Journal of applied physiology (Bethesda, Md. : 1985) · 2006
Adaptations in human neuromuscular function following prolonged unweighting: II. Neurological properties and motor imagery efficacy.
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Clark Brian C, Manini Todd M, Bolanowski Stanley J, Ploutz-Snyder Lori L
Аннотация
Strength loss following disuse may result from alterations in muscle and/or neurological properties. In this paper, we report our findings on human plantar flexor neurological properties following 4 wk of limb suspension [unilateral lower limb suspension (ULLS)], along with the effect of motor imagery (MI) training on these properties. In the companion paper (Part I), we report our findings on the changes in skeletal muscle properties. Additionally, in the present paper, we analyze our findings to determine the relative contribution of neural and muscular factors in strength loss. Measurements of central activation, the H-reflex, and nerve conduction were made before and after 4 wk of ULLS (n = 18; 19-28 yr). A subset of the subjects (n = 6) performed PF MI training 4 days/wk. Following ULLS, we observed a significant increase in the soleus H-reflex (45.4 +/- 4.0 to 51.9 +/- 3.7% expressed relative to the maximal muscle action potential). Additionally, there were longer intervals between the delivery of an electrical stimulus to the tibial nerve and the corresponding muscle action potential (M-wave latency; mean prolongation 0.49 ms) and H-reflex wave (H-wave latency; mean prolongation 0.46 ms). The efficacy of MI on strength was ambiguous, with no significant effect detected (although a modest effect size was observed; eta2 = 0.18). These findings suggest that unweighting induces plastic changes in neural function that appear to be spatially distributed throughout the nervous system. In terms of the relative contribution of neural and muscular factors regulating strength loss, we observed that neural factors (primarily deficits in central activation) explained 48% of the variability in strength loss, whereas muscular factors (primarily sarcolemma function) explained 39% of the variability.