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Takemura N, Fukui T, Inui T. A Computational Model for Aperture Control in Reach-to-Grasp Movement Based on Predictive Variability. Front Comput Neurosci. 2015;9:143doi: 10.3389/fncom.2015.00143.
Takemura, N., Fukui, T., & Inui, T. (2015). A Computational Model for Aperture Control in Reach-to-Grasp Movement Based on Predictive Variability. Frontiers in computational neuroscience, 9143. https://doi.org/10.3389/fncom.2015.00143
Takemura, Naohiro, et al. "A Computational Model for Aperture Control in Reach-to-Grasp Movement Based on Predictive Variability." Frontiers in computational neuroscience vol. 9 (2015): 143. doi: https://doi.org/10.3389/fncom.2015.00143
Takemura N, Fukui T, Inui T. A Computational Model for Aperture Control in Reach-to-Grasp Movement Based on Predictive Variability. Front Comput Neurosci. 2015 Dec 10;9:143. doi: 10.3389/fncom.2015.00143. eCollection 2015. PMID: 26696874; PMCID: PMC4675317.
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Front Comput Neurosci. 2015 Dec 10;9:143. doi: 10.3389/fncom.2015.00143. eCollection 2015.

A Computational Model for Aperture Control in Reach-to-Grasp Movement Based on Predictive Variability.

Frontiers in computational neuroscience

Naohiro Takemura, Takao Fukui, Toshio Inui

Affiliations

  1. Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Yoshida-honmachi Kyoto, Japan.

PMID: 26696874 PMCID: PMC4675317 DOI: 10.3389/fncom.2015.00143

Abstract

In human reach-to-grasp movement, visual occlusion of a target object leads to a larger peak grip aperture compared to conditions where online vision is available. However, no previous computational and neural network models for reach-to-grasp movement explain the mechanism of this effect. We simulated the effect of online vision on the reach-to-grasp movement by proposing a computational control model based on the hypothesis that the grip aperture is controlled to compensate for both motor variability and sensory uncertainty. In this model, the aperture is formed to achieve a target aperture size that is sufficiently large to accommodate the actual target; it also includes a margin to ensure proper grasping despite sensory and motor variability. To this end, the model considers: (i) the variability of the grip aperture, which is predicted by the Kalman filter, and (ii) the uncertainty of the object size, which is affected by visual noise. Using this model, we simulated experiments in which the effect of the duration of visual occlusion was investigated. The simulation replicated the experimental result wherein the peak grip aperture increased when the target object was occluded, especially in the early phase of the movement. Both predicted motor variability and sensory uncertainty play important roles in the online visuomotor process responsible for grip aperture control.

Keywords: Kalman filter; computational model; motor control; online vision; reach-to-grasp movement

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