Literature DB >> 15480596

Acquisition and generalization of visuomotor transformations by nonhuman primates.

Rony Paz1, Chen Nathan, Thomas Boraud, Hagai Bergman, Eilon Vaadia.   

Abstract

The kinematics of straight reaching movements can be specified vectorially by the direction of the movement and its extent. To explore the representation in the brain of these two properties, psychophysical studies have examined learning of visuomotor transformations of either rotation or gain and their generalization. However, the neuronal substrates of such complex learning are only beginning to be addressed. As an initial step in ensuring the validity of such investigations, it must be shown that monkeys indeed learn and generalize visuomotor transformations in the same manner as humans. Here, we analyze trajectories and velocities of movements as monkeys adapt to either rotational or gain transformations. We used rotations with different signs and magnitudes, and gains with different signs, and analyzed transfer of learning to untrained movements. The results show that monkeys can adapt to both types of transformation with a time course that resembles human learning. Analysis of the aftereffects reveals that rotation is learned locally and generalizes poorly to untrained directions, whereas gain is learned more globally and can be transferred to other amplitudes. The results lend additional support to the hypothesis that reaching movements are learned locally but can be easily rescaled to other magnitudes by scaling the peak velocity. The findings also indicate that reaching movements in monkeys are planned and executed very similarly to those in humans. This validates the underlying presumption that neuronal recordings in primates can help elucidate the mechanisms of motor learning in particular and motor planning in general.

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Year:  2004        PMID: 15480596     DOI: 10.1007/s00221-004-2061-4

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  41 in total

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Journal:  Curr Opin Neurobiol       Date:  1999-12       Impact factor: 6.627

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Authors:  S Abeele; O Bock
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Authors:  I-Han Chou; Stephen G Lisberger
Journal:  J Neurosci       Date:  2002-06-01       Impact factor: 6.167

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  12 in total

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5.  State-Based Delay Representation and Its Transfer from a Game of Pong to Reaching and Tracking.

Authors:  Guy Avraham; Raz Leib; Assaf Pressman; Lucia S Simo; Amir Karniel; Lior Shmuelof; Ferdinando A Mussa-Ivaldi; Ilana Nisky
Journal:  eNeuro       Date:  2017-12-26

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Authors:  Matthew D Golub; Byron M Yu; Steven M Chase
Journal:  Elife       Date:  2015-12-08       Impact factor: 8.140

7.  Bias, optimal linear estimation, and the differences between open-loop simulation and closed-loop performance of spiking-based brain-computer interface algorithms.

Authors:  Steven M Chase; Andrew B Schwartz; Robert E Kass
Journal:  Neural Netw       Date:  2009-05-22

8.  Expressions of multiple neuronal dynamics during sensorimotor learning in the motor cortex of behaving monkeys.

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Journal:  PLoS One       Date:  2011-07-06       Impact factor: 3.240

9.  Recasting brain-machine interface design from a physical control system perspective.

Authors:  Yin Zhang; Steven M Chase
Journal:  J Comput Neurosci       Date:  2015-07-05       Impact factor: 1.621

10.  Generalization of stochastic visuomotor rotations.

Authors:  Hugo L Fernandes; Ian H Stevenson; Konrad P Kording
Journal:  PLoS One       Date:  2012-08-14       Impact factor: 3.240

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