Recording and Decoding for Neural Prostheses

This paper reviews technologies and signal processing algorithms for decoding peripheral nerve and electrocorticogram signals to interpret human intent and control prosthetic arms. The review includes a discussion of human motor system physiology and physiological signals that can be used to decode motor intent, electrode technology for acquiring neural data, and signal processing methods including decoders based on Kalman filtering and least-squares regressors. Representative results from human experiments demonstrate the progress that has been made in neural decoding and its potential for developing neuroprosthetic arms that act and feel like natural arms.

[1]  Rahman Davoodi,et al.  Model-Based Development of Neural Prostheses for Movement , 2007, IEEE Transactions on Biomedical Engineering.

[2]  Laurent Bougrain,et al.  Decoding Finger Flexion from Band-Specific ECoG Signals in Humans , 2012, Front. Neurosci..

[3]  E. Evarts,et al.  Relation of pyramidal tract activity to force exerted during voluntary movement. , 1968, Journal of neurophysiology.

[4]  Maarten J. IJzerman,et al.  Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics , 2004, Spinal Cord.

[5]  D. Durand,et al.  Chronic Response of the Rat Sciatic Nerve to the Flat Interface Nerve Electrode , 2003, Annals of Biomedical Engineering.

[6]  Stephen C. Jacobsen,et al.  Microfabricated cylindrical multielectrodes for neural stimulation , 2006, IEEE Transactions on Biomedical Engineering.

[7]  M. Inase,et al.  Neuronal activity in the primate premotor, supplementary, and precentral motor cortex during visually guided and internally determined sequential movements. , 1991, Journal of neurophysiology.

[8]  Kevin Warwick,et al.  The application of implant technology for cybernetic systems. , 2003, Archives of neurology.

[9]  Erkki Oja,et al.  Independent Component Analysis , 2001 .

[10]  Stuart D. Harshbarger,et al.  Revolutionizing Prosthetics : Systems Engineering Challenges and Opportunities , 2011 .

[11]  K. Horch,et al.  A silicon-based, three-dimensional neural interface: manufacturing processes for an intracortical electrode array , 1991, IEEE Transactions on Biomedical Engineering.

[12]  S. Micera,et al.  Overview of the implant of intraneural multielectrodes in human for controlling a 5-fingered hand prosthesis, delivering sensorial feedback and producing rehabilitative neuroplasticity , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[13]  T. Sinkjaer,et al.  Long-term biocompatibility of implanted polymer-based intrafascicular electrodes. , 2002, Journal of biomedical materials research.

[14]  D.M. Durand,et al.  Localization and Recovery of Peripheral Neural Sources With Beamforming Algorithms , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[15]  Luca Citi,et al.  Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces , 2011, Journal of NeuroEngineering and Rehabilitation.

[16]  B. Hjorth.  An on-line transformation of EEG scalp potentials into orthogonal source derivations. , 1975, Electroencephalography and clinical neurophysiology.

[17]  Jiping He,et al.  Selection and parameterization of cortical neurons for neuroprosthetic control , 2006, Journal of neural engineering.

[18]  Shaomin Zhang,et al.  Long-term decoding stability of local field potentials from silicon arrays in primate motor cortex during a 2D center out task , 2014, Journal of neural engineering.

[19]  K. Englehart,et al.  Classification of the myoelectric signal using time-frequency based representations. , 1999, Medical engineering & physics.

[20]  P. Rossini,et al.  Double nerve intraneural interface implant on a human amputee for robotic hand control , 2010, Clinical Neurophysiology.

[21]  K. Horch,et al.  Object Discrimination With an Artificial Hand Using Electrical Stimulation of Peripheral Tactile and Proprioceptive Pathways With Intrafascicular Electrodes , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[22]  Valérie Ventura,et al.  To sort or not to sort: the impact of spike-sorting on neural decoding performance , 2014, Journal of neural engineering.

[23]  Jose M. Carmena,et al.  Designing Dynamical Properties of Brain–Machine Interfaces to Optimize Task-Specific Performance , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[24]  Erik J. Scheme,et al.  Confidence-Based Rejection for Improved Pattern Recognition Myoelectric Control , 2013, IEEE Transactions on Biomedical Engineering.

[25]  A P Georgopoulos,et al.  On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[26]  Justin A. Blanco,et al.  Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics. , 2010, Nature materials.

