Decoding grasp force profile from electrocorticography signals in non-human primate sensorimotor cortex

The relatively low invasiveness of electrocorticography (ECoG) has made it a promising candidate for the development of practical, high-performance neural prosthetics. Recent ECoG-based studies have shown success in decoding hand and finger movements and muscle activity in reaching and grasping tasks. However, decoding of force profiles is still lacking. Here, we demonstrate that lateral grasp force profile can be decoded using a sparse linear regression from 15 and 16 channel ECoG signals recorded from sensorimotor cortex in two non-human primates. The best average correlation coefficients of prediction after 10-fold cross validation were 0.82±0.09 and 0.79±0.15 for our monkeys A and B, respectively. These results show that grasp force profile was successfully decoded from ECoG signals in reaching and grasping tasks and may potentially contribute to the development of more natural control methods for grasping in neural prosthetics.

[1]  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.

[2]  Jerald D. Kralik,et al.  Real-time prediction of hand trajectory by ensembles of cortical neurons in primates , 2000, Nature.

[3]  Yasuharu Koike,et al.  Prediction of Hand Trajectory from Electrocorticography Signals in Primary Motor Cortex , 2013, PloS one.

[4]  L. Miller,et al.  Restoration of grasp following paralysis through brain-controlled stimulation of muscles , 2012, Nature.

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

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

[7]  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.

[8]  Robert Chen,et al.  Identification of arm movements using correlation of electrocorticographic spectral components and kinematic recordings , 2007, Journal of neural engineering.

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

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

[11]  David M. Santucci,et al.  Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates , 2003, PLoS biology.

[12]  Naotaka Fujii,et al.  Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques , 2012, Journal of neural engineering.

[13]  Yasuharu Koike,et al.  Prediction of Muscle Activities from Electrocorticograms in Primary Motor Cortex of Primates , 2012, PloS one.

[14]  Timothy J Ebner,et al.  Signaling of grasp dimension and grasp force in dorsal premotor cortex and primary motor cortex neurons during reach to grasp in the monkey. , 2009, Journal of neurophysiology.

[15]  T J Ebner,et al.  Primary motor cortex neuronal discharge during reach-to-grasp: controlling the hand as a unit. , 2002, Archives italiennes de biologie.

[16]  Winnie Jensen,et al.  Influence of the feature space on the estimation of hand grasping force from intramuscular EMG , 2013, Biomed. Signal Process. Control..

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

[18]  Andrew S. Whitford,et al.  Cortical control of a prosthetic arm for self-feeding , 2008, Nature.

[19]  Grant H. Mullikenb,et al.  Cognitive signals for brain – machine interfaces in posterior parietal cortex include continuous 3 D trajectory , 2012 .

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

[21]  Daryl R Kipke,et al.  High γ power in ECoG reflects cortical electrical stimulation effects on unit activity in layers V/VI. , 2013, Journal of neural engineering.

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

[23]  Hyun-Chool Shin,et al.  Asynchronous Decoding of Dexterous Finger Movements Using M1 Neurons , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[24]  Aaron C. Koralek,et al.  Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills , 2012, Nature.

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

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

[27]  Shaomin Zhang,et al.  Decoding grasp movement from monkey premotor cortex for real-time prosthetic hand control , 2013 .

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

[29]  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.

[30]  Yasuharu Koike,et al.  Prediction of arm trajectory from a small number of neuron activities in the primary motor cortex , 2006, Neuroscience Research.

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

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

[33]  John P. Donoghue,et al.  ventral premotor cortices reach and grasp kinematics in primary motor and potentials, spiking activity, and three-dimensional Relationships among low-frequency local field , 2011 .

[34]  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.

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

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

[37]  R. Andersen,et al.  Cognitive Control Signals for Neural Prosthetics , 2004, Science.

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

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

[40]  Dragan F. Dimitrov,et al.  Reversible large-scale modification of cortical networks during neuroprosthetic control , 2011, Nature Neuroscience.

[41]  Tadashi Isa,et al.  Reconstruction of movement-related intracortical activity from micro-electrocorticogram array signals in monkey primary motor cortex , 2012, Journal of neural engineering.

[42]  M. M. Morrow,et al.  Prediction of muscle activity by populations of sequentially recorded primary motor cortex neurons. , 2003, Journal of neurophysiology.

[43]  D. Hoffman,et al.  Muscle and movement representations in the primary motor cortex. , 1999, Science.

[44]  R. Lemon,et al.  Selective facilitation of different hand muscles by single corticospinal neurones in the conscious monkey. , 1986, The Journal of physiology.

[45]  Toshiki Yoshimine,et al.  Neural decoding using gyral and intrasulcal electrocorticograms , 2009, NeuroImage.

[46]  Miguel A. L. Nicolelis,et al.  Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex , 1999, Nature Neuroscience.

[47]  Hansjörg Scherberger,et al.  Context-Specific Grasp Movement Representation in the Macaque Anterior Intraparietal Area , 2009, The Journal of Neuroscience.

[48]  A. M. Smith,et al.  Relation of activity in precentral cortical neurons to force and rate of force change during isometric contractions of finger muscles , 1975, Experimental Brain Research.