Literature DB >> 24598520

Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance.

Aaron L Wong1, Mark Shelhamer2.   

Abstract

Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation.
Copyright © 2014 the American Physiological Society.

Entities:  

Keywords:  adaptation; error-correction mechanism; predictive saccades; saccades

Mesh:

Year:  2014        PMID: 24598520      PMCID: PMC4044342          DOI: 10.1152/jn.00779.2013

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


  35 in total

1.  An implicit plan overrides an explicit strategy during visuomotor adaptation.

Authors:  Pietro Mazzoni; John W Krakauer
Journal:  J Neurosci       Date:  2006-04-05       Impact factor: 6.167

2.  Modeling sensorimotor learning with linear dynamical systems.

Authors:  Sen Cheng; Philip N Sabes
Journal:  Neural Comput       Date:  2006-04       Impact factor: 2.026

3.  Explaining savings for visuomotor adaptation: linear time-invariant state-space models are not sufficient.

Authors:  Eric Zarahn; Gregory D Weston; Johnny Liang; Pietro Mazzoni; John W Krakauer
Journal:  J Neurophysiol       Date:  2008-07-02       Impact factor: 2.714

4.  Motor learning is optimally tuned to the properties of motor noise.

Authors:  Robert J van Beers
Journal:  Neuron       Date:  2009-08-13       Impact factor: 17.173

Review 5.  The role of the cerebellum in saccadic adaptation as a window into neural mechanisms of motor learning.

Authors:  Mario Prsa; Peter Thier
Journal:  Eur J Neurosci       Date:  2011-06       Impact factor: 3.386

6.  Model-based and model-free mechanisms of human motor learning.

Authors:  Adrian M Haith; John W Krakauer
Journal:  Adv Exp Med Biol       Date:  2013       Impact factor: 2.622

Review 7.  Saccadic suppression: a review and an analysis.

Authors:  E Matin
Journal:  Psychol Bull       Date:  1974-12       Impact factor: 17.737

8.  Sensorimotor adaptation error signals are derived from realistic predictions of movement outcomes.

Authors:  Aaron L Wong; Mark Shelhamer
Journal:  J Neurophysiol       Date:  2010-12-01       Impact factor: 2.714

9.  Saccadic suppression: elevation of visual threshold associated with saccadic eye movements.

Authors:  B L Zuber; L Stark
Journal:  Exp Neurol       Date:  1966-09       Impact factor: 5.330

10.  Using prediction errors to drive saccade adaptation: the implicit double-step task.

Authors:  Aaron L Wong; Mark Shelhamer
Journal:  Exp Brain Res       Date:  2012-08-01       Impact factor: 1.972

View more
  11 in total

1.  Saccadic adaptation to a systematically varying disturbance.

Authors:  Carlos R Cassanello; Sven Ohl; Martin Rolfs
Journal:  J Neurophysiol       Date:  2016-04-20       Impact factor: 2.714

2.  A switching cost for motor planning.

Authors:  Jean-Jacques Orban de Xivry; Philippe Lefèvre
Journal:  J Neurophysiol       Date:  2016-09-21       Impact factor: 2.714

3.  Inter-Trial Correlations in Predictive-Saccade Endpoints: Fractal Scaling Reflects Differential Control along Task-Relevant and Orthogonal Directions.

Authors:  Pamela Federighi; Aaron L Wong; Mark Shelhamer
Journal:  Front Hum Neurosci       Date:  2017-03-07       Impact factor: 3.169

4.  Assessing Somatosensory Utilization during Unipedal Postural Control.

Authors:  Rahul Goel; Yiri E De Dios; Nichole E Gadd; Erin E Caldwell; Brian T Peters; Millard F Reschke; Jacob J Bloomberg; Lars I E Oddsson; Ajitkumar P Mulavara
Journal:  Front Syst Neurosci       Date:  2017-04-11

5.  Strength of baseline inter-trial correlations forecasts adaptive capacity in the vestibulo-ocular reflex.

Authors:  Kara H Beaton; Aaron L Wong; Steven B Lowen; Mark Shelhamer
Journal:  PLoS One       Date:  2017-04-05       Impact factor: 3.240

Review 6.  Enhancing astronaut performance using sensorimotor adaptability training.

Authors:  Jacob J Bloomberg; Brian T Peters; Helen S Cohen; Ajitkumar P Mulavara
Journal:  Front Syst Neurosci       Date:  2015-09-16

7.  Trends in sensorimotor research and countermeasures for exploration-class space flights.

Authors:  Mark Shelhamer
Journal:  Front Syst Neurosci       Date:  2015-08-11

Review 8.  Individual predictors of sensorimotor adaptability.

Authors:  Rachael D Seidler; Ajitkumar P Mulavara; Jacob J Bloomberg; Brian T Peters
Journal:  Front Syst Neurosci       Date:  2015-07-06

9.  Predictive saccades in children and adults: A combined fMRI and eye tracking study.

Authors:  Katerina Lukasova; Mariana P Nucci; Raymundo Machado de Azevedo Neto; Gilson Vieira; João R Sato; Edson Amaro
Journal:  PLoS One       Date:  2018-05-02       Impact factor: 3.240

10.  Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy.

Authors:  R Chris Miall; Nick M Kitchen; Se-Ho Nam; Hannah Lefumat; Alix G Renault; Kristin Ørstavik; Jonathan D Cole; Fabrice R Sarlegna
Journal:  Exp Brain Res       Date:  2018-05-19       Impact factor: 1.972

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.