[27]  R.P.N. Rao,et al.  Finger Movement Classification for an Electrocorticographic BCI , 2007, 2007 3rd International IEEE/EMBS Conference on Neural Engineering.

[28]  D. M. Durand,et al.  Bayesian Spatial Filters for Source Signal Extraction: A Study in the Peripheral Nerve , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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

[30]  Rajesh P. N. Rao,et al.  Electrocorticography-based brain computer Interface-the seattle experience , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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

[32]  Craig T. Nordhausen,et al.  Optimizing recording capabilities of the Utah Intracortical Electrode Array , 1994, Brain Research.

[33]  S. Micera,et al.  On the control of a robot hand by extracting neural signals from the PNS: Preliminary results from a human implantation , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[34]  T. Stieglitz,et al.  A transverse intrafascicular multichannel electrode (TIME) to interface with the peripheral nerve. , 2010, Biosensors & bioelectronics.

[35]  A B Schwartz,et al.  Motor cortical representation of speed and direction during reaching. , 1999, Journal of neurophysiology.

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

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

[38]  John P. Cunningham,et al.  A High-Performance Neural Prosthesis Enabled by Control Algorithm Design , 2012, Nature Neuroscience.

[39]  J. Wolpaw,et al.  Decoding two-dimensional movement trajectories using electrocorticographic signals in humans , 2007, Journal of neural engineering.

[40]  P R Kennedy,et al.  Direct control of a computer from the human central nervous system. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[41]  Jose M. Carmena,et al.  Continuous Closed-Loop Decoder Adaptation with a Recursive Maximum Likelihood Algorithm Allows for Rapid Performance Acquisition in Brain-Machine Interfaces , 2014, Neural Computation.

[42]  A. Schwartz,et al.  Recording from the same neurons chronically in motor cortex. , 2012, Journal of neurophysiology.

[43]  Parag G. Patil,et al.  Ensemble Recordings Of Human Subcortical Neurons as a Source Of Motor Control Signals For a Brain-Machine Interface , 2004, Neurosurgery.

[44]  Linda Resnik,et al.  The DEKA Arm: Its features, functionality, and evolution during the Veterans Affairs Study to optimize the DEKA Arm , 2014, Prosthetics and orthotics international.

[45]  Michael J. Black,et al.  A quantitative comparison of linear and non-linear models of motor cortical activity for the encoding and decoding of arm motions , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..

[46]  M. Swiontkowski.  Targeted Muscle Reinnervation for Real-time Myoelectric Control of Multifunction Artificial Arms , 2010 .

[47]  Wei Wang,et al.  Motor-related brain activity during action observation: a neural substrate for electrocorticographic brain-computer interfaces after spinal cord injury , 2014, Front. Integr. Neurosci..

[48]  José Carlos Príncipe,et al.  A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing , 2009, Neural Computation.

[49]  Michael L Boninger,et al.  Functional priorities, assistive technology, and brain-computer interfaces after spinal cord injury. , 2013, Journal of rehabilitation research and development.

[50]  E. Todorov.  Direct cortical control of muscle activation in voluntary arm movements: a model , 2000, Nature Neuroscience.

[51]  David Sussillo,et al.  A recurrent neural network for closed-loop intracortical brain–machine interface decoders , 2012, Journal of neural engineering.

[52]  R. Andersen,et al.  Cortical Local Field Potential Encodes Movement Intentions in the Posterior Parietal Cortex , 2005, Neuron.

[53]  K. Hagberg,et al.  A novel osseointegrated percutaneous prosthetic system for the treatment of patients with transfemoral amputation: A prospective study of 51 patients. , 2014, The bone & joint journal.

[54]  M S Lewicki,et al.  A review of methods for spike sorting: the detection and classification of neural action potentials. , 1998, Network.

[55]  John P. Donoghue,et al.  Decoding 3-D Reach and Grasp Kinematics From High-Frequency Local Field Potentials in Primate Primary Motor Cortex , 2010, IEEE Transactions on Biomedical Engineering.

[56]  David T. Bundy,et al.  Microscale recording from human motor cortex: implications for minimally invasive electrocorticographic brain-computer interfaces. , 2009, Neurosurgical focus.

[57]  K. Englehart,et al.  Resolving the Limb Position Effect in Myoelectric Pattern Recognition , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[58]  Rabab K Ward,et al.  A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals , 2007, Journal of neural engineering.

