Literature DB >> 28113982

Forces That Supplement Visuomotor Learning: A "Sensory Crossover" Experiment.

Moria Fisher Bittmann, James Lanphier Patton.   

Abstract

Previous studies on reaching movements have shown that people can adapt to either visuomotor (e.g., prism glasses) or mechanical distortions (e.g., force fields) through repetitive practice. Recent work has shown that adaptation to one type of distortion might have implications on learning the other type, suggesting that neural resources are common to both kinematic and kinetic adaptation. This study investigated whether training with a novel force field might benefit the learning of a visual distortion-specifically, when forces were designed to produce aftereffects that aligned with the ideal trajectory for a visual rotation. Participants training with these forces (Force Group) were tested on a visual rotation. After training with this novel field, we found that participants had surprisingly good performance in the visual rotation condition, comparable to a group that trained on the visual rotation directly. A third group tested the rate of learning with intermittent catch trials, where we zeroed the forces and switched to the visual rotation, and found a significantly faster learning rate than the group that trained directly on the visual rotation. Interestingly, these abilities continued to significantly improve one day later, whereas the direct training showed no such effect. All participants were able to generalize what they learned to unpracticed movement directions. We speculate that when forces are used in training, haptic feedback can have a substantial influence on learning a task that heavily relies on visual feedback. Such methods can impact any situation where one might add robotic forces to the training process.

Entities:  

Mesh:

Year:  2016        PMID: 28113982      PMCID: PMC5644020          DOI: 10.1109/TNSRE.2016.2613443

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  21 in total

1.  Composition and decomposition of internal models in motor learning under altered kinematic and dynamic environments.

Authors:  J R Flanagan; E Nakano; H Imamizu; R Osu; T Yoshioka; M Kawato
Journal:  J Neurosci       Date:  1999-10-15       Impact factor: 6.167

2.  Independent learning of internal models for kinematic and dynamic control of reaching.

Authors:  J W Krakauer; M F Ghilardi; C Ghez
Journal:  Nat Neurosci       Date:  1999-11       Impact factor: 24.884

3.  Kinematics and dynamics are not represented independently in motor working memory: evidence from an interference study.

Authors:  Christine Tong; Daniel M Wolpert; J Randall Flanagan
Journal:  J Neurosci       Date:  2002-02-01       Impact factor: 6.167

4.  Robot-assisted adaptive training: custom force fields for teaching movement patterns.

Authors:  James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Trans Biomed Eng       Date:  2004-04       Impact factor: 4.538

5.  Learning kinematic mappings in laparoscopic surgery.

Authors:  Felix C Huang; Carla M Pugh; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

6.  Functional stages in the formation of human long-term motor memory.

Authors:  R Shadmehr; T Brashers-Krug
Journal:  J Neurosci       Date:  1997-01-01       Impact factor: 6.167

7.  Human cerebellar activity reflecting an acquired internal model of a new tool.

Authors:  H Imamizu; S Miyauchi; T Tamada; Y Sasaki; R Takino; B Pütz; T Yoshioka; M Kawato
Journal:  Nature       Date:  2000-01-13       Impact factor: 49.962

8.  Masked priming of complex movements: perceptual and motor processes in unconscious action perception.

Authors:  Iris Güldenpenning; Jelena F Braun; Daniel Machlitt; Thomas Schack
Journal:  Psychol Res       Date:  2014-09-04

9.  Consolidation in human motor memory.

Authors:  T Brashers-Krug; R Shadmehr; E Bizzi
Journal:  Nature       Date:  1996-07-18       Impact factor: 49.962

10.  Reduction in learning rates associated with anterograde interference results from interactions between different timescales in motor adaptation.

Authors:  Gary C Sing; Maurice A Smith
Journal:  PLoS Comput Biol       Date:  2010-08-19       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.