ArticleScientific reports2021
Quantitative evaluation of posture control in rats with inferior olive lesions.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 3 citations in OpenAlex.
- Anticipatory postural control emerges from a predictive and optimized strategy for movement preparation.Communications biology · 2026Article
- Role of CaMKIIa reticular neurons of caudal medulla in control of posture.Communications biology · 2025Article
- A Model of Predictive Postural Control Against Floor Tilting in Rats.Frontiers in systems neuroscience · 2021Article
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Authors and funding
7 authors at 4 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Impairment of inferior olivary neurons (IONs) affects whole-body movements and results in abnormal gait and posture. Because IONs are activated by unpredicted motion rather than regular body movements, the postural dysfunction caused by ION lesions is expected to involve factors other than simple loss of feedback control. In this study, we measured the postural movements of rats with pharmacological ION lesions (IO rats) trained to stand on their hindlimbs. The coordination of body segments as well as the distribution and frequency characteristics of center of mass (COM) motion were analyzed. We determined that the lesion altered the peak properties of the power spectrum density of the COM, whereas changes in coordination and COM distribution were minor. To investigate how the observed properties reflected changes in the control system, we constructed a mathematical model of the standing rats and quantitatively identified the control system. We found an increase in linear proportional control and a decrease in differential and nonlinear control in IO rats compared with intact rats. The dystonia-like changes in body stiffness explain the nature of the linear proportional and differential control, and a disorder in the internal model is one possible cause of the decrease in nonlinear control.
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