Are there distinct neural representations of object and limb dynamics?

Cothros, Nicholas; Wong, Jeremy D.; Gribble, Paul L.

doi:10.1007/s00221-006-0411-0

Cited by 90 publications

(81 citation statements)

References 26 publications

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“…In addition, subjects showed no difficulty in transitioning between the two modes (e.g., practicing with device 1, practicing with device 2, testing with device 1, testing with device 2). Recent studies have shown that as long as an intuitive contextual cue is provided (in this case, replacing the terminal device), subjects are able to quickly adapt back and forth between modes [26][27]. Also, the nondisabled subjects' VO IOF scores were similar to those of the subjects with amputation, who had extensive experience using a prosthesis.…”

Section: Discussionmentioning

confidence: 88%

Comparison of body-powered voluntary opening and voluntary closing prehensor for activities of daily life

Berning

Cohick²,

Johnson³

et al. 2014

J Rehabil Res Dev

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Abstract-Persons with an upper-limb amputation who use a body-powered prosthesis typically control the prehensor through contralateral shoulder movement, which is transmitted through a Bowden cable. Increased cable tension either opens or closes the prehensor; when tension is released, some passive element, such as a spring, returns the prehensor to the default state (closed or open). In this study, we used the Southampton Hand Assessment Procedure to examine functional differences between these two types of prehensors in 29 nondisabled subjects (who used a body-powered bypass prosthesis) and 2 persons with unilateral transradial amputations (who used a conventional body-powered device). We also administered a survey to determine whether subjects preferred one prehensor or the other for specific tasks, with a long-term goal of assessing whether a prehensor that could switch between both modes would be advantageous. We found that using the voluntary closing prehensor was 1.3 s faster (p = 0.02) than using the voluntary opening prehensor, across tasks, and that there was consensus among subjects on which types of tasks they preferred to do with each prehensor type. Twenty-five subjects wanted a device that could switch between the two modes in order to perform particular tasks.

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Section: Discussionmentioning

confidence: 88%

Comparison of body-powered voluntary opening and voluntary closing prehensor for activities of daily life

Berning

Cohick²,

Johnson³

et al. 2014

J Rehabil Res Dev

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“…In limb dynamics studies, it has been shown that a learned movement that is acquired in one context may fail to transfer to a different context even when the movement and the force environment remain unchanged (Cothros et al, 2006;Nozaki et al, 2006). Moreover, subjects can adapt to multiple environments based on a change in context (Gandolfo et al, 1996;Osu et al, 2004;Wainscott et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

“…For example, subjects can simultaneously learn opposite force patterns if they are appropriately distinguished by contextual cues (Gandolfo et al, 1996;Osu et al, 2004;Wainscott et al, 2005). Similarly, a movement that is learned in one context may fail to transfer to a novel context even when the movement itself and the force environment are unchanged (Cothros et al, 2006;Nozaki et al, 2006). There is similar evidence of specificity in speech motor learning.…”

Section: Introductionmentioning

confidence: 96%

Specificity of Speech Motor Learning

Tremblay

Houle²,

Ostry³

2008

J. Neurosci.

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The idea that the brain controls movement using a neural representation of limb dynamics has been a dominant hypothesis in motor control research for well over a decade. Speech movements offer an unusual opportunity to test this proposal by means of an examination of transfer of learning between utterances that are to varying degrees matched on kinematics. If speech learning results in a generalizable dynamics representation, then, at the least, learning should transfer when similar movements are embedded in phonetically distinct utterances. We tested this idea using three different pairs of training and transfer utterances that substantially overlap kinematically. We find that, with these stimuli, speech learning is highly contextually sensitive and fails to transfer even to utterances that involve very similar movements. Speech learning appears to be extremely local, and the specificity of learning is incompatible with the idea that speech control involves a generalized dynamics representation.

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“…The individual behavioural elements may then be driven by separate networks that, however, share this model. Support for a separation of the body model from task-specific models has been provided by Cothros et al (2006). In the experiment people were trained to make targeted movements with their arms while holding a robotic device through which a novel force field was applied to the hand.…”

Section: Discussionmentioning

confidence: 99%

“…In the experiment people were trained to make targeted movements with their arms while holding a robotic device through which a novel force field was applied to the hand. While adaptation to a given force field has been observed many times before (Shadmehr and Mussa-Ivaldi 1994) and has been termed motor learning (Kawato 1999), Cothros et al (2006) studied adaptations to different force field and were especially interested how these adaptations influence each other. The result was that subjects who returned to a known force field were able to completely retain their previous learning.…”

Section: Discussionmentioning

confidence: 99%

Universally manipulable body models—dual quaternion representations in layered and dynamic MMCs

Schilling

2011

Auton Robot

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Surprisingly complex tasks can be solved using a behaviour-based, reactive control system, i.e., a system that operates without an explicit internal representation of the environment and the own body. Nevertheless, application of internal representations has gained interest in recent years because such internal representations can be used to solve problems of perception and motor control (sensor fusion, inverse modeling) and may in addition be applied to higher cognitive functions as are the ability to plan ahead. To endow such a system with the ability to find new behavioural solutions to a given problem in a broad range of possibilities, the internal representation must be universally manipulable, i.e. the model should be able to simulate all movements that are physically possible for the body given. Using recurrent neural networks, models showing this faculty have been proposed being based on the principle of mean of multiple computation (MMC). The extension of this approach to three dimensions requires the introduction of a joint angle representation which allows for computation of mean values. Here we use dual quaternions that are singularity-free and unambiguous which allow for shortest path interpolation. In addition, it has been shown that dual quaternions are the most efficient and most compact form for representing rigid transformations. The model can easily be adapted to bodies of

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Are there distinct neural representations of object and limb dynamics?

Cited by 90 publications

References 26 publications

Comparison of body-powered voluntary opening and voluntary closing prehensor for activities of daily life

Comparison of body-powered voluntary opening and voluntary closing prehensor for activities of daily life

Specificity of Speech Motor Learning

Universally manipulable body models—dual quaternion representations in layered and dynamic MMCs

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