[59]  R. Knight,et al.  The functional role of cross-frequency coupling , 2010, Trends in Cognitive Sciences.

[60]  K D Wise,et al.  An evaluation of photoengraved microelectrodes for extracellular single-unit recording. , 1973, IEEE transactions on bio-medical engineering.

[61]  Linda Resnik,et al.  User and clinician perspectives on DEKA arm: results of VA study to optimize DEKA arm. , 2014, Journal of rehabilitation research and development.

[62]  Bradley Greger,et al.  Decoding spoken words using local field potentials recorded from the cortical surface , 2010, Journal of neural engineering.

[63]  Joseph E. O’Doherty,et al.  Unscented Kalman Filter for Brain-Machine Interfaces , 2009, PloS one.

[64]  John P. Cunningham,et al.  Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models , 2007, ICONIP.

[65]  Kip A Ludwig,et al.  Using a common average reference to improve cortical neuron recordings from microelectrode arrays. , 2009, Journal of neurophysiology.

[66]  Rajesh P. N. Rao,et al.  Cortical activity during motor execution, motor imagery, and imagery-based online feedback , 2010, Proceedings of the National Academy of Sciences.

[67]  Steven M Chase,et al.  Control of a brain–computer interface without spike sorting , 2009, Journal of neural engineering.

[68]  B J Fisch,et al.  The weighted average reference montage. , 1991, Electroencephalography and clinical neurophysiology.

[69]  Reid R. Harrison,et al.  Recording sensory and motor information from peripheral nerves with Utah Slanted Electrode Arrays , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[70]  Daniela Calvetti,et al.  Hierarchical beamformer and cross-talk reduction in electroneurography , 2011, Journal of neural engineering.

[71]  Victor Krauthamer,et al.  Rapid evaluation of the durability of cortical neural implants using accelerated aging with reactive oxygen species , 2015, Journal of neural engineering.

[72]  Yasuharu Koike,et al.  Prediction of Three-Dimensional Arm Trajectories Based on ECoG Signals Recorded from Human Sensorimotor Cortex , 2013, PloS one.

[73]  A. Aertsen,et al.  The role of ECoG magnitude and phase in decoding position, velocity, and acceleration during continuous motor behavior , 2013, Front. Neurosci..

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

[75]  J. Isaacson,et al.  Odor Representations in Olfactory Cortex: “Sparse” Coding, Global Inhibition, and Oscillations , 2009, Neuron.

[76]  D J Weber,et al.  Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[77]  Qiang Ji,et al.  Decoding onset and direction of movements using Electrocorticographic (ECoG) signals in humans , 2012, Front. Neuroeng..

[78]  Luca Citi,et al.  Decoding Information From Neural Signals Recorded Using Intraneural Electrodes: Toward the Development of a Neurocontrolled Hand Prosthesis , 2010, Proceedings of the IEEE.

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

[80]  Spencer Kellis,et al.  Neural decoding using a nonlinear generative model for brain-computer interface , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[81]  Eun Jung Hwang,et al.  The utility of multichannel local field potentials for brain–machine interfaces , 2013, Journal of neural engineering.

[82]  Ahmed H. Tewfik,et al.  High Accuracy Decoding of Movement Target Direction in Non-Human Primates Based on Common Spatial Patterns of Local Field Potentials , 2010, PloS one.

[83]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .

[84]  E. Fetz,et al.  Postspike facilitation of forelimb muscle activity by primate corticomotoneuronal cells. , 1980, Journal of neurophysiology.

[85]  Eran Stark,et al.  Predicting Movement from Multiunit Activity , 2007, The Journal of Neuroscience.

[86]  R. Triolo,et al.  Intraoperative Demonstration of Selective Stimulation of the Common Human Femoral Nerve with a FINE , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[87]  Jon A. Mukand,et al.  Neuronal ensemble control of prosthetic devices by a human with tetraplegia , 2006, Nature.

[88]  D.A. Heldman,et al.  Local field potential spectral tuning in motor cortex during reaching , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[89]  Michael J. Black,et al.  Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array , 2011 .

[90]  Thomas Sinkjær,et al.  Real Time Foot Drop Correction using Machine Learning and Natural Sensors , 2002, Neuromodulation : journal of the International Neuromodulation Society.

