Literature DB >> 22896725

Structural learning in feedforward and feedback control.

Nada Yousif1, Jörn Diedrichsen.   

Abstract

For smooth and efficient motor control, the brain needs to make fast corrections during the movement to resist possible perturbations. It also needs to adapt subsequent movements to improve future performance. It is important that both feedback corrections and feedforward adaptation need to be made based on noisy and often ambiguous sensory data. Therefore, the initial response of the motor system, both for online corrections and adaptive responses, is guided by prior assumptions about the likely structure of perturbations. In the context of correcting and adapting movements perturbed by a force field, we asked whether these priors are hard wired or whether they can be modified through repeated exposure to differently shaped force fields. We found that both feedback corrections to unexpected perturbations and feedforward adaptation to a new force field changed, such that they were appropriate to counteract the type of force field that participants had experienced previously. We then investigated whether these changes were driven by a common mechanism or by two separate mechanisms. Participants experienced force fields that were either temporally consistent, causing sustained adaptation, or temporally inconsistent, causing little overall adaptation. We found that the consistent force fields modified both feedback and feedforward responses. In contrast, the inconsistent force field modified the temporal shape of feedback corrections but not of the feedforward adaptive response. These results indicate that responses to force perturbations can be modified in a structural manner and that these modifications are at least partly dissociable for feedback and feedforward control.

Entities:  

Mesh:

Year:  2012        PMID: 22896725      PMCID: PMC3545174          DOI: 10.1152/jn.00315.2012

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


  37 in total

1.  Persistence of motor adaptation during constrained, multi-joint, arm movements.

Authors:  R A Scheidt; D J Reinkensmeyer; M A Conditt; W Z Rymer; F A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2000-08       Impact factor: 2.714

2.  A method for measuring endpoint stiffness during multi-joint arm movements.

Authors:  E Burdet; R Osu; D W Franklin; T Yoshioka; T E Milner; M Kawato
Journal:  J Biomech       Date:  2000-12       Impact factor: 2.712

3.  Description of learning to learn in human subjects.

Authors:  C P DUNCAN
Journal:  Am J Psychol       Date:  1960-03

4.  Structure and strength in causal induction.

Authors:  Thomas L Griffiths; Joshua B Tenenbaum
Journal:  Cogn Psychol       Date:  2005-10-05       Impact factor: 3.468

5.  Sensory prediction errors drive cerebellum-dependent adaptation of reaching.

Authors:  Ya-Weng Tseng; Jörn Diedrichsen; John W Krakauer; Reza Shadmehr; Amy J Bastian
Journal:  J Neurophysiol       Date:  2007-05-16       Impact factor: 2.714

6.  Evidence for the flexible sensorimotor strategies predicted by optimal feedback control.

Authors:  Dan Liu; Emanuel Todorov
Journal:  J Neurosci       Date:  2007-08-29       Impact factor: 6.167

7.  Shared internal models for feedforward and feedback control.

Authors:  Mark J Wagner; Maurice A Smith
Journal:  J Neurosci       Date:  2008-10-15       Impact factor: 6.167

8.  Adaptation to visuomotor transformations: consolidation, interference, and forgetting.

Authors:  John W Krakauer; Claude Ghez; M Felice Ghilardi
Journal:  J Neurosci       Date:  2005-01-12       Impact factor: 6.167

9.  The statistical determinants of adaptation rate in human reaching.

Authors:  Johannes Burge; Marc O Ernst; Martin S Banks
Journal:  J Vis       Date:  2008-04-23       Impact factor: 2.240

10.  Interacting adaptive processes with different timescales underlie short-term motor learning.

Authors:  Maurice A Smith; Ali Ghazizadeh; Reza Shadmehr
Journal:  PLoS Biol       Date:  2006-05-23       Impact factor: 8.029

View more
  25 in total

1.  Minimally invasive surgery training using multiple port sites to improve performance.

Authors:  Alan D White; Oscar Giles; Rebekah J Sutherland; Oliver Ziff; Mark Mon-Williams; Richard M Wilkie; J Peter A Lodge
Journal:  Surg Endosc       Date:  2014-04       Impact factor: 4.584

2.  Flexible Control of Safety Margins for Action Based on Environmental Variability.

Authors:  Alkis M Hadjiosif; Maurice A Smith
Journal:  J Neurosci       Date:  2015-06-17       Impact factor: 6.167

3.  Formation of a long-term memory for visuomotor adaptation following only a few trials of practice.

Authors:  David M Huberdeau; Adrian M Haith; John W Krakauer
Journal:  J Neurophysiol       Date:  2015-06-10       Impact factor: 2.714

4.  Time course of changes in the long-latency feedback response parallels the fast process of short-term motor adaptation.

Authors:  Susan K Coltman; Paul L Gribble
Journal:  J Neurophysiol       Date:  2020-07-08       Impact factor: 2.714

5.  Environmental consistency determines the rate of motor adaptation.

Authors:  Luis Nicolas Gonzalez Castro; Alkis M Hadjiosif; Matthew A Hemphill; Maurice A Smith
Journal:  Curr Biol       Date:  2014-05-01       Impact factor: 10.834

Review 6.  Skilled forelimb movements and internal copy motor circuits.

Authors:  Eiman Azim; Bror Alstermark
Journal:  Curr Opin Neurobiol       Date:  2015-01-10       Impact factor: 6.627

Review 7.  Computations in Sensorimotor Learning.

Authors:  Daniel M Wolpert
Journal:  Cold Spring Harb Symp Quant Biol       Date:  2015-04-07

8.  Representing delayed force feedback as a combination of current and delayed states.

Authors:  Guy Avraham; Firas Mawase; Amir Karniel; Lior Shmuelof; Opher Donchin; Ferdinando A Mussa-Ivaldi; Ilana Nisky
Journal:  J Neurophysiol       Date:  2017-07-19       Impact factor: 2.714

9.  Learning redundant motor tasks with and without overlapping dimensions: facilitation and interference effects.

Authors:  Rajiv Ranganathan; Jon Wieser; Kristine M Mosier; Ferdinando A Mussa-Ivaldi; Robert A Scheidt
Journal:  J Neurosci       Date:  2014-06-11       Impact factor: 6.167

10.  Feedforward and Feedback Control Share an Internal Model of the Arm's Dynamics.

Authors:  Rodrigo S Maeda; Tyler Cluff; Paul L Gribble; J Andrew Pruszynski
Journal:  J Neurosci       Date:  2018-10-24       Impact factor: 6.167

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.