Neural prediction of complex accelerations for object interception

To intercept or avoid moving objects successfully, we must compensate for the sensorimotor delays associated with visual processing and motor movement. Although straightforward in the case of constant velocity motion, it is unclear how humans compensate for accelerations, as our visual system is rel...

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Main Authors: de Rugy, A., Marinovic, Welber, Wallis, G.
Format: Journal Article
Published: American Physiological Society 2012
Online Access:http://hdl.handle.net/20.500.11937/50254
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author de Rugy, A.
Marinovic, Welber
Wallis, G.
author_facet de Rugy, A.
Marinovic, Welber
Wallis, G.
author_sort de Rugy, A.
building Curtin Institutional Repository
collection Online Access
description To intercept or avoid moving objects successfully, we must compensate for the sensorimotor delays associated with visual processing and motor movement. Although straightforward in the case of constant velocity motion, it is unclear how humans compensate for accelerations, as our visual system is relatively poor at detecting changes in velocity. Work on free-falling objects suggests that we are able to predict the effects of gravity, but this represents the most simple, limiting case in which acceleration is constant and motion linear. Here, we show that an internal model also predicts the effects of complex, varying accelerations when they result from lawful interactions with the environment. Participants timed their responses with the arrival of a ball rolling within a tube of various shapes. The pattern of errors indicates that participants were able to compensate for most of the effects of the ball acceleration (~85%) within a relatively short practice (~300 trials). Errors on catch trials in which the ball velocity was unexpectedly maintained constant further confirmed that participants were expecting the effect of acceleration induced by the shape of the tube. A similar effect was obtained when the visual scene was projected upside down, indicating that the mechanism of this prediction is flexible and not confined to ecologically valid interactions. These findings demonstrate that the brain is able to predict motion on the basis of prior experience of complex interactions between an object and its environment.
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spelling curtin-20.500.11937-502542017-09-13T15:41:04Z Neural prediction of complex accelerations for object interception de Rugy, A. Marinovic, Welber Wallis, G. To intercept or avoid moving objects successfully, we must compensate for the sensorimotor delays associated with visual processing and motor movement. Although straightforward in the case of constant velocity motion, it is unclear how humans compensate for accelerations, as our visual system is relatively poor at detecting changes in velocity. Work on free-falling objects suggests that we are able to predict the effects of gravity, but this represents the most simple, limiting case in which acceleration is constant and motion linear. Here, we show that an internal model also predicts the effects of complex, varying accelerations when they result from lawful interactions with the environment. Participants timed their responses with the arrival of a ball rolling within a tube of various shapes. The pattern of errors indicates that participants were able to compensate for most of the effects of the ball acceleration (~85%) within a relatively short practice (~300 trials). Errors on catch trials in which the ball velocity was unexpectedly maintained constant further confirmed that participants were expecting the effect of acceleration induced by the shape of the tube. A similar effect was obtained when the visual scene was projected upside down, indicating that the mechanism of this prediction is flexible and not confined to ecologically valid interactions. These findings demonstrate that the brain is able to predict motion on the basis of prior experience of complex interactions between an object and its environment. 2012 Journal Article http://hdl.handle.net/20.500.11937/50254 10.1152/jn.00854.2011 American Physiological Society unknown
spellingShingle de Rugy, A.
Marinovic, Welber
Wallis, G.
Neural prediction of complex accelerations for object interception
title Neural prediction of complex accelerations for object interception
title_full Neural prediction of complex accelerations for object interception
title_fullStr Neural prediction of complex accelerations for object interception
title_full_unstemmed Neural prediction of complex accelerations for object interception
title_short Neural prediction of complex accelerations for object interception
title_sort neural prediction of complex accelerations for object interception
url http://hdl.handle.net/20.500.11937/50254