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Sensorimotor control: computing the immediate future from the delayed present

Overview of attention for article published in BMC Bioinformatics, July 2016
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Title
Sensorimotor control: computing the immediate future from the delayed present
Published in
BMC Bioinformatics, July 2016
DOI 10.1186/s12859-016-1098-2
Pubmed ID
Authors

Arman Sargolzaei, Mohamed Abdelghani, Kang K. Yen, Saman Sargolzaei

Abstract

The 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. This 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. Three 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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 22%
Researcher 3 13%
Student > Bachelor 2 9%
Other 2 9%
Student > Postgraduate 2 9%
Other 6 26%
Unknown 3 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 13%
Neuroscience 3 13%
Engineering 3 13%
Medicine and Dentistry 3 13%
Psychology 2 9%
Other 7 30%
Unknown 2 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 July 2016.
All research outputs
#7,992,576
of 9,219,696 outputs
Outputs from BMC Bioinformatics
#3,618
of 3,919 outputs
Outputs of similar age
#220,668
of 264,521 outputs
Outputs of similar age from BMC Bioinformatics
#88
of 100 outputs
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