Literature DB >> 19571194

Models for the extrapolation of target motion for manual interception.

John F Soechting1, John Z Juveli, Hrishikesh M Rao.   

Abstract

Intercepting a moving target requires a prediction of the target's future motion. This extrapolation could be achieved using sensed parameters of the target motion, e.g., its position and velocity. However, the accuracy of the prediction would be improved if subjects were also able to incorporate the statistical properties of the target's motion, accumulated as they watched the target move. The present experiments were designed to test for this possibility. Subjects intercepted a target moving on the screen of a computer monitor by sliding their extended finger along the monitor's surface. Along any of the six possible target paths, target speed could be governed by one of three possible rules: constant speed, a power law relation between speed and curvature, or the trajectory resulting from a sum of sinusoids. A go signal was given to initiate interception and was always presented when the target had the same speed, irrespective of the law of motion. The dependence of the initial direction of finger motion on the target's law of motion was examined. This direction did not depend on the speed profile of the target, contrary to the hypothesis. However, finger direction could be well predicted by assuming that target location was extrapolated using target velocity and that the amount of extrapolation depended on the distance from the finger to the target. Subsequent analysis showed that the same model of target motion was also used for on-line, visually mediated corrections of finger movement when the motion was initially misdirected.

Mesh:

Year:  2009        PMID: 19571194      PMCID: PMC2746781          DOI: 10.1152/jn.00398.2009

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  39 in total

1.  Oculomotor responses to gradual changes in target direction.

Authors:  Leigh A Mrotek; Martha Flanders; John F Soechting
Journal:  Exp Brain Res       Date:  2006-01-18       Impact factor: 1.972

2.  Predicting curvilinear target motion through an occlusion.

Authors:  Leigh A Mrotek; John F Soechting
Journal:  Exp Brain Res       Date:  2006-10-12       Impact factor: 1.972

3.  Analysis and implementation of a neural extended Kalman filter for target tracking.

Authors:  Kathleen A Kramer; Stephen C Stubberud
Journal:  Int J Neural Syst       Date:  2006-02       Impact factor: 5.866

4.  Learning to integrate arbitrary signals from vision and touch.

Authors:  Marc O Ernst
Journal:  J Vis       Date:  2007-06-25       Impact factor: 2.240

Review 5.  Visuo-motor coordination and internal models for object interception.

Authors:  Myrka Zago; Joseph McIntyre; Patrice Senot; Francesco Lacquaniti
Journal:  Exp Brain Res       Date:  2009-01-13       Impact factor: 1.972

6.  On-line processing of uncertain information in visuomotor control.

Authors:  Jun Izawa; Reza Shadmehr
Journal:  J Neurosci       Date:  2008-10-29       Impact factor: 6.167

Review 7.  Computational approaches to spatial orientation: from transfer functions to dynamic Bayesian inference.

Authors:  Paul R MacNeilage; Narayan Ganesan; Dora E Angelaki
Journal:  J Neurophysiol       Date:  2008-10-08       Impact factor: 2.714

8.  Extrapolation of visual motion for manual interception.

Authors:  John F Soechting; Martha Flanders
Journal:  J Neurophysiol       Date:  2008-04-24       Impact factor: 2.714

9.  Target interception: hand-eye coordination and strategies.

Authors:  Leigh A Mrotek; John F Soechting
Journal:  J Neurosci       Date:  2007-07-04       Impact factor: 6.167

Review 10.  Probabilistic models in human sensorimotor control.

Authors:  Daniel M Wolpert
Journal:  Hum Mov Sci       Date:  2007-07-12       Impact factor: 2.161

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  14 in total

1.  Extrapolation of vertical target motion through a brief visual occlusion.

Authors:  Myrka Zago; Marco Iosa; Vincenzo Maffei; Francesco Lacquaniti
Journal:  Exp Brain Res       Date:  2009-10-31       Impact factor: 1.972

2.  Discrimination of curvature from motion during smooth pursuit eye movements and fixation.

Authors:  Nicholas M Ross; Alexander Goettker; Alexander C Schütz; Doris I Braun; Karl R Gegenfurtner
Journal:  J Neurophysiol       Date:  2017-06-28       Impact factor: 2.714

3.  Familiar trajectories facilitate the interpretation of physical forces when intercepting a moving target.

Authors:  Antonija Mijatović; Barbara La Scaleia; Nicola Mercuri; Francesco Lacquaniti; Myrka Zago
Journal:  Exp Brain Res       Date:  2014-08-21       Impact factor: 1.972

4.  Differential contributions to the interception of occluded ballistic trajectories by the temporoparietal junction, area hMT/V5+, and the intraparietal cortex.

Authors:  Sergio Delle Monache; Francesco Lacquaniti; Gianfranco Bosco
Journal:  J Neurophysiol       Date:  2017-07-12       Impact factor: 2.714

5.  Hand interception of occluded motion in humans: a test of model-based vs. on-line control.

Authors:  Barbara La Scaleia; Myrka Zago; Francesco Lacquaniti
Journal:  J Neurophysiol       Date:  2015-07-01       Impact factor: 2.714

6.  Incorporating prediction in models for two-dimensional smooth pursuit.

Authors:  John F Soechting; Hrishikesh M Rao; John Z Juveli
Journal:  PLoS One       Date:  2010-09-03       Impact factor: 3.240

7.  Following and intercepting scribbles: interactions between eye and hand control.

Authors:  Leigh A Mrotek
Journal:  Exp Brain Res       Date:  2013-04-04       Impact factor: 1.972

8.  Catching what we can't see: manual interception of occluded fly-ball trajectories.

Authors:  Gianfranco Bosco; Sergio Delle Monache; Francesco Lacquaniti
Journal:  PLoS One       Date:  2012-11-14       Impact factor: 3.240

Review 9.  Filling gaps in visual motion for target capture.

Authors:  Gianfranco Bosco; Sergio Delle Monache; Silvio Gravano; Iole Indovina; Barbara La Scaleia; Vincenzo Maffei; Myrka Zago; Francesco Lacquaniti
Journal:  Front Integr Neurosci       Date:  2015-02-23

10.  Integration of speed and time for estimating time to contact.

Authors:  Chia-Jung Chang; Mehrdad Jazayeri
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-05       Impact factor: 11.205

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