Literature DB >> 14714157

Internal models underlying grasp can be additively combined.

Paul R Davidson1, Daniel M Wolpert.   

Abstract

Our ability to additively combine two learned internal models was investigated by studying the forces people generate when lifting objects with a precision grip. Subjects were required to alternately lift two objects of identical physical appearance but differing weight. Grip force scaling prior to lift-off was used to estimate the output of the internal model associated with each object. Appropriate internal models were formed when alternately lifting two objects of different weight. The objects were then combined by stacking them one upon the other, and the combined object was lifted. Results show that subjects can additively combine internal models of object dynamics but the sum is biased by a default estimate of the object's weight.

Entities:  

Mesh:

Year:  2004        PMID: 14714157     DOI: 10.1007/s00221-003-1730-z

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


  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.  Charpentier (1891) on the size-weight illusion.

Authors:  D J Murray; R R Ellis; C A Bandomir; H E Ross
Journal:  Percept Psychophys       Date:  1999-11

4.  Multiple paired forward and inverse models for motor control.

Authors:  D M Wolpert; M Kawato
Journal:  Neural Netw       Date:  1998-10

5.  Visual size cues in the programming of manipulative forces during precision grip.

Authors:  A M Gordon; H Forssberg; R S Johansson; G Westling
Journal:  Exp Brain Res       Date:  1991       Impact factor: 1.972

6.  The integration of haptically acquired size information in the programming of precision grip.

Authors:  A M Gordon; H Forssberg; R S Johansson; G Westling
Journal:  Exp Brain Res       Date:  1991       Impact factor: 1.972

7.  Control of grasp stability when humans lift objects with different surface curvatures.

Authors:  P Jenmalm; A W Goodwin; R S Johansson
Journal:  J Neurophysiol       Date:  1998-04       Impact factor: 2.714

8.  Modular decomposition in visuomotor learning.

Authors:  Z Ghahramani; D M Wolpert
Journal:  Nature       Date:  1997-03-27       Impact factor: 49.962

9.  Memory representations underlying motor commands used during manipulation of common and novel objects.

Authors:  A M Gordon; G Westling; K J Cole; R S Johansson
Journal:  J Neurophysiol       Date:  1993-06       Impact factor: 2.714

10.  Consolidation in human motor memory.

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

View more
  19 in total

1.  Evaluation of negative viscosity as upper extremity training for stroke survivors.

Authors:  Felix C Huang; James L Patton
Journal:  IEEE Int Conf Rehabil Robot       Date:  2011

2.  Augmented dynamics and motor exploration as training for stroke.

Authors:  Felix C Huang; James L Patton
Journal:  IEEE Trans Biomed Eng       Date:  2012-04-03       Impact factor: 4.538

3.  Manual skill generalization enhanced by negative viscosity.

Authors:  Felix C Huang; James L Patton; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2010-07-21       Impact factor: 2.714

4.  Sensorimotor memory of weight asymmetry in object manipulation.

Authors:  Lulu L C D Bursztyn; J Randall Flanagan
Journal:  Exp Brain Res       Date:  2007-10-24       Impact factor: 1.972

5.  Are there distinct neural representations of object and limb dynamics?

Authors:  N Cothros; J D Wong; P L Gribble
Journal:  Exp Brain Res       Date:  2006-03-09       Impact factor: 1.972

6.  Quantifying feedforward control: a linear scaling model for fingertip forces and object weight.

Authors:  Ying Lu; Seda Bilaloglu; Viswanath Aluru; Preeti Raghavan
Journal:  J Neurophysiol       Date:  2015-04-15       Impact factor: 2.714

7.  Probabilistic information on object weight shapes force dynamics in a grip-lift task.

Authors:  Leif Trampenau; Johann P Kuhtz-Buschbeck; Thilo van Eimeren
Journal:  Exp Brain Res       Date:  2015-03-12       Impact factor: 1.972

8.  Impaired anticipatory control of fingertip forces in patients with a pure motor or sensorimotor lacunar syndrome.

Authors:  Preeti Raghavan; John W Krakauer; Andrew M Gordon
Journal:  Brain       Date:  2006-04-05       Impact factor: 13.501

9.  Auditory and visual information do not affect self-paced bilateral finger tapping in children with DCD.

Authors:  Renuka Roche; Anna Maria Wilms-Floet; Jane E Clark; Jill Whitall
Journal:  Hum Mov Sci       Date:  2011-02-19       Impact factor: 2.161

10.  Stretching the skin immediately enhances perceived stiffness and gradually enhances the predictive control of grip force.

Authors:  Mor Farajian; Raz Leib; Hanna Kossowsky; Tomer Zaidenberg; Ferdinando A Mussa-Ivaldi; Ilana Nisky
Journal:  Elife       Date:  2020-04-15       Impact factor: 8.140

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.