computer interface using electrocorticographic signals in humans , 2004, Journal of neural engineering.

[5]  X. Zeng,et al.  Geometric strategies for neuroanatomic analysis from MRI , 2004, NeuroImage.

[6]  Jeremy R. Manning,et al.  Broadband Shifts in Local Field Potential Power Spectra Are Correlated with Single-Neuron Spiking in Humans , 2009, The Journal of Neuroscience.

[7]  H. Yokoi,et al.  Electrocorticographic control of a prosthetic arm in paralyzed patients , 2012, Annals of neurology.

[8]  Stuart D. Harshbarger,et al.  An Overview of the Developmental Process for the Modular Prosthetic Limb , 2011 .

[9]  Heidi E Kirsch,et al.  Single-Trial Speech Suppression of Auditory Cortex Activity in Humans , 2010, The Journal of Neuroscience.

[10]  D. Moran,et al.  Cortical Adaptation to a Chronic Micro-Electrocorticographic Brain Computer Interface , 2013, The Journal of Neuroscience.

[11]  Justin C. Williams,et al.  A Micro-Electrocorticography Platform and Deployment Strategies for Chronic BCI Applications , 2011, Clinical EEG and neuroscience.

[12]  Naotaka Fujii,et al.  Long-Term Asynchronous Decoding of Arm Motion Using Electrocorticographic Signals in Monkeys , 2009, Front. Neuroeng..

[13]  Nicolas Y. Masse,et al.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm , 2012, Nature.

[14]  Josef Parvizi,et al.  Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas , 2013, Journal of neural engineering.

[15]  M. Laubach,et al.  Redundancy and Synergy of Neuronal Ensembles in Motor Cortex , 2005, The Journal of Neuroscience.

[16]  Andreas Schulze-Bonhage,et al.  Decoding natural grasp types from human ECoG , 2012, NeuroImage.

[17]  Brian Litt,et al.  Flexible, Foldable, Actively Multiplexed, High-Density Electrode Array for Mapping Brain Activity in vivo , 2011, Nature Neuroscience.

[18]  W. Freeman,et al.  Spatial spectra of scalp EEG and EMG from awake humans , 2003, Clinical Neurophysiology.

[19]  R. Lesser,et al.  Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis. II. Event-related synchronization in the gamma band. , 1998, Brain : a journal of neurology.

[20]  H. Yokoi,et al.  Real-time control of a prosthetic hand using human electrocorticography signals. , 2011, Journal of neurosurgery.

[21]  L. Miller,et al.  Optimal spacing of surface electrode arrays for brain–machine interface applications , 2010, Journal of neural engineering.

[22]  J. Wolpaw,et al.  Decoding flexion of individual fingers using electrocorticographic signals in humans , 2009, Journal of neural engineering.

[23]  J R Wolpaw,et al.  Spatial filter selection for EEG-based communication. , 1997, Electroencephalography and clinical neurophysiology.

[24]  Andreas Schulze-Bonhage,et al.  Grasp Detection from Human ECoG during Natural Reach-to-Grasp Movements , 2013, PloS one.

[25]  R. Irizarry,et al.  Electrocorticographic gamma activity during word production in spoken and sign language , 2001, Neurology.

[26]  Kapil D. Katyal,et al.  Revolutionizing Prosthetics software technology , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[27]  E. Halgren,et al.  High-frequency neural activity and human cognition: Past, present and possible future of intracranial EEG research , 2012, Progress in Neurobiology.

[28]  J. A. Wilson,et al.  Two-dimensional movement control using electrocorticographic signals in humans , 2008, Journal of neural engineering.

[29]  G. Schalk,et al.  The emerging world of motor neuroprosthetics: a neurosurgical perspective. , 2006, Neurosurgery.

[30]  W. Newsome,et al.  Local Field Potential in Cortical Area MT: Stimulus Tuning and Behavioral Correlations , 2006, The Journal of Neuroscience.

[31]  Andreas Schulze-Bonhage,et al.  Signal quality of simultaneously recorded invasive and non-invasive EEG , 2009, NeuroImage.

[32]  S. Acharya,et al.  Toward Electrocorticographic Control of a Dexterous Upper Limb Prosthesis: Building Brain-Machine Interfaces , 2012, IEEE Pulse.

[33]  Flavia Filimon.  Human Cortical Control of Hand Movements: Parietofrontal Networks for Reaching, Grasping, and Pointing , 2010, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[34]  Robin C. Ashmore,et al.  An Electrocorticographic Brain Interface in an Individual with Tetraplegia , 2013, PloS one.

[35]  E. F. Chang,et al.  Sub-centimeter language organization in the human temporal lobe , 2011, Brain and Language.

[36]  Y Hochberg,et al.  Mathematical formulae for the prediction of the residual beta cell function during the first two years of disease in children and adolescents with insulin-dependent diabetes mellitus. , 1995, Medical hypotheses.

[37]  Michael L. Boninger,et al.  Toward Synergy-Based Brain-Machine Interfaces , 2011, IEEE Transactions on Information Technology in Biomedicine.

[38]  W. A. Sarnacki,et al.  Electroencephalographic (EEG) control of three-dimensional movement , 2010, Journal of neural engineering.

[39]  E. Niebur,et al.  Neural Correlates of High-Gamma Oscillations (60–200 Hz) in Macaque Local Field Potentials and Their Potential Implications in Electrocorticography , 2008, The Journal of Neuroscience.

[40]  A. Schwartz,et al.  High-performance neuroprosthetic control by an individual with tetraplegia , 2013, The Lancet.

[41]  Rajesh P. N. Rao,et al.  Spectral Changes in Cortical Surface Potentials during Motor Movement , 2007, The Journal of Neuroscience.

[42]  Ernst Niebur,et al.  High-frequency gamma activity (80–150Hz) is increased in human cortex during selective attention , 2008, Clinical Neurophysiology.

[43]  J. Maunsell,et al.  Different Origins of Gamma Rhythm and High-Gamma Activity in Macaque Visual Cortex , 2011, PLoS biology.

[44]  G. Rizzolatti,et al.  The organization of the cortical motor system: new concepts. , 1998, Electroencephalography and clinical neurophysiology.