Prediction of upper limb muscle activity from motor cortical discharge during reaching

Abstract

Movement representation by the motor cortex (M1) has been a theoretical interest for many years, but in the past several years it has become a more practical question, with the advent of the brainmachine interface. An increasing number of groups have demonstrated the ability to predict a variety of kinematic signals on the basis of M1 recordings and to use these predictions to control the movement of a cursor or robotic limb. We, on the other hand, have undertaken the prediction of myoelectric (EMG) signals recorded from various muscles of the arm and hand during button pressing and prehension movements. We have shown that these signals can be predicted with accuracy that is similar to that of kinematic signals, despite their stochastic nature and greater bandwidth. The predictions were made using a subset of 12 or 16 neural signals selected in the order of each signal's unique, output-related information content. The accuracy of the resultant predictions remained stable through a typical experimental session. Accuracy remained above 80% of its initial level for most muscles even across periods as long as two weeks. We are exploring the use of these predictions as control signals for neuromuscular electrical stimulation in quadriplegic patients.

Motor cortical prediction of EMG: evidence that a kinetic brain-machine interface may be robust across altered movement dynamics

“…A direct comparison of end point kinematics and grip force found the latter to be predicted dramatically better (Carmena et al 2003), although EMG was predicted less accurately in that study. However, two other studies achieved predictions of the EMG measured from wrist muscles during isometric contractions with R 2 in the 0.7-0.8 range (Oby et al 2010;Pohlmeyer et al 2007b).…”

“…It is thought that caudal M1, with its increased tactile responsiveness, represents a newer cortical system that has evolved to provide the increased dexterity of humans and more advanced primates (Nakajima et al 2000;Preston 1978a, 1978b). Attempts to decode muscle activity related to the wrist and hand may well profit from recordings made in caudal M1 (Oby et al 2010;Pohlmeyer et al 2007bPohlmeyer et al , 2009). …”

“…We used a least squares regression method to compute a linear filter that minimized the error between the output of the decoder and the measured output (Pohlmeyer et al 2007b). The filters were 50 points long, thereby providing a weighted average of the discharge rates in 10-ms bins up to 500 ms in the past.…”

“…One group found accuracy in joint torque predictions that was nearly comparable to kinematic predictions during planar reaching (Fagg et al 2009). Another study achieved predictions of electromyogram (EMG) activity that were of similar or greater accuracy than those typical of kinematic studies (Pohlmeyer et al 2007b). Similar muscle activity predictions have been used as inputs to a forward dynamical model of the limb to provide both joint torque and kinematics predictions (Kim et al 2007).…”

Intrafascicular stimulation of monkey arm nerves evokes coordinated grasp and sensory responses

“…In a closely related project, we have demonstrated that recordings from similar UEAs implanted in the primary motor cortex of monkeys can provide accurate information about muscle activity during normal or intended movement (Pohlmeyer et al 2007). The information can be used to restore simple voluntary movement to monkeys during peripheral nerve block, used as a temporary paralysis model of SCI.…”