Sensorimotor control: computing the immediate future from the delayed present

BMC Bioinformatics

Research

Arman Sargolzaei¹  Kang K. Yen¹  Mohamed Abdelghani²  Saman Sargolzaei³ 

[1] Department of Electrical and Computer Engineering, Florida International University, 33174, Miami, FL, USA;Department of Mathematics and Statistics, University of Alberta, 30332, Edmonton, Canada;Research and Development Department, Rancs Group LLC, 33172, Miami, FL, USA;

关键词: Sensorimotor control;    Time delay estimation;    Vestibulo-Ocular Reflex (VOR);    Predictive control;    Motor learning;   

DOI  :  10.1186/s12859-016-1098-2

来源: Springer

【 摘 要 】

BackgroundThe predictive nature of the primate sensorimotor systems, for example the smooth pursuit system and their ability to compensate for long delays have been proven by many physiological experiments. However, few theoretical models have tried to explain these facts comprehensively. Here, we propose a sensorimotor learning and control model that can be used to (1) predict the dynamics of variable time delays and current and future sensory states from delayed sensory information; (2) learn new sensorimotor realities; and (3) control a motor system in real time.ResultsThis paper proposed a new time-delay estimation method and developed a computational model for a predictive control solution of a sensorimotor control system under time delay. Simulation experiments are used to demonstrate how the proposed model can explain a sensorimotor system’s ability to compensate for delays during online learning and control. To further illustrate the benefits of the proposed time-delay estimation method and predictive control in sensorimotor systems a simulation of the horizontal Vestibulo-Ocular Reflex (hVOR) system is presented.Without the proposed time-delay estimation and prediction, the hVOR can be unstable and could be affected by high frequency oscillations. These oscillations are reminiscent of a fast correction mechanism, e.g., a saccade to compensate for the hVOR delays. Comparing results of the proposed model with those in literature, it is clear that the hVOR system with impaired time-delay estimation or impaired sensory state predictor can mimic certain outcomes of sensorimotor diseases. Even more, if the control of hVOR is augmented with the proposed time-delay estimator and the predictor for eye position relative to the head, then hVOR control system can be stabilized.ConclusionsThree claims with varying degrees of experimental support are proposed in this paper. Firstly, the brain or any sensorimotor system has time-delay estimation circuits for the various sensorimotor control systems. Secondly, the brain continuously estimates current/future sensory states from the previously sensed states. Thirdly, the brain uses predicted sensory states to perform optimal motor control.

【 授权许可】

CC BY   
© The Author(s). 2016

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