[91]  K. Wise,et al.  A three-dimensional microelectrode array for chronic neural recording , 1994, IEEE Transactions on Biomedical Engineering.

[92]  J. Kalaska,et al.  A comparison of movement direction-related versus load direction- related activity in primate motor cortex, using a two-dimensional reaching task , 1989, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[93]  K. Horch,et al.  Effects of short-term training on sensory and motor function in severed nerves of long-term human amputees. , 2005, Journal of neurophysiology.

[94]  Partha P. Mitra,et al.  Chronux: A platform for analyzing neural signals , 2010, Journal of Neuroscience Methods.

[95]  Michael J. Black,et al.  Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia , 2008, Journal of neural engineering.

[96]  Eun Jung Hwang,et al.  Spiking and LFP activity in PRR during symbolically instructed reaches. , 2012, Journal of neurophysiology.

[97]  N. Thakor,et al.  Electrocorticographic amplitude predicts finger positions during slow grasping motions of the hand , 2010, Journal of neural engineering.

[98]  K. Horch,et al.  Residual function in peripheral nerve stumps of amputees: implications for neural control of artificial limbs. , 2004, The Journal of hand surgery.

[99]  K. Englehart,et al.  Electromyogram Whitening for Improved Classification Accuracy in Upper Limb Prosthesis Control , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[100]  Bradley Greger,et al.  Human neocortical electrical activity recorded on nonpenetrating microwire arrays: applicability for neuroprostheses. , 2009, Neurosurgical focus.

[101]  Vikash Gilja,et al.  Long-term Stability of Neural Prosthetic Control Signals from Silicon Cortical Arrays in Rhesus Macaque Motor Cortex , 2010 .

[102]  Spencer Kellis,et al.  Decoding hand trajectories from micro-electrocorticography in human patients , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[103]  C. Mehring,et al.  Encoding of Movement Direction in Different Frequency Ranges of Motor Cortical Local Field Potentials , 2005, The Journal of Neuroscience.

[104]  C. Mehring,et al.  Inference of hand movements from local field potentials in monkey motor cortex , 2003, Nature Neuroscience.

[105]  C. Koch,et al.  The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes , 2012, Nature Reviews Neuroscience.

[106]  K. Anderson.  Targeting recovery: priorities of the spinal cord-injured population. , 2004, Journal of neurotrauma.

[107]  Eun Jung Hwang,et al.  Brain Control of Movement Execution Onset Using Local Field Potentials in Posterior Parietal Cortex , 2009, The Journal of Neuroscience.

[108]  D T Hutchinson,et al.  Continuous Detection and Decoding of Dexterous Finger Flexions With Implantable MyoElectric Sensors , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[109]  Robert Frysch,et al.  Hidden Markov model and support vector machine based decoding of finger movements using electrocorticography , 2013, Journal of neural engineering.

[110]  Richard A Andersen,et al.  Decoding Trajectories from Posterior Parietal Cortex Ensembles , 2008, The Journal of Neuroscience.

[111]  Vikash Gilja,et al.  Assessment of brain–machine interfaces from the perspective of people with paralysis , 2015, Journal of neural engineering.

[112]  Erik J. Scheme,et al.  Validation of a Selective Ensemble-Based Classification Scheme for Myoelectric Control Using a Three-Dimensional Fitts' Law Test , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[113]  Bruce C. Wheeler,et al.  EMG feature evaluation for movement control of upper extremity prostheses , 1995 .

[114]  R. Andersen,et al.  Selecting the signals for a brain–machine interface , 2004, Current Opinion in Neurobiology.

[115]  M. Keith,et al.  A neural interface provides long-term stable natural touch perception , 2014, Science Translational Medicine.

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

[117]  Robert D. Lipschutz,et al.  The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee , 2004, Prosthetics and orthotics international.

[118]  Robert D Flint,et al.  Long term, stable brain machine interface performance using local field potentials and multiunit spikes , 2013, Journal of neural engineering.

[119]  Kelvin So,et al.  Subject-specific modulation of local field potential spectral power during brain–machine interface control in primates , 2014, Journal of neural engineering.

[120]  G.S. Dhillon,et al.  Direct neural sensory feedback and control of a prosthetic arm , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[121]  S Micera,et al.  Control of Hand Prostheses Using Peripheral Information , 2010, IEEE Reviews in Biomedical Engineering.

