Literature DB >> 3730133

Manual tracking of visual targets by trained monkeys.

R C Miall, D J Weir, J F Stein.   

Abstract

Monkeys were trained to track moving visual targets using a hand-held joystick. The overall frequency response of their visuomotor system was determined using sinusoidal target waveforms. Their responses could be approximately represented by a linear feedforward model consisting of a 0.9 Hz low-pass filter with an additional 150 ms time delay. However, the monkeys normally tracked the target by making intermittent movements of the joystick. Thus, their responses were more realistically modelled as a non-linear sampled feedback model with a loop delay of 250-280 ms. Intermittency allows the monkeys to achieve a good frequency response and maintain tracking stability despite an irreducible visuomotor loop delay of 250-300 ms. When tracking pseudorandom waveforms the monkeys' movements were mainly controlled by positional error. But when tracking predictable sinusoids the amplitude and velocity of each movement was not solely determined by positional error. Instead the monkeys made use of target feedforward, and also internal models of the target waveform, in order to improve their tracking performance. Feedforward control dominated feedback control at high target frequencies, suggesting that the monkeys cannot model targets with long cycle periods.

Mesh:

Year:  1986        PMID: 3730133     DOI: 10.1016/0166-4328(86)90003-3

Source DB:  PubMed          Journal:  Behav Brain Res        ISSN: 0166-4328            Impact factor:   3.332


  36 in total

1.  Manual tracking enhances smooth pursuit eye movements.

Authors:  Diederick C Niehorster; Wilfred W F Siu; Li Li
Journal:  J Vis       Date:  2015       Impact factor: 2.240

2.  Adaptation to visual feedback delays in manual tracking: evidence against the Smith Predictor model of human visually guided action.

Authors:  R C Miall; J K Jackson
Journal:  Exp Brain Res       Date:  2006-01-20       Impact factor: 1.972

3.  Role of vestibular and neck inputs for the perception of object motion in space.

Authors:  T Mergner; G Rottler; H Kimmig; W Becker
Journal:  Exp Brain Res       Date:  1992       Impact factor: 1.972

4.  Binding of movement, sound and touch: multimodal coordination dynamics.

Authors:  J Lagarde; J A S Kelso
Journal:  Exp Brain Res       Date:  2006-03-10       Impact factor: 1.972

5.  An internal model of a moving visual target in the lateral cerebellum.

Authors:  Nadia L Cerminara; Richard Apps; Dilwyn E Marple-Horvat
Journal:  J Physiol       Date:  2008-12-01       Impact factor: 5.182

6.  Control of force during rapid visuomotor force-matching tasks can be described by discrete time PID control algorithms.

Authors:  Jakob Lund Dideriksen; Daniel F Feeney; Awad M Almuklass; Roger M Enoka
Journal:  Exp Brain Res       Date:  2017-05-29       Impact factor: 1.972

7.  Corrective jitter motion shows similar individual frequencies for the arm and the finger.

Authors:  Lior Noy; Uri Alon; Jason Friedman
Journal:  Exp Brain Res       Date:  2015-01-29       Impact factor: 1.972

8.  Learning the trajectory of a moving visual target and evolution of its tracking in the monkey.

Authors:  Clara Bourrelly; Julie Quinet; Patrick Cavanagh; Laurent Goffart
Journal:  J Neurophysiol       Date:  2016-09-28       Impact factor: 2.714

9.  Oculo-manual tracking of visual targets in monkey: role of the arm afferent information in the control of arm and eye movements.

Authors:  G M Gauthier; F Mussa Ivaldi
Journal:  Exp Brain Res       Date:  1988       Impact factor: 1.972

10.  Visuo-motor tracking during reversible inactivation of the cerebellum.

Authors:  R C Miall; D J Weir; J F Stein
Journal:  Exp Brain Res       Date:  1987       Impact factor: 1.972

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