Literature DB >> 12968016

Neuronal activity in the supplementary motor area of monkeys adapting to a new dynamic environment.

Camillo Padoa-Schioppa1, Chiang-Shan Ray Li, Emilio Bizzi.   

Abstract

To execute visually guided reaching movements, the central nervous system (CNS) must transform a desired hand trajectory (kinematics) into appropriate muscle-related commands (dynamics). It has been suggested that the CNS might face this challenging computation by using internal forward models for the dynamics. Previous work in humans found that new internal models can be acquired through experience. In a series of studies in monkeys, we investigated how neurons in the motor areas of the frontal lobe reflect the movement dynamics and how their activity changes when monkeys learn a new internal model. Here we describe the results for the supplementary motor area (SMA-proper, or SMA). In the experiments, monkeys executed visually guided reaching movements and adapted to an external perturbing force field. The experimental design allowed dissociating the neuronal activity related to movement dynamics from that related to movement kinematics. It also allowed dissociating the changes related to motor learning from the activity related to motor performance (kinematics and dynamics). We show that neurons in SMA reflect the movement dynamics individually and as a population, and that their activity undergoes a variety of plastic changes when monkeys adapt to a new dynamic environment.

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Year:  2003        PMID: 12968016     DOI: 10.1152/jn.00876.2002

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


  39 in total

1.  Activity of the same motor cortex neurons during repeated experience with perturbed movement dynamics.

Authors:  Andrew G Richardson; Tommaso Borghi; Emilio Bizzi
Journal:  J Neurophysiol       Date:  2012-03-28       Impact factor: 2.714

2.  Neuronal correlates of movement dynamics in the dorsal and ventral premotor area in the monkey.

Authors:  Jun Xiao; Camillo Padoa-Schioppa; Emilio Bizzi
Journal:  Exp Brain Res       Date:  2005-09-22       Impact factor: 1.972

Review 3.  Internal models in sensorimotor integration: perspectives from adaptive control theory.

Authors:  Chung Tin; Chi-Sang Poon
Journal:  J Neural Eng       Date:  2005-08-31       Impact factor: 5.379

4.  Functional network reorganization during learning in a brain-computer interface paradigm.

Authors:  Beata Jarosiewicz; Steven M Chase; George W Fraser; Meel Velliste; Robert E Kass; Andrew B Schwartz
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-01       Impact factor: 11.205

5.  Concurrent stable and unstable cortical correlates of human wrist movements.

Authors:  Matthias Witte; Ferran Galán; Stephan Waldert; Christoph Braun; Carsten Mehring
Journal:  Hum Brain Mapp       Date:  2014-01-22       Impact factor: 5.038

6.  Corticocortical Systems Underlying High-Order Motor Control.

Authors:  Alexandra Battaglia-Mayer; Roberto Caminiti
Journal:  J Neurosci       Date:  2019-03-18       Impact factor: 6.167

7.  Changes in corticospinal excitability during reach adaptation in force fields.

Authors:  Jean-Jacques Orban de Xivry; Mohammad Ali Ahmadi-Pajouh; Michelle D Harran; Yousef Salimpour; Reza Shadmehr
Journal:  J Neurophysiol       Date:  2012-10-03       Impact factor: 2.714

8.  Primary motor cortical discharge during force field adaptation reflects muscle-like dynamics.

Authors:  Anil Cherian; Hugo L Fernandes; Lee E Miller
Journal:  J Neurophysiol       Date:  2013-05-08       Impact factor: 2.714

9.  Affine differential geometry analysis of human arm movements.

Authors:  Tamar Flash; Amir A Handzel
Journal:  Biol Cybern       Date:  2007-04-04       Impact factor: 2.086

10.  Emergence of a stable cortical map for neuroprosthetic control.

Authors:  Karunesh Ganguly; Jose M Carmena
Journal:  PLoS Biol       Date:  2009-07-21       Impact factor: 8.029

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