Relation of pyramidal tract activity to force exerted during voluntary movement.

Evarts, Edward V.

doi:10.1152/jn.1968.31.1.14

Cited by 1,106 publications

(533 citation statements)

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“…Many studies have tested the robustness of the signals encoded by single neurons by observing the relation between the neural discharge and movement-related variables while varying postural or loading conditions (Caminiti et al 1990;Evarts 1968;Kakei et al 1999;Kalaska et al 1989;Fig. 10.…”

Section: Discussionmentioning

confidence: 99%

“…While correlations exist between M1 and both kinematic and kinetic signals, it is not clear which, if any, may represent the "true" signal type encoded by M1. Experimentally, numerous attempts have been made to dissociate kinematic and kinetic signals by adding loads to the limb (Evarts 1968;Fagg et al 2009;Gandolfo et al 2000;Gribble and Scott 2002;Kalaska et al 1989) or by changing the posture of the limb to alter its mechanics (Caminiti et al 1990;Kakei et al 1999;Morrow et al 2007; Scott and Kalaska 1997). Taken together, these studies indicate that the discharge of many, but not all, M1 neurons is influenced by posture and external load.…”

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confidence: 99%

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

Cherian

Krucoff

Miller

2011

Journal of Neurophysiology

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Cherian A, Krucoff MO, Miller LE. Motor cortical prediction of EMG: evidence that a kinetic brain-machine interface may be robust across altered movement dynamics. J Neurophysiol 106: 564 -575, 2011. First published May 11, 2011 doi:10.1152/jn.00553.2010.-During typical movements, signals related to both the kinematics and kinetics of movement are mutually correlated, and each is correlated to some extent with the discharge of neurons in the primary motor cortex (M1). However, it is well known, if not always appreciated, that causality cannot be inferred from correlations. Although these mutual correlations persist, their nature changes with changing postural or dynamical conditions. Under changing conditions, only signals directly controlled by M1 can be expected to maintain a stable relationship with its discharge. If one were to rely on noncausal correlations for a brain-machine interface, its generalization across conditions would likely suffer. We examined this effect, using multielectrode recordings in M1 as input to linear decoders of both end point kinematics (position and velocity) and proximal limb myoelectric signals (EMG) during reaching. We tested these decoders across tasks that altered either the posture of the limb or the end point forces encountered during movement. Within any given task, the accuracy of the kinematic predictions tended to be somewhat better than the EMG predictions. However, when we used the decoders developed under one task condition to predict the signals recorded under different postural or dynamical conditions, only the EMG decoders consistently generalized well. Our results support the view that M1 discharge is more closely related to kinetic variables like EMG than it is to limb kinematics. These results suggest that brain-machine interface applications using M1 to control kinetic variables may prove to be more successful than the more standard kinematic approach.electromyogram; force field; limb movement; posture REACHING IS a deceptively simple action. We are typically aware only of the relatively straight, smoothly accelerating movement of the hand toward a target.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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

Cherian

Krucoff

Miller

2011

Journal of Neurophysiology

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“…The relation between limb force control and neural firing patterns in primate motor cortex is strongly correlated with the rate and direction of force change (Evarts, 1968;Georgopolous et al, 1992;Hepp-Reymond et al, 1978Humphrey et al, 1970;Moran and Schwartz, 1999;Smith et al, 1975) and preferred-torque directions biased toward limbflexor and limb-extensor torques (Herter et al, 2007;Kurtzer et al, 2006). Recent evidence suggests that the primary motor cortex plays a role in setting sensorimotor memory for fingertip forces during grip force (Berner et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

Modulation of the trigeminofacial pathway during syllabic speech

Estep

Barlow

2007

Brain Research

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The human orofacial system is richly endowed with low threshold, slowly adapting mechanoreceptors that respond to self-generated movements and external loads. The functional linkage between these afferents and the recruitment of motor units in the lower face during the dynamics of speech is unknown. Mechanically evoked activity in the orbicularis oris muscles was studied in young human female adults (N=10) during a lip force recruitment task associated with the repetition of the nonsense speech utterance "ah-wah." This speech task involved the recruitment of perioral motor units against an elastic load. A skin contactor probe coupled to a servo-controlled linear motor delivered punctate ipsilateral mechanical inputs (25 ms duration, 1800 μm displacement) to the glabrous surface of the upper lip in order to index the modulation and specificity of the compound trigeminofacial response as a function of speech force recruitment threshold (Ft). Modulation of the early (Ft = 0.2N) and later (Ft = 1.0N) components of the evoked perioral response was found at the two force thresholds. Beginning at approximately 60 ms post-stimulus, a significant suppression response was found among lower lip EMG recording sites and its magnitude was greatest when the mechanical perturbation occurred during the early phase of lip force recruitment. Variation in the lip force trajectories was manifest by a greater difference in net interangle force associated with lip perturbations indexed to the early Ft. This was interpreted to reflect the operation of a feedforward mechanism which may play a more significant role during an evolving speech action. Thus, the application of servo-controlled mechanosensory inputs effectively indexed the excitability of the facial motor nucleus during production of a simple speech phrase. Future studies are needed to explore mechanisms of short-term adaptation and trigeminofacial modulation during propositional speech in health and disease.

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“…Among the earliest experiments in which movement-related discharge from pyramidal tract neurons (PTNs) was recorded were those of Evarts. Those experiments revealed that the discharge rate of most PTNs was primarily related to the forces generating movement or the first time derivative of force (Evarts 1968). Somewhat later, experiments by Georgopoulos and colleagues revealed that movement-related discharge was related to the direction of hand movement by a simple, sinusoidal relation to a given cell's 'preferred direction' (Georgopoulos et al 1982).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2007

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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.

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Relation of pyramidal tract activity to force exerted during voluntary movement.

Cited by 1,106 publications

References 2 publications

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

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

Modulation of the trigeminofacial pathway during syllabic speech

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

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