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

[123]  Lee E. Miller,et al.  Interfacing the Somatosensory System to Restore Touch and Proprioception: Essential Considerations , 2012, Journal of motor behavior.

[124]  R. J. Vogelstein,et al.  Restoring the sense of touch with a prosthetic hand through a brain interface , 2013, Proceedings of the National Academy of Sciences.

[125]  T. Hasbroucq,et al.  Spatial enhancement of EEG traces by surface Laplacian estimation: comparison between local and global methods , 2005, Clinical Neurophysiology.

[126]  A. Schulze-Bonhage,et al.  First long term in vivo study on subdurally implanted Micro-ECoG electrodes, manufactured with a novel laser technology , 2011, Biomedical microdevices.

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

[128]  S. Wise,et al.  The premotor cortex of the monkey , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[129]  Wei Wu,et al.  Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter , 2006, Neural Computation.

[130]  Luca Citi,et al.  Restoring Natural Sensory Feedback in Real-Time Bidirectional Hand Prostheses , 2014, Science Translational Medicine.

[131]  David J. Warren,et al.  Using multiple high-count electrode arrays in human median and ulnar nerves to restore sensorimotor function after previous transradial amputation of the hand , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[132]  Alain Rakotomamonjy,et al.  Decoding Finger Movements from ECoG Signals Using Switching Linear Models , 2011, Front. Neurosci..

[133]  Spencer Kellis,et al.  Platinum microwire for subdural electrocorticography over human neocortex: Millimeter-scale spatiotemporal dynamics , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[134]  T. Kuiken,et al.  Control of a six degree of freedom prosthetic arm after targeted muscle reinnervation surgery. , 2008, Archives of physical medicine and rehabilitation.

[135]  Max Ortiz-Catalan,et al.  On the viability of implantable electrodes for the natural control of artificial limbs: Review and discussion , 2012, Biomedical engineering online.

[136]  Arjun K. Bansal,et al.  Relationships among low-frequency local field potentials, spiking activity, and three-dimensional reach and grasp kinematics in primary motor and ventral premotor cortices. , 2011, Journal of neurophysiology.

[137]  T. Bullock,et al.  EEG coherence has structure in the millimeter domain: subdural and hippocampal recordings from epileptic patients. , 1995, Electroencephalography and clinical neurophysiology.

[138]  Byron M. Yu,et al.  A high-performance brain–computer interface , 2006, Nature.

[139]  Todd A. Kuiken,et al.  Improving Myoelectric Pattern Recognition Robustness to Electrode Shift by Changing Interelectrode Distance and Electrode Configuration , 2012, IEEE Transactions on Biomedical Engineering.

[140]  R. Stein,et al.  Selective stimulation of cat sciatic nerve using an array of varying-length microelectrodes. , 2001, Journal of neurophysiology.

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

[142]  K. Horch,et al.  An intrafascicular electrode for recording of action potentials in peripheral nerves , 2006, Annals of Biomedical Engineering.

[143]  Richard T. Johnson,et al.  Development of the Utah Artificial Arm , 1982, IEEE Transactions on Biomedical Engineering.

[144]  M. Keith,et al.  Stimulation Stability and Selectivity of Chronically Implanted Multicontact Nerve Cuff Electrodes in the Human Upper Extremity , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[145]  F. Offner,et al.  The EEG as potential mapping: the value of the average monopolar reference. , 1950, Electroencephalography and clinical neurophysiology.

[146]  Arjun K. Bansal,et al.  Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials. , 2012, Journal of neurophysiology.

[147]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.

[148]  Sampsa Vanhatalo,et al.  Fine spatiotemporal structure of phase in human intracranial EEG , 2006, Clinical Neurophysiology.

[149]  M A Lebedev,et al.  A comparison of optimal MIMO linear and nonlinear models for brain–machine interfaces , 2006, Journal of neural engineering.

[150]  J. Donoghue,et al.  Neural discharge and local field potential oscillations in primate motor cortex during voluntary movements. , 1998, Journal of neurophysiology.

[151]  Rajesh P. N. Rao,et al.  Generalized Features for Electrocorticographic BCIs , 2008, IEEE Transactions on Biomedical Engineering.

[152]  N. Ramsey,et al.  Give me a sign: decoding four complex hand gestures based on high-density ECoG , 2014, Brain Structure and Function.