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High-probability grants
According to our matching algorithm, James Gordon is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2004 — 2007 |
Lan, Ning [⬀]
Gordon, James |
N/AActivity Code Description:
No activity code was retrieved: click on the grant title for more information |
A Simulation Study of Sensorimotor Control of Reaching Movements @ University of Southern California
The purpose of this project is to determine how the nervous system implements principles of movement control. A computer model of neural control that is capable of generating simulated reaching movements that correspond closely to actual movements in both the dynamics of the trajectories and the acquisition of a final position will be developed. With this model two hypotheses about the control of human reaching movements will be tested: (1) multi-joint reaching movements are controlled with a dual strategy that separately specifies the dynamics of the movement trajectory and the final end point (or equilibrium point); and (2) spinal proprioceptive afferents from spindles and Golgi tendon organs are coordinated with gamma fusimotor control to provide simultaneous regulation of the equilibrium point and the surrounding stiffness field of joints, so that accurate and stable postures can be achieved. A recently developed, structural model of single-joint movement control by the investigators is able to produce simulated movements that are consistent with experimental findings. Simulations suggested that one of the roles of proprioceptive afferents in movement control is to regulate the equilibrium point of the joint via control to spindles. The results also demonstrated that movement trajectory can generated via a tri-phasic, pulse command to gamma motoneurons. By extending the model to a multi-joint system, simulation studies will allow determination of the demonstrated error pattern of reaching movements by the model. The research fosters a multi-disciplinary approach, in which the physiologically realistic, structural model is used as a means to interpret experimental data and to test hypotheses on motor control. Broader impacts include opportunities to enhance teaching in applying analytical methods of science and engineering to the interpretation of biological data for understanding sensorimotor control of movements.
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