Arm Movements Evoked by Electrical Stimulation in the Motor Cortex of Monkeys

Graziano, Michael S. A.; Aflalo, Tyson; Cooke, Dylan F.

doi:10.1152/jn.01303.2004

Cited by 155 publications

(155 citation statements)

References 47 publications

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“…Our data support the finding that HFLD-ICMS at a particular cortical site produces movements of the forelimb toward a final common end-point position independent of the starting position (Graziano et al, 2002;Graziano et al, 2005). We also found that muscle activation associated with HFLD-ICMS is largely stable in sign, magnitude, and temporal pattern independent of starting position or arm posture.…”

Section: Discussionsupporting

confidence: 87%

EMG Activation Patterns Associated with High Frequency, Long-Duration Intracortical Microstimulation of Primary Motor Cortex

et al. 2014

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The delivery of high-frequency, long-duration intracortical microstimulation (HFLD-ICMS) to primary motor cortex (M1) in primates produces hand movements to a common final end-point regardless of the starting hand position (Graziano et al., 2002). We have confirmed this general conclusion. We further investigated the extent to which the (1) temporal pattern, (2) magnitude, and (3) latency of electromyographic (EMG) activation associated with HFLD-ICMS-evoked movements are dependent on task conditions, including limb posture. HFLD-ICMS was applied to layer V sites in M1 cortex. EMG activation with HFLD-ICMS was evaluated while two male rhesus macaques performed a number of tasks in which the starting position of the hand could be varied throughout the workspace. HFLD-ICMS-evoked EMG activity was largely stable across all parameters tested independent of starting hand position. The most common temporal pattern of HFLD-ICMS-evoked EMG activity (58% of responses) was a sharp rise to a plateau. The plateau level was maintained essentially constant for the entire duration of the stimulus train. The plateau pattern is qualitatively different from the largely bell-shaped patterns typical of EMG activity associated with natural goal directed movements (Brown and Cooke, 1990; Hoffman and Strick, 1999). HFLD-ICMS produces relatively fixed parameters of muscle activation independent of limb position. We conclude that joint movement associated with HFLD-ICMS occurs as a function of the length-tension properties of stimulus-activated muscles until an equilibrium between agonist and antagonist muscle force is achieved.

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Section: Discussionsupporting

confidence: 87%

EMG Activation Patterns Associated with High Frequency, Long-Duration Intracortical Microstimulation of Primary Motor Cortex

et al. 2014

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“…In this light, it is important to consider that control potentials are revealing the effects of only one component signal in the broader motor programme. Showing how these specific causal relationships are combined, perhaps nonlinearly, into synergies [24,56,57] or motor primitives [22,58], or how they remain flexible, distinct elements [57,59] will test how specific muscles contribute to a control strategy.…”

Section: Discussionmentioning

confidence: 99%

A single muscle's multifunctional control potential of body dynamics for postural control and running

Sponberg

Spence

Mullens

et al. 2011

Phil. Trans. R. Soc. B

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A neuromechanical approach to control requires understanding how mechanics alters the potential of neural feedback to control body dynamics. Here, we rewrite activation of individual motor units of a behaving animal to mimic the effects of neural feedback without concomitant changes in other muscles. We target a putative control muscle in the cockroach, Blaberus discoidalis (L.), and simultaneously capture limb and body dynamics through high-speed videography and a microaccelerometer backpack. We test four neuromechanical control hypotheses. We supported the hypothesis that mechanics linearly translates neural feedback into accelerations and rotations during static postural control. However, during running, the same neural feedback produced a nonlinear acceleration control potential restricted to the vertical plane. Using this, we reject the hypothesis from previous work that this muscle acts primarily to absorb energy from the body. The conversion of the control potential is paralleled by nonlinear changes in limb kinematics, supporting the hypothesis that significant mechanical feedback filters the graded neural feedback for running control. Finally, we insert the same neural feedback signal but at different phases in the dynamics. In this context, mechanical feedback enables turning by changing the timing and direction of the accelerations produced by the graded neural feedback.

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“…Further evidence for the importance of kinematic parameters in the generation of reaching movements was provided by direct stimulation of the motor cortex (Graziano, Aflalo, & Cooke, 2005;Graziano, Taylor, & Moore, 2002). These studies imply one-toone mappings between workspace and arm posture located in the motor cortex.…”

Section: Relation To Neurophysiological Evidencementioning

confidence: 93%

Inter-joint coupling and joint angle synergies of human catching movements

Bockemühl

Troje

Dürr

2010

Human Movement Science

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A central question in motor control is how the central nervous system (CNS) deals with redundant degrees of freedom (DoFs) inherent in the musculoskeletal system. One way to simplify control of a redundant system is to combine several DoFs into synergies. In reaching movements of the human arm, redundancy occurs at the kinematic level because there are an unlimited number of arm postures for each position of the hand. Redundancy also occurs at the level of muscle forces because each arm posture can be maintained by a set of muscle activation patterns. Both postural and force-related motor synergies may contribute to simplify the control problem. The present study analyzes the kinematic complexity of natural, unrestrained human arm movements, and detects the amount of kinematic synergy in a vast variety of arm postures. We have measured interjoint coupling of the human arm and shoulder girdle during fast, unrestrained and untrained catching movements. Participants were asked to catch a ball launched towards them on 16 different trajectories. These had to be reached from two different initial positions. Movement of the right arm was recorded using optical motion capture and was transformed into 10 joint angle time courses, corresponding to 3 DoFs of the shoulder girdle and 7 of the arm. The resulting time series of the arm postures were analyzed by Principal Components Analysis (PCA). We found that the first three principal components (PCs) always captured more than 97% of the variance. Furthermore, subspaces spanned by PC sets associated with different catching positions varied smoothly across the arm's workspace. When we pooled complete sets of movements, three PCs, the theoretical minimum for reaching in 3D space, were sufficient to explain 80% of the data's variance. We assumed that the linearly correlated DoFs of each significant PC represent cardinal joint angle synergies, and showed that catching movements towards a multitude of targets in the arm's workspace can be generated efficiently by linear combinations of three of such synergies. The contribution of each synergy changed during a single catching movement and often varied systematically with target location. We conclude that unrestrained, one-handed catching movements are dominated by strong kinematic couplings between the joints that reduce the kinematic complexity of the human arm and shoulder girdle to three non-redundant DoFs. ACCEPTED MANUSCRIPT4

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Arm Movements Evoked by Electrical Stimulation in the Motor Cortex of Monkeys

Cited by 155 publications

References 47 publications

EMG Activation Patterns Associated with High Frequency, Long-Duration Intracortical Microstimulation of Primary Motor Cortex

EMG Activation Patterns Associated with High Frequency, Long-Duration Intracortical Microstimulation of Primary Motor Cortex

A single muscle's multifunctional control potential of body dynamics for postural control and running

Inter-joint coupling and joint angle synergies of human catching movements

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