Neural prediction of complex accelerations for object interception
Journal of Neurophysiology. 2012-02-01; 107(3): 766-771
DOI: 10.1152/jn.00854.2011
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1. J Neurophysiol. 2012 Feb;107(3):766-71. doi: 10.1152/jn.00854.2011. Epub 2011 Nov
16.
Neural prediction of complex accelerations for object interception.
de Rugy A(1), Marinovic W, Wallis G.
Author information:
(1)Centre for Sensorimotor Neuroscience, School of Human Movement Studies,
University of Queensland, Brisbane, Queensland, Australia.
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.
DOI: 10.1152/jn.00854.2011
PMID: 22090456 [Indexed for MEDLINE]