Plasticity in the Distribution of the Red Nucleus Output to Forearm Muscles After Unilateral Lesions of the Pyramidal Tract
- 1 May 2000
- journal article
- research article
- Published by American Physiological Society in Journal of Neurophysiology
- Vol. 83 (5) , 3147-3153
- https://doi.org/10.1152/jn.2000.83.5.3147
Abstract
It has been hypothesized that the magnocellular red nucleus (RNm) contributes to compensation for motor impairments associated with lesions of the pyramidal tract. To test this hypothesis, we used stimulus triggered averaging (StTA) of electromyographic (EMG) activity to characterize changes in motor output from the red nucleus after lesions of the pyramidal tract. Three monkeys were trained to perform a reach and prehension task. EMG activity was recorded from 11 forearm muscles including one elbow, five wrist, and five digit muscles. Microstimulation (20 μA at 20 Hz) was delivered throughout the movement task to compute StTAs. Two monkeys served as controls. In a third monkey, 65% of the left pyramidal tract had been destroyed by an electrolytic lesion method five years before recording. The results demonstrate a clear pattern of postlesion reorganization in red nucleus–mediated output effects on forearm muscles. The normally prominent extensor preference in excitatory output from the RNm (92% in extensors) was greatly diminished in the lesioned monkey (59%). Similarly, suppression effects, which are normally much more prominent in flexor than in extensor muscles (90% in flexors), were also more evenly distributed after recovery from pyramidal tract lesions. Because of the limited excitatory output from the RNm to flexor muscles that normally exists, loss of corticospinal output would leave control of flexors particularly weak. The changes in RNm organization reported in this study would help restore function to flexor muscles. These results support the hypothesis that the RNm is capable of reorganization that contributes to the recovery of forelimb motor function after pyramidal tract lesions.Keywords
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